High Frequency Electromagnetic Dosimetry (Artech House Electromagnetic Analysis)

High Frequency Electromagnetic Dosimetry

For a listing of recent titles in the Artech House Electromagnetic Analysis Series, turn to the back of this book.

High Frequency Electromagnetic Dosimetry David A. Sánchez-Hernández Editor

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Library of Congress Cataloging-in-Publication Data A catalog record of this book is available from the Library of Congress.

British Library Cataloguing in Publication Data A catalogue record of this book is available from the British Library. ISBN

978-1-59693-397-2

Cover design by Igor Valdman © 2009 ARTECH HOUSE, INC. 685 Canton Street Norwood, MA 02062 All rights reserved. Printed and bound in the United States of America. No part of this book may be reproduced or utilized in any form or by any means, electronic or mechanical, including photocopying, recording, or by any information storage and retrieval system, without permission in writing from the publisher. All terms mentioned in this book that are known to be trademarks or service marks have been appropriately capitalized. Artech House cannot attest to the accuracy of this information. Use of a term in this book should not be regarded as affecting the validity of any trademark or service mark.

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This book is dedicated to Lucía, Mario, Bruno, Irene, Paula, Marina, Javier, Juan, Pedro, Julia, and Helena, our breed, and to Marien, Sylvia, Marina, Lucía, Ángeles, Ana Belén, Marta, and Ana, our mates and family. They are our daily source of energy for smiling at life.

Contents Foreword

xi

CHAPTER 1 Introduction

1

1.1 1.2 1.3 1.4 1.5 1.6

Introduction 1 Exposure Scenarios 5 The Nature of the Interaction: Rationale for Limiting Exposure to EMF 7 International Scientific Messages 9 Risk Communication and Perception 11 The Reason for Writing this Book 13 References 16

CHAPTER 2 Fundamentals of Electromagnetic Fields Interaction with Matter 2.1 Introduction 2.2 Electromagnetic Dosimetry 2.2.1 Definition 2.2.2 Electromagnetic Fields and Matter 2.2.3 Specific Absorption Rate 2.3 Dielectric Properties 2.3.1 Measurement Techniques 2.3.2 Current Knowledge on Dielectric Properties 2.3.3 The Role of Tissue Dielectric Properties and Geometry on Electromagnetic Dosimetry 2.4 Heat Generation 2.4.1 Bioheat Equation 2.4.2 Thermal Properties of Human Tissues 2.5 Conclusions References

21 21 22 22 23 27 29 29 38 46 50 50 56 57 59

CHAPTER 3 Far-Field Numerical Electromagnetic Dosimetry

67

3.1 Introduction 3.2 Electromagnetic Exposure Evaluation and Compliance Testing 3.3 Human Body and Source Modeling 3.3.1 Human Body Model 3.3.2 Source Modeling

67 69 71 71 76

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Contents

3.4 Simulation Techniques References

82 85

CHAPTER 4 Near-Field Numerical Electromagnetic Dosimetry

93

4.1 Phantom and Source Modeling 4.1.1 Phantom Developments 4.1.2 Source Modeling 4.2 Simulation Techniques 4.2.1 Averaging Strategies 4.2.2 Meshing Strategies References

93 93 100 103 109 110 111

CHAPTER 5 In Situ Measured Exposure Assessment and Compliance Testing

121

5.1 Introduction 5.2 Preevaluation 5.3 Instrumentation for Measurement 5.3.1 Broadband Probes 5.3.2 Narrowband Equipment 5.3.3 Antennas 5.3.4 Digital Mobile Communications Measuring Instrument 5.4 Volunteer Studies 5.5 Accurate Far-Field Compliance Testing for 2G Measurements 5.5.1 Measurement Campaigns 5.5.2 Measurement Procedures 5.5.3 Base Station Activity Determination 5.5.4 Broadband Measurements 5.5.5 Data Acquisition and Evaluation of Compliance with Broadband Probes 5.5.6 Narrowband Measurements 5.5.7 Data Acquisition and Evaluation of Compliance with Narrowband Probes 5.6 Accurate Far-Field Compliance Testing for 3G Measurements 5.6.1 The Need for Measurements 5.6.2 The UMTS Downlink Signal References

147 153 153 154 158

CHAPTER 6 Near-Field SAR Measurements with Automated Scanning Systems

165

6.1 6.2 6.3 6.4 6.5

Introduction Dosimetric Assessment System SAR Assessment System Portable SAR Systems Sources of Inaccuracies References

121 124 126 126 128 129 132 132 134 134 137 140 143 144 146

165 167 167 169 171 172

Contents

ix

CHAPTER 7 The Effect of Metallic Objects on SAR Distributions 7.1 7.2 7.3 7.4 7.5 7.6 7.7

Introduction Perfectly Conducting Spectacles and Eye Implants Electrodes and Wire-Leads Pins Plates Rings, Piercings, and Auditory Implants Stents References

CHAPTER 8 Worldwide Standardization and Guideline Discrepancies 8.1 8.2 8.3 8.4

Introduction Extremities and Mass- and Time-Averaging Volume Averaging Regulations References

175 175 177 180 183 184 186 202 202

207 207 210 212 213 216

CHAPTER 9 Medical Applications of High Frequency Electromagnetic Energy

221

9.1 Electromagnetic Therapy and Hypothermia 9.1.1 Biological Response and Risk 9.2 Therapeutic Applications 9.2.1 Cardiac Treatments 9.2.2 Urological Pathologies 9.2.3 Gastric Pathologies 9.2.4 Tumor Ablation 9.2.5 Sleep Breathing Disorders 9.2.6 Endometrial Ablation 9.2.7 Assistance to Arthroscopic Surgery 9.2.8 Assistance to Lipoclasty 9.3 Conclusions and Future Research References

221 222 223 224 225 227 227 230 230 231 232 232 233

CHAPTER 10 Conclusions

237

References

240

Acronyms

243

About the Editor

249

About the Contributors Index

249 253

Foreword Since the 1990s there has been an explosive growth of mobile communications, with billions of subscribers around the world. Fourth generation systems are bringing broadband wireless internet access to the mobile user. The safety of electromagnetic fields has been the subject of much debate, originally concerned with fields from power lines and more recently with radiated power from handsets, laptops, and base stations. It is an emotive topic and it is important for protagonists on both sides of the debate to make sure that their opinions are drawn from in-depth study of the topic—it is all too easy to pick on the results of one study that confirm a strongly held personal opinion. Sometimes the press can use scientific terms loosely—for example, failing to make the distinction between electromagnetic fields and ionizing radiation is certain to lead to alarm amongst the public. Even specialists in the study of the effects of nonionizing radiation on the human body have differing opinions, and there are varying exposure limits and standards across the world. This is because the study of the effects of high frequency fields on the human body has many facets; frequencies of interest cover a vast range from HF through microwave to THz and infrared. Biological materials have frequency-dependant properties and the human body is not simple to model. The biological interactions may be thermal, from dielectric heating, or more complex nonthermal bioelectromagnetic effects. It is timely, therefore, to have an extensive treatment of the subject of high frequency electromagnetic dosimetry. The text before you is the result of exhaustive research and includes an excellent overview of the theory and practice of dosimetry systems. Such an authoritative source of information on the science behind, and engineering of, practical dosimetry systems has not been found before in a single volume. You will also find a summary of some of the main opportunities for application of RF and microwave frequencies in medical treatment, from treatment of hypothermia to surgery for cancer therapy. There is no doubt that with a fuller understanding of the interactions between high frequency electromagnetic radiation and the human body, and more precise characterization of such interactions, these applications will develop enormously. Prof I.D. Robertson University of Leeds April 2009

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CHAPTER 1

Introduction David A. Sánchez-Hernández

1.1

Introduction Recent decades have witnessed important advances in the technological development of applications with radiofrequency and microwave energy, which have lead to important cost reductions in an ever-increasing number of utilities in industrial, medical, commercial, research, and domestic environments. Nowadays, it is commonplace to find radiofrequency and microwave systems at home, in workplaces, cars, public transport, hospitals, schools, and virtually everywhere else, both outdoors and indoors. The services offered by wired and wireless networks have an ever-increasing complexity. Mobile phones are able to communicate through voice, SMS, pictures, or MMS, and also at high data rate transmissions for financial transactions or even real-time broadband Internet access. This development is seemingly unstoppable, yet at the same time, public fear about possible adverse effects to human health from electromagnetic radiation has also been growing in an exponential increasing reality, with a particular focus on the use of mobile phones and the location of base stations on the top of buildings in urban areas. In spite of social outcry against radioelectric emissions, the use of mobile phones is still exponentially growing around the globe. This is directly reflected in the increasing penetration ratios, with an increasing number of countries witnessing well over 100% penetration ratios in 2008. The general public receives information about new technologies typically from mass media. Sometimes information with little scientific relevance is presented as important, and it is relatively easy to find press and other media references related to radioelectric emissions and public health, an issue that has become recurrent and seems to remain prominent. As influence of mass media has increased in recent years, so has their responsibility when influencing decision-making procedures [1, 2]. Journalists are normally trained to improve the efficiency when broadcasting, controlling, and selling news to the general public, wherein the main aspects include: •

Facts, basic knowledge, and some correlations are presented in a summarized way—that is, in a black and white image, where gray scales are scarce. Scientific and technological discoveries, however, do not conform well to black and

1

2

Introduction

•

•

•

white scenarios as they contain many diverse aspects enriching the discovery in a usually complicated manner. When such discoveries are forced into a simple scenario, sometimes the delivered message is wrong. News can be created from opinions, and since the diversity of opinion is enormous, public opinion may change as the news creation process progresses. News is presented as an entertainment or amusement tool, and due to the inherent characteristics of leisure, bad news, even that which produces fear, is well received by the general public from the commercial point of view. Yet, the news is slow and inefficient in changing permanent habits, notwithstanding their ability to make people desire what other people or companies with responsibilities have to do. This responsibility relocation also happens at the news consuming stage, but with an artificial and virtual distance between the news consumer and the action being described on TV, heard on the radio, or written in the newspaper or on Web pages. Thus, journalists themselves believe their influence on the general public or individuals is not really so important, and that people are clearly able to distinguish between rigorous news and those broadcasted for entertainment.

In this complicated world of roles one has to add, however, that not only a well-trained journalist is required to transmit rigorous scientific news, but also a well-trained scientist/researcher. When delivering biorelated issues, sometimes good journalists have to distinguish between the results of a solo study, which cannot be generalized, and its replica studies, which are the ones from which scientific basis is derived for obtaining conclusions. Yet, the engineering way of doing science is different, and only proven, peer-reviewed and demonstrated facts get published. This diversity, which enriches science from the scientific point of view, makes scientific committees sometimes make decisions by voting, which is not really well understood by the general public or by mass media. Researchers also need to learn on result delivering techniques, not only to scientific and technical journals, which is essential to divulge science and technology, but also in a way that is comprehensible to the general public and the mass media. This includes avoiding technical jargon and complicated descriptions when addressing the mass media. There is certainly a lack of communication and risk perception tools employed in the electromagnetic dosimetry issue. Thus, it is not surprising the feeling of fear that remains in part of the population, who may see the new wireless technologies as a threat. To date, at frequencies and power levels used in mobile communications systems, any causal relationship between radioelectric exposure and adverse health effects has not been established for a continuous use of less than 20 years. Nevertheless, messages from scientific organizations worldwide that reaffirm this lack of causal-effect data for long-term exposure does not seem to get to people in the same proportion as those other messages with less scientific content and more sensationalist content. Governments, local administrations, and, of course, operators and service providers have the responsibility of introducing into mainstream society the appropriate scientific information about the new systems and technological advances.

1.1 Introduction

3

The innate nature of science and its way forward does not help at all. In the biomedical scenario, papers get published based upon hypotheses, and need to be replicated long before medical protocols are established and applied over a specific technique. Even when a technique is well established, only practice in the long term can ensure medical feasibility. There are many operational techniques which are discarded by other more recent and scientific ones. This is not well understood by the general public. It is not the intention of researchers to address the general public with scientific publications, but the wide availability of scientific tests cannot be avoided. This sometimes turns into misinterpretation of published results. The way that epidemiologic science progresses does not help either. When the causal relationship of an effect is not known, it is very important to gather epidemiological data on it. Mankind has obtained many successful advances through observation, such as epidemiologic studies, but the possibility of biasing and the inherent complexity of dealing with statistical data and its boundary conditions over assumptions are not normally considered by the profanes. Observational studies do not adjust to typical laboratory testing, with an absence of random, double blind, and placebo tests, which are considered to be the paradigm of rigorous science based on evidence. It is for this reason that the majority of epidemiological studies include a paragraph about the inherent observational deficiencies. Among the many available research project results, two recently published ones are of special interest, that of the STROBE and INTERPHONE projects. The international 3-year STROBE project [3] was aimed at reinforcing the rigor on both realization and interpretation of epidemiological studies. Specific detailed descriptions (as detailed as laboratory tests) are recommended, focusing the conclusions to be obtained upon the objective being defined, and identifying critical variables which could lead to different results and interpretation of results. Similarly, reference to similar works both reaching and not reaching the same conclusions are recommended to be included in the study, as well as identifying funding sources and possible conflicts of interest. A particular study which has been recognized worldwide as state-of-science and well reputed is that of the INTERPHONE project, for which partial results have being published in 2005, 2006, 2007, and 2008. The INTERPHONE project was intended to clarify whether the radiofrequency radiation emitted by mobile telephones is carcinogenic through large-scale transnational epidemiological studies. The project was also intended to avoid the typical sample and ambiguities problems of previous studies and to break new ground. With highly reputed partners and coordinated by the World Health Organization’s International Agency for Research on Cancer (IARC), INTERPHONE study results were eagerly awaited. INTERPHONE concentrated on three types of cancer: those associated with the parotid gland, those associated with glial and meningeal brain tissues (gliomas and meningiomas), and those associated with the vestibular part of the eight cranial nerve (acoustic neurinomas). The selection of these types was made because these tumors arise around those tissues that absorb the highest proportion of the RF energy from handheld mobile phones. Results from INTERPHONE are already available [4–12], but have not clearly solved the issue. The studies on the three tumor types have not provided conclusive results. Not all results were consistent with each other. One study found, among

4

Introduction

persons who had used cellular phones for 10 or more years, an increased risk for gliomas but not for meningiomas [5]. The increment was found to be of borderline statistical significance [9], and in the conclusions of the project identified to either causal or artifactual due to recall bias [10], related to differential recall between cases and controls [11]. This was reinforced by the fact that the increase was found for ipsilateral use, but a decrease was also found for contralateral use. Most studies did not found an association between use of a mobile phone, either in the short or medium term. Even in the largest of the INTERPHONE national studies published to date there are not enough cases among long-term users to conclude confidently whether or not there is a link between mobile phone use and any type of head or neck cancer. In consequence, in the latest INTERPHONE update, that of February 2008, the IARC reports little evidence in the main analyses for an overall association between mobile phone use and an increase in the incidence of head and neck tumors. The IARC now estimates that INTERPHONE includes approximately 1,100 acoustic-neurinoma cases, 2,600 glioma, 2,300 meningioma and their matched controls. This is considered sufficient to detect confidently a 50% risk increase linked to mobile phone use beginning 5 years or more before enrollment. So the eager anticipation of INTERPHONE’s results is not over yet. Manuscripts presenting results of the international analyses, based on much larger numbers of long-term and heavy users, are in preparation. If no conclusive association is found, then further studies could be questioned. Even if an association could be encountered for ipsilateral use of more than 10 years, the systems employed then (analog) and the power they used is no longer available for the handset. Consequently, the implications for today’s technologies could not be determined in a straightforward manner. Some authors are already questioning whether the effects of long-term and analog factors are mixed-up in the first handful of meat-analyses results being published [13]. Moreover, even in these and other international studies, it has been demonstrated that exposure assessment methods have a considerable potential for bias through exposure misclassification and may therefore not be valid in studies investigating possibly subtle changes in risk [8]. In this sense, chance findings are not discarded in some results [6]. Moreover, results from the INTERPHONE study have revealed some concern over researchers regarding the exposure assessment method for the epidemiological study. INTERPHONE researchers [8] have questioned both self-reported findings, based on questionnaire data, and findings based upon subscription data provided by network operators to be good enough to allow a detection of possibly only subtle changes in risk, and they have called for advanced techniques in follow-up studies. Other EU-funded research projects include REFLEX, THz-BRIDGE, CEMFEC, RAMP2001, GUARD, PERFORM-A, PERFORM-B, EMFnEAR, and EMF-NET. These and other non-EU projects are of great interest to biologist, engineers, and physicists, yet they are oriented towards the end-result, which is typically biology oriented. When studying the role of engineering in the problem, the WHO clearly identified the need to provide for an accurate exposure assessment that has to be repeatable and reproducible. This role was recently reinforced by a recent study on measured results using volunteers [14], jointly performed by ETH Zurich, University of Zurich, and the Nokia Research Center. Results in [14] show a 500% difference when comparing the exposure conditions in different human volunteers. The

1.2 Exposure Scenarios

5

relationship between exposure values and electromagnetic energy deposed in the body is named “electromagnetic dosimetry.” With such a disparity in exposure conditions, the amount of deposed energy for each study could be extremely different. There are already several guidelines about harmonization of electromagnetic dosimetry when performing research on the issue. Even these guidelines have some divergences [15–20]. This poses a big question on the way the scientific problem has been addressed from the electromagnetic dosimetry point of view. It is precisely this role of electromagnetic dosimetry and the vast amount of information in this area that is the seed of this book. It is the aim of this book to present the recent advances regarding high frequency electromagnetic dosimetry from a scientific and rigorous telecommunications engineering point of view; that is, to obtain advances regarding accurate exposure assessments. The aim is to provide the advanced reader (engineer, scientist, biologist, physicist) with a state-of-science description of the problem at a glance. Most of the potential readers are current scientific leaders in their communities, and many of them are questioned about the issue of EMF and health. While we believe that strong research is the appropriate way to understand the issue, this book is intended for those researchers, scientists, and engineers who are not doing research in the field but are interested in knowing more about it. In addition, any researcher would welcome the availability of an up-to-date compilation text like this one. Readers must not expect, however, detailed biological experiments and results, as only high frequency electromagnetic dosimetry is the key issue of the book. By understanding EMF dosimetry, biological experiments may be made repeatable and comparable, which is a must for science to progress.

1.2

Exposure Scenarios Two different exposure scenarios can be distinguished for mobile communications systems: that of the human head, due to the near-field radioelectric emissions from handsets, and the exposure of the general public or workers due to radioelectric emissions from base station antennas. Exposure to base station radioelectric emissions typically occur in the far-field, but it may also take place in the near-field. The diverse techniques and technical specifications limit the power transmitted by a mobile handset today, but the wide variety of commercial units and their use patterns make the analyses of human interaction with electromagnetic waves a complicated task depending upon many different variables. The fundamentals of electromagnetic field interaction with matter will be covered in Chapter 2. Due to both the popularity of mobile phone use and also the focusing effect of EMF-related risk perception issues on base station antennas and mobile handsets, it has received much more scientific attention than other sources of radioelectric emissions. Measurements carried out over mobile networks up to date all around the world have demonstrated that electromagnetic field levels for the general public at the street level, emitted by base stations transmitters, are some orders of magnitude lower than maximum permissible levels. Electromagnetic dosimetry associated with emissions from mobile phones, on the other hand, is higher than that from base stations due to their proximity to the user, and power limitations have been derived

6

Introduction

specifically for mobile handsets. Since mobile phones emit electromagnetic waves very near of the user’s head and cause a complex exposure environment which is difficult to measure, this problem has received more attention than that of the base station scenario. As it will be described in this book, both problems are equally complex and several different factors have to be taken into account for accurate and rigorous exposure assessment. Yet, while many references can be found in the scientific literature for the handset scenario, the base station scenario has not received comparable attention, and further, particular references to third generation systems are scarce. For the handset scenario, all mobile phones to be commercialized in the European Union or the United States have to undergo strict quality tests, including several wherein specific absorption rate (SAR) levels are evaluated and results have to conform to frequency-dependent preestablished safety limits. In the European Union the SAR evaluation results are normally provided by the manufacturer, while in the United States the Federal Communications Commission (FCC) regularly publishes the results so that users are well aware of this parameter when acquiring their units. For the base station scenario, maximum SAR values have been observed in regions of the human body like the chest or the back [21–23], different to those encountered for the first scenario, mainly due to either direct exposure or to reflections on nearby walls or buildings. In [21], for instance, three different user positions were studied, always at far-field distances, providing peak SAR values of 12.9, 8.2, and 2.45 mW/g, averaged over 1g, 10g, and the whole body, respectively, which is well below the limits recommended by the European Council. A 20-cm safety distance was established in [23] for several GSM1800 base station antennas with an input CW power of 10W when a person was located directly in front of the antenna’s main beam. Depending upon the specific EMF limit under study, near-field safety distances between 1 and 65 cm were found in [24] using automated scanning systems. These systems will be described in Chapter 6. In absolute terms, electric field levels emitted from base stations and evaluated as reference levels on human beings on the street are lower than those from mobile phones. Yet, the concern about base stations is greater than that of mobile phones. The explanation is simple: The nature of both elements is different. People can decide whether or not to use a mobile phone and which one they prefer, but nothing can be decided as far as general public is concerned about the installation of a base station near their home. In addition, people are well aware of the direct benefits of a mobile phone, but they do not perceive the same benefits from a base station installed at a few meters away from their homes. On the contrary, this base station can be the origin of their anxiety or even devaluate the price of their houses, which may be the cause for some of their real feelings, and it is certainly the subject of recent studies. With these arguments, it is understandable that people fiercely oppose the installation of new base stations in the vicinity of their houses, supported by something that can or cannot be guaranteed by scientific investigations. Far- and near-field numerical electromagnetic dosimetry will be explained in Chapters 3 and 4, respectively. Chapter 5 will describe in situ measured exposure assessment and compliance testing.

1.3 The Nature of the Interaction: Rationale for Limiting Exposure to EMF

7

1.3 The Nature of the Interaction: Rationale for Limiting Exposure to EMF Human beings have lived with natural radioelectric emissions from the beginning of time, and with artificial radioelectric emissions for more than one century, starting when Guglielmo Marconi invented the wireless telegraph. Microwaves and radioelectric emissions are presented in nature from the Sun, galaxies, and our own planet Earth. The Earth’s biosphere is characterized by its electric and magnetic fields and also by atmospheric discharges. Any body with a temperature higher than 0K (−273ºC) emits electromagnetic radiation as a result of the accelerations suffered by charged particles due to thermal vibration. This is known as the body’s thermal radiation. For example, the Earth emits a power density of up to 0.3 mW/cm2 at 300 GHz, assuming an averaged temperature of 293K (20ºC). Of course, the human body has a temperature higher than 0K, which means that it emits electromagnetic energy of around 0.3 mW/cm2 within the frequency range of 10 kHz to 300 GHz. Interest in the incidence of this kind of emissions on human health began with the development of the first artificial radioelectric systems. Since then some scientific organizations and institutions have investigated the possible effects (positive, innocuous, and negative) associated to the interaction of electromagnetic waves with human beings, animals, and the environment. Radioelectric emissions from mobile phones and base stations are just part of the story, but they can be evaluated and verified by measurement techniques and procedures established with general character with any source of radioelectric emission. It is well known that exposure to high intensity electromagnetic fields produces biological effects [25]. The diverse recommendations and guidelines established by international scientific committees share the same basis for the setup of a peak SAR limit averaged over the whole body so that exposure does not pose a threat to human health. It was shared knowledge that adverse behavioral effects could be observed in primates for exposure rates over ∼4 W/kg [25]. This limit was associated with the body thermal increment which could not be coped with by the primate’s thermoregulatory system. Assuming similar coupling mechanisms in human beings, a safety factor of 10 was established for workers (occupational exposure), and an additional factor of 5 (making a total of 50) for the general public, thus deriving the SAR limit of 0.08 W/kg, averaged over the whole body. These factors are intended to cover different situations, like preheated situations during exercise, increased thermal environment, humidity, thermal conditions in infants, sensitive people, or even the ingestion of drugs and alcohol. Before the guidelines were developed in the European Union and the United States, some experiments on human volunteers were performed, and this ∼4 W/kg value was confirmed to produce body thermal increments less than 1ºC. This already established averaged thermoregulation capacity for humans was reaffirmed as the correct threshold [26], although temperature measurements were only performed in the surface. Yet, while it is possible to be exposed at frequency values for which only parts of the body are resonant, as in the mobile communications scenario, local temperature increments and SAR values could well exceed those of the limit, yet the whole-body averaged value would not be surpassed and rectal temperature (assumed to equal core body temperature) may remain constant. These minor incre-

8

Introduction

ments were found particularly important in the hypothalamus of the primates [27], wherein only a 0.2ºC to 0.3ºC increment could alter he primate’s thermoregulation system. At the same time, skin could be heated up to ∼45ºC (10ºC to 15ºC increments) to start producing pricking pain [28, 29], and at least an increment of 3.5ºC is required in the brain to lead to physiological damage [30]. In contrast, oncological hyperthermia units try to get cancer cell temperatures rise up to ∼42ºC for an efficient treatment [31]. Thus, local SAR limits were also established. Here, the rationale for deriving local SAR limit values, excellently explained in [32, 33], is different for diverse committees’ guidelines with respect to the averaging in both time and space. Since the ratio of the local peak to whole-body averaged SAR is about 20:1, in the United States the guidelines for a 20-fold peak SAR limit was introduced, giving rise to a local SAR limit of 1.6 W/kg averaged over a cubic shape of 1g in mass (until a change in 2006). In the European Union, however, the restriction on eye effects was employed, which was demonstrated to be around 100 W/kg for the induction of lens opacities in rabbits. Since the human eye weighs approximately 10g, 10- and 50-fold safety factors were made equivalent to imposing local peak SAR limits of 10 and 2 W/kg averaged over 10g for occupational and general public exposure, respectively. This represents a 25-fold increase over the whole-body average SAR limit. Yet, an exception was made for the limbs, wherein a maximum of 4 W/kg was allowed over 10g of contiguous tissue, representing a 50-fold increase over whole-body averaged SAR. Time-averaging is 6 minutes in the European Union and was 30 minutes in the United States until 2006, when a frequency-dependent formula was employed for time averaging. In Canada, for instance, the guidelines of Safety Code 6 provide particular restrictions for the eye. Some specific worker eyesight test examination was originally proposed in Australia. These and other standardization differences will be explained in Chapter 8. In the same pot we have: (a) the diverse revisions to safety limits; (b) the fact that the rationale for limiting local peak SAR is not harmonized to specifically establish limits that ensure that local heating remains below thresholds for the induction of tissue thermal damage, given by a safety factor; and (c) the fact that the restrictions set up by the International Commission for Non-Ionizing Radiation Protection (ICNIRP) were established on the basis of nerve and muscle tissue stimulation by electric currents which are induced in the cells, which was assumed to be thresholded. Consequently, it is not strange that some recent papers are suggesting the establishment of more direct temperature-increase-based safety limits; in other words, to use directly the concept of thermal dose, which is the one directly involved with the potential damage. The idea is backed up by some recent studies providing body thermal increments over 1ºC for maximum allowable plane-wave exposure levels [34] or increments in SAR limits for near-field exposure scenarios [35, 36] when the subject wears specific metallic implants. Special care for these particular situations has recently been suggested, and in consequence the effects of metallic objects on SAR will be described in detail in Chapter 7. The recent availability of refined hybridized electromagnetic and heat- and mass-transfer equations has prompted the possibility for a revision of current safety limits, based on incident field exposure, to more precise thermal-based limits. In this way an enhanced accuracy would be provided for current safety factors and precautionary principle clauses [34]. In order to be able to accurately determine these limits for radiofre-

1.4 International Scientific Messages

9

quency exposure, rigorous exposure assessment methods hybridized to thermal modeling techniques including heat- and mass-transfer mechanisms, which have to include all possible mechanisms, have to be fully developed. Simulated thermal doses could then be compared to those producing tissue damage, and the advance on hybridization techniques, which started with very simple human model and thermal modeling, has achieved a rigorously level comparable to those of current electromagnetic models employed for deriving SAR limits.

1.4

International Scientific Messages Despite initial divergences, which took standardization bodies all throughout the world to propose different safety limits and their subsequent revisions of 1964 (IRPA), 1966 (IRE), 1974 (ANSI), 1982 (ANSI), 1984 (IRPA), 1988 (IRPA), 1998 (ICNIRP), 1999 (IEEE), 2002 (IEEE), 2003 (IEEE), 2004 (IEEE), 2005 (IEEE), and 2006 (IEEE), the different scientific committees have agreed that current whole-body averaged exposure safety limits are currently well settled for human health protection [37–40] and that these limits do not need, according to recent scientific literature, any additional revision. To date, the two main EMF standardization and recommendation bodies, the International Committee on Electromagnetic Safety (ICES) and the International Commission for Non-Ionizing Radiation Protection (ICNIRP), are working towards a single set of worldwide guidelines and standards [33], with the first results providing a put-into-market standard for handsets by the International Electrotechnical Commission (IEC) [41]. The direction of institutional messages since 1998 is towards ensuring citizens that health protection is well developed by current EMF safety limits; yet research programs are being approved due to the tremendous pressure by consumer associations and the recommendations to maintain research efforts made by the scientific committees themselves, and small amendments are approved for some EMF-related standards as more scientific knowledge becomes known on the issue. The European Commission, within the Vth and VIth Framework Programme, started several international R&D projects regarding electromagnetic fields and human health. Very recently an initiative of the EU has submitted the final report—that of the European Information System on ElectroMagnetic Fields (JRC-EIS-EMF)—which was requested by Directorate General of Health and Consumer Protection (SANCO) and Directorate General Enterprise (ENTERPRISE) to the Physical and Chemical Exposure Unit of the European Joint Research Centre at Ispra (Italy). The overall scope was to provide a common basis for decision makers to increase the coherence of the approaches taken in the various member states, help restore public confidence, and liaise to other initiatives like COST-284 and WHO-EMF. The European Scientific Committee on Toxicity, Ecotoxicity, and the Environment (CSTEE) has reaffirmed the validity of current radiofrequency and microwave EMF safety limits at the 27th plenary meeting (October 2001), the 33rd plenary meeting (September 2002), and the 35th plenary meeting (December 2002). In the last report the CSTEE found insufficient scientific evidence, with regard to thermal and nonthermal effects, for proposing alternatives to the technical annex for the EU

10

Introduction

Council Recommendation setting up basic restrictions and reference levels limiting the exposure to nonionizing radiation. These limits are based on the guidelines published by ICNIRP [25]. Yet, the CSTEE also established as high priority the need for of studies intended to improve the validity of assessment of human exposure—for example, the use of biomarkers—and those for theoretical modeling of possible mechanisms of interaction with biological systems. Upon the request of the European Commission, the Scientific Committee on Emerging and Newly Identified Health Risks (SCENIHR) has recently updated the previous opinion of the CSTEE with respect to whether or not exposure to electromagnetic fields (EMF) is a cause for human health concern [42]. The opinion is divided into frequency (f) bands, namely: radio frequency (RF) (100 kHz < f ≤ 300 GHz), intermediate frequency (IF) (300 Hz < f ≤ 100 kHz), extremely low frequency (ELF) (0 < f ≤ 300 Hz), and magnetic static (0 Hz), with a separate section for environmental effects. In the opinion of SCENIHR, the balance of epidemiologic evidence indicates that mobile phone use of less than 10 years does not pose any increased risk of brain tumor or acoustic neurinoma. Lack of data to derive certain conclusions is claimed for longer use, diseases other than cancer, and studies on children. With the available data, SCENIHR also concludes that: •

•

•

•

•

There is no increased risk for brain tumors in long-term users, with the exception of acoustic neurinoma for which there are some indications of an association. RF exposure has not consistently been shown to have an effect on self-reported symptoms (e.g., headache, fatigue, dizziness, and concentration difficulties) or general well-being. Studies on neurological effects and reproductive effects have not indicated any health risks at exposure levels below the ICNIRP-limits established in 1998. Animal studies have not provided evidence that RF fields could induce cancer, enhance the effects of known carcinogens, or accelerate the development of transplanted tumors. There is no consistent indication from in vitro research that RF fields affect cells at the nonthermal exposure level.

The World Health Organization has promoted the Electro Magnetic Field Project (EMF) where the human health effects from radioelectric emissions are being investigated [43]. WHO has identified the necessity for more investigation to evaluate the health risk and promotes investigations among those agencies with funding capability. To date, the following conclusions have been reached: •

•

Cancer. Evidence shows that it is improbable that exposure to mobile phones and base stations cause cancer. Given the widespread presence of base stations in the environment, it is expected that possible cancer clusters will occur near base stations merely by chance. Moreover, the reported cancers in these clusters are often a collection of different types of cancer with no common characteristics and hence are unlikely to have a common cause. Other effects. Few studies have investigated general health effects in individuals exposed to RF fields from base stations. This is because of the difficulty in

1.5 Risk Communication and Perception

•

•

•

11

distinguishing possible health effects from the very low signals emitted by base stations from other higher strength RF signals in the environment. Most studies have focused on the RF exposures of mobile phone users. No consistent evidence of altered sleep or cardiovascular function has been reported. Electromagnetic interference. The use of mobile phones near some medical devices like pacemakers or defibrillators, or near earrings may possibly cause interference. Risk of interference with navigating systems in aircrafts is also possible. Driving risks. The risk of mobile phone use is not only in the direct interaction of electromagnetic fields with human tissues but also in the appropriate use of these devices; for example, while driving vehicles [44–46]. Some countries have developed specific legislation to prevent the use of mobile phones while driving. Public perception of risks. Some people perceive risks from RF exposure as likely and even possibly severe. Several reasons for public fear include media announcements of new and unconfirmed scientific studies, leading to a feeling of uncertainty and a perception that there may be unknown or undiscovered hazards. Other factors are aesthetic concerns and a feeling of a lack of control or input to the process of determining the location of new base stations. Experience shows that education programs as well as effective communications and involvement of the public and other stakeholders at appropriate stages of the decision process before installing RF sources can enhance public confidence and acceptability.

These and other considerations regarding worldwide standardization discrepancies and regulations are dealt with in Chapter 8.

1.5

Risk Communication and Perception It is important to point out that the generalized use of nonscientific terms when speaking about radioelectric emissions—such as electrosmog and electromagnetic pollution—makes people assimilate ionizing and nonionizing radiation, avoiding the important basic differences between these two radiation types and even between radiations within these two types. One clear example is the differences between the magnetic fields created by high voltage electric lines and high frequency radioelectric emissions (e.g., those emitted by mobile phones, wherein the electric field dominates the interaction mechanism with matter). Other terms such as “electric Chernobyl” to refer to short-wave antenna fields or other nontechnical comparisons may stimulate fear or even catastrophic feelings in general public. The role of terms’ familiarity is important in current Western societies [47]. There is a general scientific culture about electricity since it represents a basic need, but in most countries the electric appliances provide light and not electricity, and the scientific knowledge of the general public about electromagnetic fields is not even that basic. This is due to the fact that electromagnetic fields cannot be touched, seen, or perceived in any way, with rare exceptions like the microwave hearing effect or the hair stimulation when in presence of high level electric fields. It is this hidden nature

12

Introduction

of EMFs which is one of the main reasons for people’s concerns, augmented by the fact that, as we have mentioned before, it is easily confused with other energy types, such as ionizing radiation. This blurred information does not aid the required clarification process for citizens. While the biological effects and the effects on health due to high intensity electromagnetic fields are well known and understood, the basic interaction mechanisms that serve as a basis for hypothetic effects of very low intensity electromagnetic exposure have not even been undoubtedly identified. Controversy over the existence of these low intensity effects is served between scientists, with physicists and engineers generally more skeptical than biologists and epidemiologists. The scientific basis for pursuing standardization and legislative actions, however, must be based on published peer-reviewed evidence, and to date the causal-effect relationship between adverse effects on human health of low intensity electromagnetic fields has yet to be demonstrated [40, 48]. In spite of this, one factor that augments citizen worries is their inability to be able to control the possible, if existent, risk, and the typical unawareness of the exposure. While people can choose when, how, and with which terminal they can make a call, the location of base stations is generally out of their scope. Consequently, risk perception is completely different in spite of a lower exposure generally found for the base station scenario compared to the mobile phone situation. In 1995 and 1996 the Harvard Center for Risk Analysis (HCRA) issued two reports on the variety of risks associated with electromagnetic fields [49]. As reproduced in Table 1.1, electromagnetic fields were perceived as the least suspected of the analyzed risks. The tremendous similarity in perception rates between X-rays and electromagnetic fields revealed a tendency of people to assimilate, even confound, these two, despite their inherent and important differences between the ionizing and nonionizing radiation types that these two energy sources represent. Another interesting conclusion was reached when the Spanish Association Against Cancer (AECC) published a survey regarding the public perception of risk associated to electromagnetic fields in Spain. The survey took place in early 2004 and covered the entire country. The survey was per-

Table 1.1

Risk Perception for Several Daily Activities Percent Top 1 2 Score (7-10) Mean Score

Heavy Smoking

90.0

9.1

Environmental Tobacco 71.9 Smoke

7.7

Ozone Depletion

63.2

7.1

Particles in Air

59.8

7.0

Global Warming

51.4

6.4

Radon

46.7

6.2

Medical X-Rays

38.8

5.6

Electric and Magnetic Fields

38.3

5.5

Relaxing Music

5.2

1.0

1. Percentage of responses equal to 7, 8, 9, or 10 on the 10-point scale. 2. Mean score of the 1,000 respondents.

1.6 The Reason for Writing this Book

13

formed by Demoscopia, a well-reputed survey specialist company. The results were made public by a report in an ad hoc extraordinary congress with a scientific panel of the outmost quality. The main conclusion was that, for the general public, the existence of a mobile communications base station was synonymous with cancer, with percentages that made this association greater the closer a user lived to the BS. Yet, the AECC also concluded that in the light of evidence there was no proven link between the two, that research must continue, and that current legislation is adequate to protect the public health. The interesting observation of the results came when a comparison between the answers to two questions was made. When the public was asked to assert whether living close to a BS poses a risk to human health, 52.1% answered yes. Interestingly enough, this percentage rose to 63.7% when the public was asked to assert whether electromagnetic fields are linked to cancer. This happened despite cancer being just one risk to human health, and a serious one. Or in other words, the first question was more general than the second, but the word “cancer” triggered some positive responses. In this sense several organizations are asking for more epidemiological data on long-term exposure to EMF, yet at the same time, concerns are also being published on the required rigor of these studies and the need to make them comparable and reproducible. At the same time, there are many medical applications that employ microwave energy which are common practice nowadays. The list includes bone healing, dental caries treatment, hyperthermia cancer treatment, and many therapeutic procedures. To obtain the whole picture regarding electromagnetic exposure to EMF, an update on the possibilities of existing therapeutic applications of high frequency electromagnetic energy and a description of future avenues currently under R&D is performed in Chapter 9.

1.6

The Reason for Writing this Book The risk perception about electromagnetic fields, evaluated by the HCRA, has changed in the last few years mainly due to the influence of mass media. In 1999 the National Radiological Protection Board (NRPB) in the United Kingdom provided different data. In the period under analysis, from August to October 1999, the NRPB received one-quarter of all queries related to risks presumably associated with electromagnetic fields, and from these queries a significant 41% were devoted to mobile communications base stations. The recently completed coordinating action by the EU on a “European Information System on Electromagnetic Fields Exposure and Health Impact,” developed through the Joint Research Center at Ispra (Italy), revealed that risk communication in the European Union has been significantly hampered by the absence of a clear strategy to promote cooperation among policy makers to exchange experiences, and to develop common approaches and coordinated communication actions on public health and EMF issues. More research is therefore needed in order to estimate with enhanced accuracy the differences between risk perception related to electromagnetic fields for the general public and for the scientific community. Even for the scientific community risk perception related to EMFs has a large variance [50].

14

Introduction

What is clear is the fact that communication between scientists, governments, telecommunication operators, and the general public has failed, and that new communication tools are required to recover the lost confidence of the general public on official statements by health protection agencies worldwide. The public demands information that can be trusted, and it deserves communication strategies that can make information understandable by cooperative schemes between governments, companies, scientists, researchers, and the general public. Increased dialogue is the way forward, and this book intends to put together some of the latest developments and issues that have been settled for quite some time through numerous papers with the scientific independence of electromagnetic dosimetry research. In this way we intend to address the issue of high frequency electromagnetic dosimetry from a rigorous engineering point of view. We have already mentioned that adverse behavioral effects could be observed in primates for exposure rates over ~4 W/kg, and a safety factor or 10 was established for workers (occupational exposure), and an additional factor of 5 (making a total of 50) for general public, thus deriving the SAR limit of 0.08 W/kg, averaged over the whole body. This general limit is shared by most guidelines worldwide. Yet, there are additional safety factors which are not mentioned for electromagnetic dosimetry. These additional safety factors include the following: 1. The human thermoregulatory model is certainly capable of coping with more absorbed energy that those of primates or rodents (Factor W). 2. The threshold limit was established for observed behavioral effects, which may not be a threat to health (Factor X). 3. The reference levels for evaluating external fields were calculated for the worst-case coupling scenario and plane waves, which is not normally the case (Factor Y). 4. Measurements performed to test whether the external fields conform to the safety limits are normally performed over worst-case traffic scenarios, or even extrapolated to account for technology-variables such as discontinuous transmission or power control [51], which again is not the usual exposure situation (Factor Z). Consequently, the safety factor for human health protection (depicted in Figure 1.1) is really, Safety Factor = W × X × 10 × 5 × Y × Z

(1.1)

Thus, knowing two out of six different safety factors means that there is still a large degree of uncertainty when ruling limits to electromagnetic dosimetry. In fact, the uncertainty lays mainly on hazardous thermal dose induced by EMF exposure. The thermal threshold values for discomfort have already been made dependent upon metabolic rate and weight, as well as on the tube-restrained mice conditions [52]. On top of this, the diverse safety factors help determining safety limits with a large overprotection, intended to cover special cases such as infants (for which the thermoregulatory model and electromagnetic coupling scenario is certainly different from adults), pregnant women [53, 54], or simply more sensitive people. Yet, with the current state of science the uncertainties could be reduced, which does not necessarily mean that the existing limits would be relaxed. In contrast, we could gain knowledge in how large are these safety factors, which in turn could help develop

1.6 The Reason for Writing this Book

15

0.0006 mW/cm2

Average value at street level (100m)

2

0.006 mW/cm Average value close to a BS (7m) 0.06 mW/cm2 0.8 mW/cm2 4 mW/cm2 40 mW/cm2 60 mW/cm2

No exposure Average exposure Average close exposure

Maximum value close to a BS (7m) ICNIRP max. permissible exposure limit Observable behavioral effects on primates Possible cytotoxic effects Possible risk to human health

High-frequency electromagnetic dosimetry

Maximum close exposure Maximum permissible exposure Behavioral effects exposure Potentially hazardous exposure Possible hazardous exposure

Figure 1.1

Safety factors for human health protection on EMF exposure.

novel applications. The use of thermal dose induced by accurate prediction of electromagnetic dosimetry is gaining acceptance for deriving more precise safety limits. In contrast, limits are normally evaluated today in the absence of a person; that is, in terms of external field values. According to the physical principle of the Grotthuss-Draper Law, a physical agent can only have an effect on the human body if it can get into it. Electromagnetic fields can certainly get into the human body. With electromagnetic fields recently having been treated legally as a physical agent in the European Union [55], this book clearly identifies current flaws on safety guidelines worldwide which can help in the reviewing processes. For instance, in a near-field scenario, it is more adequate to measure the amount of energy deposed on the human body and its ratios to the energies absorbed and dissipated through thermoregulation, as well as the specific temperature increments that the exposure to electromagnetic fields can provide, rather than incident electromagnetic fields due to the large amount of energy reflected and scattered. This is done despite the authors’ opinion that current guideline safety limits provide adequate protection levels to the general public with the scientific evidence that exists today, in agreement with numerous official statements. Yet, we believe that scientific rigor is the way to progress in a scientific discipline, and this book also tries to contribute to the response to the recent petitions of CSTEE to continue investigating in the field and of WHO to provide studies with reliable exposure assessments with improved accuracy and validity [39, 56]. With this in mind, this book is intended for engineers, physicists, researchers, biologists, and others who are not necessarily doing research on the field but are either interested by the problem or are frequently asked about it.

16

Introduction

The precise up-to-date compilation of information in this book provides an accurate, independent, and complete source of information at a glance. In addition, this book provides any researcher in the field is a detailed review of the state of science.

References [1] [2]

[3]

[4]

[5] [6]

[7]

[8]

[9] [10] [11] [12] [13] [14]

[15]

[16]

[17]

Wartenberg, D., and Greenberg, M., “Epidemiology, the press and the EMF controversy. Public understand,” SCI, Vol.1, pp. 383–394, 1992. Martínez-González, A.M., “Estudio y desarrollo de técnicas de evaluación de dosimetría electromagnética y de niveles de exposición a emisiones radioeléctricas,” Ph.D dissertation, February 2004 (in Spanish). von Elm, E., et al., “The strengthening the reporting of observational studies in epidemiology (STROBE) statement: Guidelines for reporting observational studies,” PLOS Medicine, Vol. 4, No. 10, pp. 1623–1627, October 2007. Berg, G., et al., “The assessment of radiofrequency exposure from cellular telephone daily use in an epidemiological study: German validation study of the international case-control study of cancers of the brain— INTERPHONE-Study,” J. Expo. Anal. Environ. Epidemiol., Vol. 15, No. 3, pp. 217–224, May 2005. Lonn, S., et al., “Swedish Interphone Study Group. Long-term mobile phone use and brain tumor risk,” Am. J. Epidemiol., Vol. 161, No. 6, pp. 526–535, March 2005. Schüz, J., et al., “Cellular phones, cordless phones, and the risks of glioma and meningioma (Interphone Study Group, Germany),” American Journal of Epidemiology, Vol. 163, No. 6, pp. 512–520, Jan. 2006. Sage, C., et al., “Personal digital assistant (PDA) cell phone units produce elevated extremely-low frequency electromagnetic field emissions,” Bioelectromagnetics, Vol. 28, pp. 386–392, 2007. Schüz, J., and Johansen, C., “A comparison of self-reported cellular telephone use with subscriber data: agreement between the two methods and implications for risk estimation,” Bioelectromagnetics, Vol. 28, pp. 130–136, 2007. Lahkola, A., et al., “Mobile phone use and risk of glioma in 5 North European countries,” Int. J. Cancer, Vol. 120, pp. 1769–1775, 2007. Hepworth, S.J., et al., “Mobile phone use and risk of glioma in adults: case-control study,” British Medical Journal, Vol. 15, pp. 883–887, April 2006. INTERPHONE Study, “Results update,” 25 September 2007. Cardis, E., et al., “Distribution of RF energy emitted by mobile phones in anatomical structures of the brain,” Phys. Med. Biol., Vol. 53, pp. 2771–2783, 2008. Rajakesari, S., “Cell phones and brain tumours,” EPIB671 Student Symposium, 2008. Boutry, C.M., et al., “Dosimetric Evaluation and Comparison of Different RF Exposure Apparatuses Used in Human Volunteer Studies,” Bioelectromagnetics, Vol. 29, pp.11–19, 2008. Beard, B.B., and Kainz, W., “Review and standardization of cell phone exposure calculations using the SAM phantom and anatomically correct head models,” Biomedical Engineering OnLine, Vol. 3, pp. 34–44, 2004. Apollonio, F., et al., “Definition and development of an automated procedure for narrowband measurements,” Radiation Protection Dosimetry, Vol. 97, No. 4, pp. 375–381, 2001. Barbiroli, M., et al., “Evaluation of exposure levels generated by Cellular systems: methodology and results,” IEEE Transactions on Vehicular Technology, Vol. 51, No. 6, pp. 1322–1329, 2002.

1.6 The Reason for Writing this Book

17

[18] Anderson, V., and McIntosh, R., “Guidelines for the RF exposure assessment of metallic implants,” in International EMF Dosimetry Handbook, available at http://www.emfdosimetry.org/. [19] Kuster, N., et al., “Guidance for exposure design of human studies addressing health risk evaluations of mobile phones,” Bioelectromagnetics, Vol. 25, pp. 524–529, 2004. [20] Kuster, N., et al., “Methodology of Detailed Dosimetry and Treatment of Uncertainty and Variations for InVivo Studies,” Bioelectromagnetics, Vol. 27, pp. 378–391, 2006. [21] Bernardi, P.; Cavagnaro, M.; Pisa, S.; Piuzzi, E.; “Human exposure to radio base-station antennas in urban environment,” IEEE Transactions on Microwave Theory and Techniques, 2000, Vol. 48, No. 11, pp. 1996–2002, 2000. [22] Lautru, D., et al., “Calculation of the power deposited in a phantom close to a base station antenna using a hybrid FDTD-MoMTD approach,” 30th European Microwave Conference, Paris, pp. 304–307, 2000. [23] Bahr, A., et al., “Occupational safety in the near field of GSM base stations,” 2000 International Millennium Conference on Antennas & Propagation (AP-2000), Davos, Switzerland, 2000. [24] Cooper, J., et al., “Determination of safety distance limits for a human near a cellular base station antenna, adopting the IEEE standard or ICNIRP guidelines,” Bioelectromagnetics, Vol. 23, pp. 429–443, 2002. [25] International Commission for Non-Ionizing Radiation Protection, “Guidelines for limiting exposure to time-varying electric, magnetic, and electromagnetic fields (up to 300 GHz),” Health Physics, Vol. 74, pp. 494–522, 1998. [26] Michaelson, S. M., and Elson, E. C., “Modulated fields and “window” effects,” Biological Effects of Electromagnetic Fields, Boca Raton, FL, CRC Press, pp. 435–533, 1996. [27] Adair, E.R., Adams, B.W., and Akel, G.M., “Minimal changes in hypothalamic temperature accompany microwave-induced alteration of thermoregulatory behavior,” Bioelectromagnetics, Vol. 5, pp. 13–30, 1984. [28] Hardy, J.D., “The nature of pain,” J. Chronic Dis., Vol. 4, No. 22, 1956. [29] Morita, M., Hirata, A., and Shiozawa, T., “Temperature increases in the human head exposed to EM waves emitted from a dipole antenna at various microwave frequencies,” Proc. OFSET 2000, Osaka, Japan, pp. 283–286, Dec. 2000. [30] Guyton, A.C., and Hall, J.E., Textbook of Medical Physiology, Philadelphia, PA: Saunders, Ch. 73, 1996. [31] Spiegel, R.J., “A review of numerical models for predicting the energy deposition and resultant thermal response of humans exposed to electromagnetic fields,” IEEE Transactions on Microwave Theory and Techniques, Vol. 32, pp. 730–746, 1984. [32] Lin, J.C., “Safety standards for human exposure to radio frequency radiation and their biological rationale,” IEE Microwave Magazine, pp. 22–26, Dec. 2003. [33] Adair, E.R., and Petersen, R.C., “Biological effects of radio-frequency/microwave radiation,” IEEE Transactions on Microwave Theory and Techniques, Vol. 50, No. 3, pp. 953–962, March 2002. [34] McIntosh, R.L., Anderson, V., and McKenzie, R.J., “A numerical evaluation of SAR distribution and temperature changes around a metallic plate in the head of a RF exposed worker,” Bioelectromagnetics, Vol. 26, pp. 377–388, 2005. [35] Virtanen, H., Huttunen, J., Toropainen, A., and Lappalainen, R., “Interaction of mobile phones with superficial passive metallic implants,” Physics in Medicine and Biology, Vol. 50, pp. 2689–2700, 2005. [36] Fayos-Fernández, J., Arranz-faz, C., Martínez-González, A.M., and Sánchez-Hernández, D., “Effect of pierced metallic objects on SAR distributions at 900 MHz,” Bioelectromagnetics, Vol. 27, pp. 337–353, 2006. [37] Scientific committee on toxicity, ecotoxicity and the environment (CSTEE), “Opinion on possible effects of electromagnetic fields (EMF), radio frequency fields (RF) and microwave

18

Introduction

[38]

[39]

[40] [41]

[42]

[43] [44] [45] [46] [47]

[48] [49] [50]

[51]

[52]

[53]

[54] [55]

radiation on human health,” Brussels, C2/JCD/csteeop/EMF/RFF30102001/D(01), Oct. 2001. Scientific committee on toxicity, ecotoxicity, and the environment (CSTEE), “Opinion of the CSTEE on effects of electromagnetic fields on health,” Brussels,C2/AST/csteeop/EMF 24092002/D(02), Sept. 2002. Scientific committee on toxicity, ecotoxicity, and the environment (CSTEE), “Opinion of the CSTEE on effects of electromagnetic fields on health-appendix to the opinion expressed on 24 September 2002,” Brussels,C2/VR/csteeop/EMF 17122002/D(02), Dec. 2002. WHO Fact Sheet no. 374, “Electromagnetic fields and public health base stations and wireless technologies,” May 2006. IEC 62209-1, “Human exposure to radio frequency fields from hand-held and body-mounted wireless communication devices, Part 1: procedures to determine the specific absorption rate (SAR) for hand-held devices used in close proximity to the ear (frequency range of 300 MHz to 3 GHz),” February 2005. Ahlbom, A., et al., “Possible effects of electromagnetic fields (EMF) on human health—Opinion of the Scientific Committee on Emerging and Newly Identified Health Risks (SCENIHR),” Toxicology, Vol. 246, pp. 248–250, March 2008. UNEP/WHO/IRPA, “Electromagnetic fields (300 Hz to 300 GHz). Environmental Health Criteria 137,” World Health Organization, Geneva, 1993. Strayer, D.L., Johnston, W.A. & Grison, S., “Driven to distraction: studies of driving and cellular phone use,” Psychonomic Soc., Vol. 4, No. 16 (Conference Abstract), 1999. Brookhuis, K.A, De Vries, G. & Waard, D., “The effects of mobile telephoning on driving performance,” Accid. Anal. Prev., Vol. 23, No. 309, 1991. Violanti, J.M., “Cellular phones and fatal traffic collisions,” Accid. Anal. Prev., Vol. 29, No. 265, 1998. Arbete Och Hälsa Vetenskaplig Skriftserie (National Swedish Institute of Working Life). “Industrial relations and social affairs. Possible health implications of subjective symptoms and electromagnetic fields. A report prepared by a European group of experts for the European Commission, Directorate General V Employment, public health analysis, policy and programme coordination and development,” 1997. WHO, “The international EMF projects: Progress report 2003-2004,” World Health Organization, Geneva, Switzerland, 2004. Harvard Center for Risk Analysis, “Workers, EMFs and cancer,” Report Vol. 3, No. 2, Boston, Mass, U.S.A., 1995. Covello, V., “Educating and informing the public about radiation risks: A review of obstacles to public understanding,” OECD Workshop on Public Understanding of Radiation Protection Concepts, Paris, 1987. Martínez-González, A.M., et al., “Practical procedure for verification of compliance of digital mobile radio base stations to limitations of exposure of the general public to electromagnetic fields,” IEE Proceedings on Microwaves, Antennas & Propagation, Vol. 149, pp. 218–228, 2002. Ebert, S., et al., “ Response, thermal regulatory threshold and thermal breakdown threshold of restrained RF-exposed mice at 905 MHz,” Phys. Med. Biol., Vol. 50, pp. 5203–5215, 2005. Kainz, W., et al., “Calculation of induced current densities and specific absorption rates (SAR) for pregnant women exposed to hand-held metal detectors,” Phys. Med. Biol., Vol. 48, pp. 2551–2560, 2003. Dimbylow, P., “SAR in the mother and foetus for RF plane wave irradiation,” Phys. Med. Biol., Vol. 52, pp. 3791–3802, 2007. “Directive 2004/40/EC of the European Parliament and of the Council of 29 April 2004 on the minimum health and safety requirements regarding the exposure of workers to the risks arising from physical agents (electromagnetic fields) (18th individual Directive within the meaning of Article 16(1) of Directive 89/391/EEC,” Official Journal of the European

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19

Union, L 159 of 30 April 2004, Corrigenda in Official Journal of the European Union L 184 of 25 May 2004. [56] Repacholi, M.H., and van Deventer, T.E., “WHO policy framework: A case study on electromagnetic fields,” Workshop on Guiding Public Health Policy Options in Areas of Scientific Uncertainty, Ottawa, Canada, 11–15 July, 2005.

CHAPTER 2

Fundamentals of Electromagnetic Fields Interaction with Matter Alejandro Díaz-Morcillo, Juan Monzó-Cabrera, and Miguel A. García-Fernández

2.1

Introduction Since the seventeenth century, when Otto von Guericke developed the first electrical machine, and with the continuous electronic technology development ever since, human interest in physics as a science and its relation to the electrical phenomena and their biological effects has been increasing. In 1941 a team of physicists and engineers measured the absorbed energy in a patient during a diathermy process, wherein an electrical current was applied to produce heating over the patient’s ill parts, and estimated that this energy was roughly 5%. Results were expressed in absorbed energy per volume (W/liter), which is similar to the magnitude actually employed to quantify the absorbed electromagnetic energy by biological tissues, the specific absorption rate (SAR), expressed in W/Kg and usually normalized to 1W of transmitted power. During the first half of the twentieth century, radiofrequency energy found many applications in industry, science, medicine, communications, transport, and defense, among others. Radiofrequency heating effects have been successfully used in cancer treatment, physiotherapy, and food and industry heating applications such as wood manufacturing, leather drying, or rubber vulcanization processes applied to the automobile or footwear industries. With the arrival of new, more powerful radiofrequency energy sources, the potential risks associated with human exposure to electromagnetic fields also increased, and this brought the necessity of developing appropriate security regulations, as well as standardized measurement and exposure evaluation techniques. In June 1993, David Reynard, of the United States, sued the mobile phone company where his wife bought the mobile phone. According to him, the use of the mobile phone caused or aggravated his wife’s brain cancer, which was the final cause of her death. The David Reynard affair received a large amount of radio, television, and press coverage in the United States, and it is now perceived as the first alarm in modern times of public concern related to human health and the exposure to electromagnetic fields, particularly those produced by mobile phone usage. U.S. courts did not find in his favor, considering that there was no conclusive proof that

21

22

Fundamentals of Electromagnetic Fields Interaction with Matter

associated the use of the mobile phone and the brain cancer developed by his wife. Nevertheless, an important debate began about the health security offered by mobile phones, and the mobile phone and mobile communications industry witnessed a fundamental questioning of the health risks posed by its technology. It is not the aim of this book to raise these issues, but rather to engineer them. Since there is a vast number of papers and books related to the basic fundamentals of human interaction with electromagnetic fields, this chapter will only briefly describe the most important parameters, with specific interest devoted to the role of dielectric properties on final electromagnetic dosimetry evaluation. An advanced reader is referred to the references at the end of the chapter for further details.

2.2

Electromagnetic Dosimetry 2.2.1

Definition

Electromagnetic dosimetry establishes the relationship between an electromagnetic field distribution in free space and the induced fields inside biological tissues, generally the human body. Mobile phones, and other portable devices used in mobile communications systems, emit radiofrequency energy, which may be as low as a few watts (W) in the case of some mobile phone terminals and as high as a hundred of watts for some mobile phone stations. In normal operation conditions, mobile phones cause a higher exposure level than mobile phone stations, although radiated power for these devices is usually lower than 10W. This is mainly due to the immediate vicinity of the radiofrequency (RF) source for mobile phones with users’ vital organs, particularly the brain. For mobile base stations the exposure level is normally reduced by the distance from the user to the source of energy. In Western countries, until 1982 the exposure to radiofrequency electromagnetic fields in the band of 100 kHz to 100 GHz was quantified in terms of the incident power density measured in Watts/m2. Actual exposure to electromagnetic fields in the band of 3 kHz to 300 GHz is quantified in terms of electric field, magnetic field, and incident power density according to several standardization guidelines [1, 2]. The absorption phenomenon is different when exposure occurs in the near-field region or in the far-field region of the electromagnetic fields. In the close vicinity of a radiofrequency source, the fields are complicated and power density is not defined in this situation since only one direction of incidence simply does not exist. Nevertheless, for most user positions, portable devices provide a radiofrequency exposure only a few centimeters away from the source. At locations close to the source, the direction of propagation of radiofrequency energy is not the Pointing vector direction, which is defined in the far-field region as r 1r r P = E × H* 2

(2.1)

r r where E is the electric field intensity and H * the complex conjugate of the magnetic field intensity. Complex numerical tools or near-field probes are required for proper evaluation of the exposure in these scenarios. Exposure in the far-field region is quite different;

2.2 Electromagnetic Dosimetry

23

it is limited in terms of the electromagnetic field that is present in absence of the human body and assuming plane wave interaction and coupling, and has to be evaluated according to some well-defined procedures [3, 4]. For low frequencies, the human body absorption is low. For higher frequencies, the absorbed energy increases up to the maximum value. For an adult human body this occurs at resonance frequency between 30 and 80 MHz (depending upon the height). When an electromagnetic wave arrives at the human body in far-field conditions with linear z-axis polarization, it can induce electric currents when the wavelength is 1.5 to 5 times the individual height depending on the isolation conditions [5, 6]. Thus, in the far-field region, frequency, polarization, and the body dimensions constitute fundamental parameters for evaluating the radiofrequency energy absorption [7]. But since the human body does not have magnetic materials, it does not absorb significant amounts of magnetic energy. The human body is formed basically of water, electrolytes, and molecules with a dipolar momentum which is able to interact with the electric field. Consequently, the human body extracts the energy from an electromagnetic field mainly by its ionic activity [8]. 2.2.2

Electromagnetic Fields and Matter

For an exhaustive analysis of the electromagnetic problem defined by a radiating source and an exposed body, the well-known Maxwell equations must be solved, r r ∂B (2.2) ∇×E= − ∂t r r r ∂D (2.3) ∇×H = J+ ∂t r (2.4) ∇ ⋅D = ρ r ∇⋅B = 0

(2.5)

r r where D is the electric flux density, the magnetic flux density, ρ the volumetric B r density of electric charge, and J the surface density of electric current. These equations relate the electric and magnetic fields, and these with the electric charges and currents in the domain of the problem. Maxwell equations are complemented by the so-named constitutive relations, r r (2.6) D = εE r r (2.7) B = μH which introduce the material electromagnetic properties in the problem (i.e., the electric permittivity ε [F/m] and the magnetic permeability μ [H/m]). Basically, the electric permittivity provides a description of the macroscopic interaction between the electric field intensity vector and the dielectric material, whereas the magnetic permeability describes the interaction of the material with the magnetic field. Tak-

24

Fundamentals of Electromagnetic Fields Interaction with Matter

ing into account these relationships, (2.2) through (2.5) can be rewritten for the frequency domain as r r (2.8) ∇ × E = − jωμH r r r ∇ × H = σE + jωεE

(2.9)

r ∇ ⋅ εE = ρ

( )

(2.10)

r ∇ ⋅ μH = 0

(2.11)

( )

where ω is the angular frequency. By applying the curl operator on (2.8) r r r r ∇ × ∇ × E = jωμ∇ × H = − jωμ J + jωεE

(

)

(

)

(2.12)

(2.8) and (2.9) can be uncoupled, and the problem is set up by means of the vector wave equation with its electric field formulation, r r r ∇ × ∇ × E − ω 2 μεE = − jωμJ

(

)

(2.13)

In the same manner, the application of the curl operator on (2.9) leads to the vector wave equation for magnetic field formulation, r r r J (2.14) ∇ × ∇ × H − ω 2 μεH = ∇ × ε

(

)

Materials involved in dosimetry simulations (human tissues and different clothes: cotton, silk, leather, etc.) are nonmagnetic, and therefore, their magnetic −7 permeability is the vacuum one (μ = μ0 = 4π · 10 H/m). This points out the electric permittivity as the key material property for determining the electromagnetic field distribution in the body under study and, therefore, the power dissipated in it. The negligible anisotropy of human tissues and fabrics simplifies the general tensor form of the electric permittivity into a scalar and complex magnitude, ε = ε 0 ( ε ′ − jε ′′ )

(2.15)

where ε 0 = 8.854 × 10 −12 F/m is the electric permittivity of the vacuum, ε ′ the dielectric constant, and ε ′′ the loss factor. The relative electric permittivity ( r) is often used in the specialized literature, since it is a dimensionless quantity, εr =

ε = ε ′ − jε ′′ = ε ′(1 − j tan δ) ε0

where tan δ is the dielectric loss tangent.

(2.16)

2.2 Electromagnetic Dosimetry

25

It is generally admitted that the dielectric constant expresses the ability of the material to store electric energy and the loss factor (or the loss tangent) describes the energy dissipation due to polarization mechanisms within the dielectric [9]. This dissipation of electromagnetic energy and the resulting heat generation can be explained by the friction of microscopic dipoles at molecular or atomic level, produced when an electric field is applied and the dipoles try to follow the field variations, as Figure 2.1 shows. It is usual to extend the meaning of the electric permittivity in order to take into account not only dielectric dissipation, but also conduction or ohmic losses, since separation of both effects is normally not possible. By applying the Ohm law, r r (2.17) J = σE in (2.13), the homogeneous vector wave equation is obtained, r σ⎞ r ⎛ ∇ × ∇ × E − ω 2 μ⎜ ε − j ⎟ E = 0 ⎝ ω⎠

(

)

(2.18)

By comparing with (2.13) the new or effective electric permittivity is given by ε ef = ε − j

σ ω

(2.19)

Thus, while conduction does not affect the dielectric constant, it modifies the loss factor, ⎛ σ ⎞ ε ef = ε 0 ⎜ ε ′ − jε ′′ − j ⎟ = ε 0 ε ′ef − jε ′′ef ωε ⎝ 0⎠

(

)

(2.20)

where ε ′ef = ε ′

Figure 2.1

Dipole microscopic reorientation in dielectric materials.

(2.21)

26

Fundamentals of Electromagnetic Fields Interaction with Matter

ε ′′ef = ε ′′ +

σ ωε 0

(2.22)

As it is observed in (2.22), the effect of ionic conductivity is inversely proportional to operating frequency. From these new parameters an effective loss tangent can be defined, tan δ ef =

ε ef′′ ε ef′

(2.23)

Usually electric conductivity is preferred to express material losses, mainly for SAR calculations. It is possible to define an effective conductivity that takes into account the dielectric losses by relating it with the effective loss factor, ε ′′ef =

σ ef ωε 0

→ σ ef = ωε 0 ε ef′′ = ωε 0 ε ′ef tan δ ef

(2.24)

These effective parameters will be used throughout the chapter, eliminating the subindex for the sake of simplicity. An interesting phenomenon related to conductivity is the skin effect. It is normally related with electric conductors and can be defined as the tendency of a high frequency electric field to distribute itself within a conductor so that the current density near the surface is much greater than that at its core, with an exponential decrease x

r r −δ p J = J0 e

(2.25)

r where J 0 is the current density at the surface, and δp is the so-named penetration depth. For electric conductors the penetration depth can be obtained as δp =

1 πfμσ

(2.26)

This phenomenon can be generalized to any lossy material, not only conductors. For a lossy dielectric material, the penetration depth is given by δp =

1 2 ⎤ μ0 ε0 ε′ ⎡ ⎛ ε ′′ ⎞ ω ⎢ 1 + ⎜ ⎟ − 1⎥ ⎝ ε′ ⎠ 2 ⎢⎣ ⎥⎦

(2.27)

Taking into account that tan δ < 1 for biological tissues, (2.27) shows that the dielectric constant ε ′ determines the penetration of the wave in the body. Once the electric field distribution in the problem is known, the heat generated per volume unit and time unit [W/m3] by the radiofrequency energy (i.e., the absorbed power per volume unit) can be expressed, from (2.1), as

2.2 Electromagnetic Dosimetry

27

r 2 Q gen ( x , y, z ) = πfε 0 ε ′′( x , y, z ) E( x , y, z )

(2.28)

where x, y, z are the Cartesian coordinates of an arbitrary reference system containing the human body. Alternatively, this power can be obtained from the conductivity of the material as Q gen ( x , y, z ) =

r 2 1 σ( x , y, z ) E( x , y, z ) 2

(2.29)

The total power absorbed inside the object or body can be obtained by integrating throughout the whole object, r 2 P = πfε 0 ∫ ε ′′( x , y, z ) = E( x , y, z ) dV

(2.30)

V

Roughly, the electric field distribution is mainly determined by the dielectric constant ε ′ whilst the quantity of absorbed power for a given electric field distribution depends mainly on the loss factor ε ′′. 2.2.3

Specific Absorption Rate

When dealing with health issues in the near-field between 100 kHz and 10 GHz, and in order to prevent whole-body heat stress and excessive localized heating of tissues, it is usual to provide basic restrictions on specific absorption rate (SAR) values. SAR is defined as the time rate at which energy is deposited in any kind of material per unit of mass; that is, the power absorbed by the tissue per unit of mass. Thus, SAR is the parameter employed to quantify the electromagnetic absorption inside biological tissues like human body. It is also defined as the ratio between the infinitesimal amount of radiofrequency power absorbed in the infinitesimal mass of tissue surrounding a specific point. In other terms, SAR can be seen as the velocity at which the human body absorbs the electromagnetic energy. In practice SAR is normalized to the maximum radiated power and, from (2.29), is related with the electric field by SAR =

σ r2 E ρ

(2.31)

r 3 where ρ is the tissue density [kg/m ] and E refers to the rms electric field value [10]. SAR can also be defined as the time derivative of the absorbed energy by a differential element of mass contained in a differential volume with a known density [11] by SAR =

d ⎛ dW ⎞ d ⎛ dW ⎞ ⎜ ⎟ ⎜ ⎟ = dt ⎝ dm ⎠ dt ⎝ ρdv ⎠

(2.32)

Should total RF absorbed power need to be calculated, the following integral has to be solved:

28

Fundamentals of Electromagnetic Fields Interaction with Matter

P=

∫ SARdm = ∫ SARρdV

M

(2.33)

V

where M is the total mass for the organ under study, which can be the human body. The time integral of SAR is known as specific absorption (SA), and it is evaluated as the relationship between the electromagnetic field energy (EMF) energy [dW] absorbed by a differential mass element (dm). SA =

dW dm

(2.34)

These concepts of SA and SAR have been inherited by medical science, which uses them routinely for the treatment of tumors with ionizing radiation, yet with a dosimetric concept essentially different to the one employed in the radioelectric scenario. SAR also has a relationship to other parameters, such as the induced current density in biological tissues as a consequence of their exposure to electromagnetic energy. Hence, another way of evaluating SAR is by SAR =

J2 ρσ

(2.35)

2

where J is expressed in A/m . Due to the induced currents, the biological tissues suffer a temperature increase. SAR is also related to this increment, and in the linear stage wherein no thermoregulation process takes place, no heat diffusion is accounted for and there is no heat loss, this relationship can be expressed by SAR = c

ΔT ΔT ≅ 4186c H Δt Δt

(2.36)

where c is the specific heat of the tissue in J/kgK, cH is the specific heat capacity in kcal/kgK, 4186 is the figure that converts kilocalories to Joules, ΔT is the temperature increment in K, and Δt is the exposure time in seconds. From all these definitions for SAR it is clear that the RF energy absorption phenomenon in the human body is a very complex issue. On the one hand, tissue conductivity depends on both frequency and tissue constitution [12]. σ = σ( x , y, z, f )

(2.37)

Moreover, conductivity also depends on temperature, as we will see in Section 2.3.2. The volumetric tissue density, on the other hand, also changes with tissue type since it is a water-content dependent variable. The electric field inside the tissue depends upon many other factors, such as the dielectric properties, shape, size, orientation, polarization and frequency, source configuration, and exposure environment, among others. On top of this, (2.31) to (2.35) are only valid for sinusoidal fields in permanent state, and since it is usual that an electric field in mobile communications has a temporal variation different to a continuous wave (CW), and modulated through complex procedures, the above formulas could be used for well-defined worst-case scenarios only. Evaluating the exposure is particularly diffi-

2.3 Dielectric Properties

29

cult for spread spectrum signals, such as in the Universal Mobile Telecommunication System (UMTS), with code division multiple access (CDMA) technology, wherein proper evaluation is only achieved if conductivity values for all employed frequencies are used. Despite these difficulties, SAR is widely accepted by the main normalization and standardization agencies as the magnitude of reference for limiting the exposure to electromagnetic fields in the near-field. Using SAR to limit EMF exposure steals part of the main role of incident electromagnetic fields; that is, it highlights the fact that it is a near-field situation rather than a far-field one. Despite the simplification that could arise from using field imitations in the near-field, the complexity of field values in the near-field region makes this task extremely complicated, and exposure evaluation is then divided into two main scenarios, that of near-field and the far-field. Likewise, both near- and far-field situations can occur at indoor and outdoor scenarios, but SAR is evaluated in the near-field using complicated and unstable equipment at indoor facilities.

2.3

Dielectric Properties As described earlier, the permittivity of human tissues are responsible for both electromagnetic field distribution within the human body and heat conversion of that energy. Therefore, tissues permittivity measurement is a key issue for SAR estimation or prediction. In this section the most popular techniques for permittivity measurement are described, the current knowledge of dielectric properties is reviewed, and the role of these dielectric properties on SAR is also reviewed and discussed. 2.3.1

Measurement Techniques

Dielectric materials are widely used in many applications ranging from communication devices to military satellite services, and therefore, permittivity characterization is a very important task in many technological areas. Because of this, from early 1950s to present day measurement permittivity techniques have been continuously developed and improved [13]. There are many review contributions on complex permittivity measurement methods [14–19]. These methods can be very roughly classified as resonant or nonresonant methods depending on the used measurement cells. The impedance analyzer has been employed for tissue permittivity estimation [12] mainly for frequencies below 1 GHz. This technique is based on the use of a parallel plate and can be used up to 1.8 GHz [20]. The parallel plate method, also called the three terminal method in ASTM D150 [21], involves sandwiching a thin sheet of material or liquid between two electrodes to form a capacitor. The advantages of this method are high accuracy and easy sample preparation. However, the method cannot be used at higher frequencies due to edge fields escaping from the parallel plates. Transmission lines such as coaxial cables, microstrip lines, or waveguides have also been used for permittivity estimation with transmission-reflection techniques. Resonators based on those transmission lines have also been used mainly for estima-

30

Fundamentals of Electromagnetic Fields Interaction with Matter

tion of low-loss material properties. In this last case, resonance frequency and quality factors changes within the resonator are used for permittivity estimation. The dielectric properties of human tissues have called the attention of the scientific community for several reasons. First of all, conductivity is needed for SAR calculations and estimation as shown earlier. Second, permittivity maps for the human body allow for a proper modeling of interaction of EM waves and human tissues. For instance, at millimeter-wave frequencies, the absorption of electromagnetic radiation is mostly due to skin permittivity because of the small penetration depths at these frequencies [22], but at lower frequencies the different tissue layers may interact with each other to provide electric field resonances at certain tissue locations due to impedance mismatch, as shown in [23]. Therefore, a better human tissue permittivity characterization will lead to better SAR estimation and measurement when using phantoms for SAR compliance tests of communication devices. In the following paragraphs we describe and assess the most popular permittivity measurement techniques. Two kinds of measurement methods are reviewed in this section: nonresonant and resonant ones. In the first case, the propagation constant and impedance variations due to the material interaction with the transmission line can be related to the permittivity of the material. In the second one, the dielectric constant and loss factor are derived from changes in resonant frequencies and quality factors of resonant structures such as cavities or dielectric resonators [13]. Both resonant and nonresonant methods can be implemented in different technologies such as waveguides, coaxial, microstrip, or coplanar transmission lines. The election of the measurement cell or method depends on many factors such as availability, material dimensions and mechanization possibilities, accuracy specifications, bandwidth measurement needs, and so on. In the specific case of electromagnetic dosimetry, one has to decide whether to carry out measurements for in vivo tissues or in vitro ones, which also determines the most suitable permittivity measurement method. 2.3.1.1

Nonresonant Methods

Nonresonant methods employ transmission lines such as coaxial or rectangular waveguides as measurement cells which are in interaction with the material to be measured. Two types of approaches are mainly used in nonresonant methods: reflection measurements and transmission/reflection techniques. Reflection Methods

In this case, the material is placed at the end of the transmission line and reflections in the sample-air interface within the transmission line are used to derive its relative permittivity. Two kinds of reflections can again be generated at the end of the transmission lines: open-circuit and short-circuit ones. In open-circuit reflection methods the material is placed at the end of the transmission line and the end of the line is left in an open-circuit configuration. In contrast, in short-circuit reflection techniques the end of the line is short-circuited after the sample. Therefore, a practical implication derives from each approach: in short-circuit methods the sample must be placed within the transmission line, whereas in open-reflection methods the sample is outside the line.

2.3 Dielectric Properties

31

Coaxial Dielectric Probe

Figure 2.2 shows the scheme of the basic measurement configuration of an open-reflection method. In this case, a coaxial line is depicted and the sample is placed at the end of the coaxial open-circuit. As it can be observed, the outer conductor at the open end is usually fabricated into a flange to ensure a proper capacitance and repeatability of sample loading. This configuration is typically called coaxial dielectric probe [24, 25]. Usually coaxial lines are preferred for the implementation of the open-reflection method since they can cover broad frequency bands. In fact, most permittivity measurements for biological tissues are obtained by using the coaxial probe due to this characteristic and to the fact that the coaxial probe can be easily applied directly over the tissue. This method assumes that materials under test are nonmagnetic ones, which is the usual case for human tissues. There are several commercial packages (coaxial probe plus related software for both calibrating and measuring) such as the ones provided by [26] and [27] that automate complex permittivity and permeability measurements with transmission methods. As a disadvantage, low precision measurements are obtained with this method both for dielectric constant and low-loss factor values. In fact, coaxial probe should be used preferably for liquids and biological tissues under very restrictive geometrical and frequency conditions [27]. The analysis of open-ended coaxial probes is very extensive in the literature, although five typical approaches or models can be identified [28]: capacitive model [29], antenna model [30], virtual line model [31], rational function model [32], and full-wave approaches [33]. Due to its simplicity and the fact that the coaxial probe is very often used to measure biological tissues, the capacitance model is described here in detail. A good description of the rest of the approaches can be found in [13]. Capacitive Model of the Coaxial Probe

In this approach the open end of the coaxial line is modeled as two capacitances in parallel. The first capacitance (C( r)) is related to the dielectric properties of the sample, whereas the second one (Cf) is assumed to be independent of the dielectric sample. By changing the dielectric sample by those capacitances one can obtain the complex reflection coefficient at the entrance of the coaxial line as Γ=

( ) (C( ε ) + C )

1 − jωZ 0 C( ε r ) + C f 1 + jωZ 0

r

(2.38)

f

Coaxial flange Coaxial line Dielectric sample

Figure 2.2

Scheme for open-reflection measurement configuration.

32

Fundamentals of Electromagnetic Fields Interaction with Matter

where C( r) = rC0, C0 is the capacitance of the equivalent capacitor filled with air and Z0 is the characteristic impedance of the coaxial line connected to the open-ended probe. By measuring the reflection coefficient and using (2.38), one can derive the complex relative permittivity of the medium that is in contact with the open-end of the coaxial probe as expressed in (2.39). εr =

Cf 1− Γ − jωZ 0 C 0 (1 + Γ ) C 0

(2.39)

Since the two parameters of the model are unknown for a coaxial probe, both Cf and C0 must be obtained by calibrating the probe with a standard sample with known dielectric permittivity such as, for instance, deionized water [28]. Waveguide Measurements

Reflection methods can also be implemented with structures such as rectangular or cylindrical waveguides. The most common configuration consists of a rectangular waveguide short-circuited at its end. Figure 2.3 shows a rectangular waveguide containing a dielectric sample and a short-circuit at the end of the waveguide. In this case, the dielectric sample completely fills the waveguide cross-section. There are several possibilities and methods for sample size and location when using reflection methods in waveguides for measuring complex permittivity of materials. The simplest ones use a dielectric material which completely fills the waveguide cross-section such as the situation depicted in Figure 2.3 but other approaches are possible [34]. In the case of using waveguides as transmission line holders, one has to take into account that current measurement methods assume that only the fundamental mode propagates along the waveguide. For instance, this means for rectangular waveguides that the TE10 mode is the only one propagating in the waveguide [35]. This has practical consequences regarding frequencies where the method can be applied. In fact, permittivity measurements carried out in standard rectangular waveguides can only be applied from the cut-off frequency of TE10 mode to the cut-off frequency of the next mode, usually the TE20 mode. Therefore, if one has to cover a broad frequency range for the permittivity estimation and uses waveguide configurations, several waveguide cells would be necessary to cover this frequency range. On the other hand, commercial methods need the sample introduced in the waveguide to have very restrictive geometries and dimensions, which is not always easy to achieve. This means that the sample very often has to be mechanized to presShort circuit

Waveguide port

Dielectric sample

Figure 2.3 Scheme for a short-circuit reflection measurement configuration with a rectangular waveguide.

2.3 Dielectric Properties

33

ent a rectangular cross-section and consequently this measurement method is destructive. Therefore, the coaxial probe is preferred to waveguide configurations when trying to estimate permittivity on broad frequency ranges. Transmission/Reflection Methods

In transmission/reflection methods the sample is placed within the transmission line and the scattering parameters of the line are used for permittivity estimation. In this case two ports are used in the permittivity measurement and both reflections from the material interface and energy transmission through the material are used to deduce its electrical features. This method is preferred to characterize both low-loss and high-loss materials and has the advantage of providing both permittivity and permeability in just one measurement [36, 37]. Figure 2.4 shows the schematics for a transmission/reflection measurement in a rectangular waveguide. Again, commercial solutions are available for the measurement with this configuration such as the ones provided by [26] or [27]. Impedance Analysis

When using an impedance-measuring instrument to measure permittivity, the parallel plate method is usually employed. In this case, the material or liquid between two electrodes forms a capacitor whose capacitance varies as a function of the material relative dielectric constant [21]. The measured capacitance is then used to calculate permittivity. In an actual test setup, two electrodes are configured with a test fixture sandwiching dielectric material. The impedance-measuring instrument would measure vector components of capacitance (Cp) and dissipation and a software program would calculate permittivity and loss tangent from these data. Several configurations can be used for measuring the capacitance of the material. In fact, the material can be in contact with the material to be measured or not. The contacting electrode method implies that both electrodes touch the material surface as depicted in Figure 2.5. The guard electrode is needed since it absorbs the electric field at the edge of the guarded electrode and, in this way, the capacitance that is measured between the electrodes is only composed of the current that flows through the dielectric material. Therefore, accurate measurements are possible with this configuration. In this method the dielectric constant can be simply related to the capacitance measurement: εr =

t mC p

(2.40)

Aε 0

Waveguide port 2

Waveguide port 1

Figure 2.4

Dielectric sample

Configuration for transmission/reflection measurements in a rectangular waveguide.

34

Fundamentals of Electromagnetic Fields Interaction with Matter Guard electrodes

Guarded electrode Material under test

tm

Unguarded electrode

Figure 2.5

Contacting electrode method scheme.

where tm is the material thickness, Cp is the parallel plate capacitance, A is the electrode’s surface area, and 0 is the permittivity of free space. The loss tangent can be directly related to the energy dissipation suffered across the parallel plate. The contacting electrode method requires little material preparation and measuring operation is simple. Therefore, it is the most widely used method. However, a significant measurement error can occur if air gap and its effects are not considered when using this method. A more detailed description of this measurement technique and other more precise alternatives can be found at [20]. Inverse Techniques

Sometimes the dielectric samples cannot be mechanized into canonical shapes such as cylindrical or rectangular ones due to their hardness, fragility, and so on. On the other hand, multilayer dielectric materials cannot be handled by traditional methods and they provide an effective permittivity for the whole multilayer structure. In those cases, traditional methods cannot be applied and other measurement approaches must be considered. The improvement of numerical techniques and commercial software in the electromagnetic area during the last decade have allowed the growth of new measurement methods known as inverse techniques. In these inverse techniques the sample shape is just restricted to those shapes that can be handled by the electromagnetic code and consequently the measurement possibilities are expanded when compared to traditional methods. Inverse techniques are based on the comparison of two results: those provided by the measurement cell and those ones provided by the electromagnetic software that exactly reproduces this measurement cell. The error produced during the comparison of both results is used for convergence purposes until both the measured and simulated results show a high correlation. Therefore, inverse techniques are based on optimization processes where the error between the measurement and simulated results must be minimized. Many examples of inverse techniques can be found in the literature, such as the ones shown in [38–41]. In those works the measured and simulated scattering parameters are used for comparison purposes. A common disadvantage of the different inverse techniques is the high computing times required when threedimensional scenarios must be modeled since many optimization cycles are required in order to obtain an acceptable convergence between simulated and measured results.

2.3 Dielectric Properties

2.3.1.2

35

Resonant Methods

Resonant methods use resonant structures such as cavities or dielectric resonators in order to estimate the relative permittivity of materials. Usually they are more suitable for small and low-loss dielectric samples and offer higher accuracies and sensitivities than methods based on transmission lines [13]. Therefore, these techniques are not often used for measuring biological tissues since those materials show high dielectric losses. Nevertheless, they can be useful to characterize the dielectric properties of common objects present at SAR measurements or simulations such as clothes, contact lenses, and glasses, which may present low dielectric losses. The resonance of an electromagnetic structure occurs when both the electric and magnetic energy are equal at a given frequency. Two important parameters define the resonance properties: the resonant frequency and the quality factor. The first one is related to the geometry of the resonator and the dielectric constant of the sample. The second one is related to the losses of the resonant structure, which may be classified as dielectric or metallic losses. Resonant methods may be classified into two groups: resonator methods and resonant-perturbation methods. In the first case, the sample itself behaves as a resonator and, therefore, the resonant frequency and quality factor may be related to its dimensions, shape, permittivity, and permeability. The resonant-perturbation method, on the contrary, uses the dielectric sample to modify the resonant frequency and quality factor of a resonator, which usually is built as a metallic cavity [35]. Rectangular or cylindrical cavities may be used in this case. In this method, the perturbation approximation assumes that the introduction of the sample does not modify the electric or magnetic field distribution of the empty cavity. This obviously introduces a small error in the permittivity measurement. Due to this, dielectric samples are as small as possible when using this technique. The resonant-perturbation method uses the differences of the resonant frequency and the quality factor of both the empty and loaded cavity in order to derive the dielectric properties of the sample. Resonator Method

This method is also called the dielectric resonator method and as explained previously the dielectric sample under measurement serves itself as resonator and the permittivity can be determined from its resonant frequency and quality factor [42]. A possible measurement setup is to place a cylindrical dielectric sample between two circular conducting planes, whose electrical properties are assumed to be known. In this case we are using the so-called Courtney Method since Courtney was the first one to fully analyze and develop it in [43]. The excited mode is usually the TE011 since this mode does not show a transverse electric field between the sample and the conducting planes, which reduces the error in case that a small air gap is present between the sample and the conducting planes [44, 45]. In this method, the dielectric sample dimensions are limited by the frequency, dielectric properties of the sample, dimensions of the shorting plates, and the diameter of the coupling probes. Therefore, a usable range can be established for a particular dielectric resonator fixture [43].

36

Fundamentals of Electromagnetic Fields Interaction with Matter

Resonant-Perturbation Methods

Due to their high accuracy and sensitivity, these methods are widely used for low-loss and small-size samples, powders, and samples of irregular shapes. The most used resonators are hollow metallic cavities although dielectric resonators can also be used. Due to this, they are also called cavity-perturbation methods. There are several types of cavity perturbation: cavity-shape, wall-impedance, and material perturbations. For dielectric materials characterization the last one is more interesting since in this case the dielectric under test is introduced in the cavity, thus changing the resonance frequency and quality factor of the system. The complex permittivity can be determined by using the changes in both the resonance frequency and the quality factor due to the introduction of the sample. From Maxwell’s equations one can derive the changes in the complex angular resonant frequencies of the cavity before and after introducing a dielectric material [13]. Equation (2.41) shows the relationship between the different complex angular resonant frequencies and the electric and magnetic fields after and before inserting the sample in the cavity: r

∫ (ΔεE

Δω ω 2 − ω1 V = =− c ω ω1

2

r r ⋅ E1* + ΔμH 2 ⋅ H 1* dV

r r r ε1 E 2 ⋅ E1* + μH 2

∫(

Vc

) ⋅ H )dV * 1

(2.41)

where ω1 and ω2 are the complex angular resonant frequencies before and after the introduction of the simple, ε1 and ε2 are the complex permittivities of the original medium in the hollow cavity and the sample, μ1 and μ2 are the complex r permeabilities of the original medium in the hollow cavity and the sample, H 1 and r H 2 are the magnetic fields in the cavity before and after the introduction of the samr r ple, E1 and E 2 are the electric fields in the cavity before and after the introduction of the sample, Vc is the region enclosed by the cavity, and Vs is the sample volume. This equation can be simplified if a small object is considered and if it is assumed that the introduction of the sample does not significantly change and r ther electric r r magnetic field distribution within the cavity. In this case, by using E1 ≈ E 2 , H 1 ≈ H 2 , and

1

≈

2

one can obtain: ⎛

r

∫ ⎜⎝ Δε E

2

1

ω 2 − ω1 V ≈− s ω1 ⎛ r ∫V ⎜⎝ ε1 E1 c

2

r 2 + Δμ H1 ⎞⎟ dV ⎠ r 2⎞ + μ1 H1 ⎟ dV ⎠

(2.42)

Equation (2.42) indicates that an increase of both the permittivity and/or permeability inside the cavity will lead to a decrease of the resonant frequency. Additionally, if one assumes that the medium in the cavity is vacuum and that the material to be measured only shows a dielectric behavior, then (2.42) can be further simplified into

2.3 Dielectric Properties

37

r

∫E − 1⎞

1

r ⋅ E 2 dV

ω 2 − ω1 ⎛ε Vs ≈ −⎜ r ⎟ r 2 ⎝ 2 ⎠ ω1 ∫ E1 dV

(2.43)

Vc

where r is the relative complex permittivity of the sample. Since is a complex angular resonant frequency, it can be expressed with a real ( r) and imaginary part ( i) and related to the resonant frequency (f) and quality factor of the cavity (Q) as expressed in (2.44) through (2.46). ω = ω r + jω i

(2.44)

ω r = 2 πf

(2.45)

⎛ω ⎞ Q=⎜ r ⎟ ⎝ 2ω i ⎠

(2.46)

By assuming that 1 ≈ 2, that high quality factors are obtained within the cavity, and i > r, a relationship between the dielectric constant and the resonant frequency decrease can be obtained. Additionally, a relationship between the loss factor of the dielectric material and quality factor changes can also be derived: f1 − f 2 V = ( ε ′r − 1)A s f2 VC

(2.47)

V 1 1 − = Bε ′′r s Q 2 Q1 VC

(2.48)

where ε ′r and ε ′′r are the dielectric constant and the loss factor of the sample, respectively. A and B are constants related to the configuration and working mode of the cavity, sample shape, and location within the cavity. Since its determination is complicated from an analytical study, they are often obtained by calibrating the cavity with a dielectric sample of known characteristics. However, the sample size and shape used for calibration must be of similar values than those samples under test. 2.3.1.3

In Vivo or In Vitro Techniques

One can find in the literature two kinds of procedures to measure the permittivity of tissues. In vivo procedures have been applied to animals and consist of applying the measurement probe directly on the tissues of the living animal. Many times this requires surgery and/or sedation for animals, and that is the main reason why this procedure is not applied on humans [46]. Additionally, efforts have to be made to avoid contamination of the tissue with blood or other substances, and many times suction and dry cotton swabs and buds are used to eliminate excess fluid. In-vitro measurements differ from the previous procedure in the nature of the tissues. In this case the whole organ, or part of it, is excised, cleaned, and, after that, placed in a proper container before its dielectric properties can be measured. Basically, this

38

Fundamentals of Electromagnetic Fields Interaction with Matter

modifies temperature, moisture content, and, obviously, the working conditions of the living organ which may provide different results from in vivo measurements as described in [46]. 2.3.1.4

Permittivity of Usual Materials Worn by People

Several useful permittivity values for materials worn by people and which can be used in SAR simulations or measurements can be found at [9]. Table 2.1 shows some data for these materials. 2.3.2

Current Knowledge on Dielectric Properties

The electrical properties of materials involved in dosimetry evaluations have been reported in the literature, and the typically used values are those of Gabriel [12], who made her study after the contribution of Herman P. Schwan [47]. It has to be mentioned, however, that dielectric measuring techniques may not be very accurate, particularly below 1 kHz, with errors affecting the dielectric parameters by up to a factor of two [12]. A polar dielectric material under an electric field is electrically polarized at the molecular and atomic levels, and the total polarization reaches a steady state as a first-order process when a step field is applied. The total polarization magnitude, characterized by the time constant of the dipolar rotation τ which depends on the physical process, is

(

P = P∞ + (P0 − P∞ ) 1 − e −t

τ

)

(2.49)

where P∞ and P0 are the instantaneous and steady-state polarization, respectively. As we have seen before, in time-varying fields the relative permittivity is a complex function ε$ = ε ′ − jε ′′ = ε ′ − j

σ ωε 0

(2.50)

Table 2.1

Properties of Some Common Industrial Materials Worn by People

Material

Relative Complex Permittivity 7

9

9

10 Hz

10 Hz

3 10 Hz

3.78–j0.0001

3.78–j0.0002

3.78–j0.0002

1.2–j0.01

—

—

Cotton (210 kg/m ), 7% moisture content dry basis

1.5–j0.03

—

—

Natural rubber (25°C)

—

—

2.15–j0.0065

Nylon FM10001 (25°C)

3.24–j0.07

3.06–j0.043

3.02–j0.036

Glass 3

Wool (68 kg/m ), 20% moisture content dry basis 3

Extracted from [9] with permission from IET.

2.3 Dielectric Properties

39

where the real part ε ′ is the dielectric constant (i.e., a measure of the induced polarization per unit field), and the imaginary part ε ′′ is the out-of-phase loss factor associated with it. The frequency response of the first-order system is obtained from the Laplace transformation, which provides the relationship known as the Debye equation [48]. ε$ = ε ∞ +

εS − ε∞ = ε ′ − jε ′′ 1 + jωτ

(2.51)

where εS and ε∞ are known as static and infinite permittivity. This can be obtained easily from the Laplace transformation of (2.49), L[P] =

∫

∞

0

Pe − st dt =

∫

∞

0

(P

∞

(

+ (P0 − P∞ ) 1 − e −t

τ

))e

− st

dt = t =∞

P − P∞ − ( s + 1 τ )t ⎤ ⎡ P dt = ⎢− 0 e − st + 0 e ∫0 ⎥ s s+1τ ⎣ ⎦t =0 1 τ + − − P s P P s ) ( 0 ∞ ) P∞ s + P0 τ P P − P∞ 0( = 0 − 0 = = = s s+1τ s( s + 1 τ) s( s + 1 τ) =

= =

∞

(

P0 e − st − (P0 − P∞ )e

− ( s + 1 τ )t

P∞ ( s + 1 τ ) + P0 τ − P∞ τ s( s + 1 τ)

=

)

P∞ ( s + 1 τ) s( s + 1 τ )

+

(P0 − P∞ ) τ s( s + 1 τ)

(2.52)

=

P − P∞ P∞ + 0 s(1 + sτ ) s

taking into account that $ε = L[P ]/L[E ] and thus dividing (2.52) by the Laplace transformation of the step field applied L[E] = 1/s, the Debye equation is obtained after translating the instantaneous and steady-state polarization to the infinite and static permittivity, respectively. The current density J per unit of field E also follows a first-order law such that J E = σ$ = σ ∞ +

σS − σ∞ 1 + jωτ

(2.53)

where σ$ is the conductivity equivalent of the Debye equation, whereas σS and σ∞ are known as the static and infinite conductivity. Conduction currents can be arisen from, for example, a drift of free ions in static field, and its effect is not included in the Debye expression. It would become ε$ = ε ∞ +

εS − ε∞ σ + S 1 + jωτ jωε 0

(2.54)

This complex permittivity can be broken down in its real and imaginary parts: ε′ = ε∞ +

εS − ε∞

1 + ( ωτ )

2

(2.55)

40

Fundamentals of Electromagnetic Fields Interaction with Matter

( ε S − ε ∞ )ωτ σS + 2 ωε 0 1 + ( ωτ)

ε ′′ =

(2.56)

Likewise, the total conductivity σ is σ = ωε 0 ε ′′ = σ S +

(εS

− ε ∞ )ε 0 ω 2 τ

(

1 + ωτ 2

(2.57)

)

As we can see, the total conductivity σ is made of two terms, the residual static conductivity σS and polarization losses. Only the total conductivity of a material can be measured in practice. σS can be obtained from data analysis or by measurement at frequencies corresponding to ωτ << 1 where the dipolar contribution to the total conductivity can be neglected. Up to this point the dielectric response has been modeled as a first order process, but the presence of complex intermolecular interactions or multiple molecular conformational states may cause the polarization process kinetics of a substance not to be first order. This would cause its dielectric behavior to exhibit multiple relaxation time dispersions, bringing about the need of more complex models to analyze a dielectric response deviated from the Debye expression. The simplest one will consist of more than one Debye terms ε$ = ε ∞ +

Δ ε1 Δε 2 + +K 1 + jωτ1 1 + jωτ 2

(2.58)

where Δεn corresponds to the limits of the dispersion characterized by time constant τn. Another modified version of the Debye expression, known as the Cole-Cole model [49], was proposed in 1941 by Cole and Cole and is one of the most commonly used models, ε$ = ε ∞ +

εS − ε∞

1 + ( jωτ )

1−α

= ε ′ − jε ′′

(2.59)

where α is a distribution parameter in the range 0 ≤ α < 1. For α = 0, the model returns to the Debye equation. This complex permittivity can also be broken down in its real and imaginary parts: ε′ = ε∞ +

(εS

[

− ε ∞ ) 1 + ( ωτ )

1 + ( ωτ )

2 (1 − α )

1−α

+ 2( ωτ )

]

sin( α π 2 )

1−α

sin( α π 2 )

( ε S − ε ∞ )( ωτ) cos( α π 2 ) ε ′′ = 2 (1 − α ) 1−α 1 + ( ωτ ) + 2( ωτ ) sin( α π 2 )

(2.60)

1−α

(2.61)

Another variant of the Debye equation was proposed in 1951 by Davidson and Cole [50],

2.3 Dielectric Properties

41

ε$ = ε ∞ +

εS − ε∞

(1 + jωτ)

(2.62)

β

This differs from the previous one in that an exponent β is applied to the whole denominator, which entails the next expressions for its real and imaginary parts, ε ′ = ε ∞ + ( ε S − ε ∞ ) cos( βφ)( cos φ) ε ′′ = ( ε S − ε ∞ ) sin( βφ)( cos φ)

β

β

(2.63) (2.64)

where φ = arctan(ωτ). When β = 1, this variant returns to the Debye equation. Another expression which combines the variations introduced in both the Cole-Cole and the Cole-Davidson models was proposed by Havriliak and Negami in 1966 [51], ε$ = ε ∞ +

εS − ε∞

(1 + ( jωτ) ) 1−α

(2.65)

β

The Havriliak-Negami variant returns to the previous ones for the appropriate values of α and β. The Debye model and its many variations lend to simple curve-fitting procedures. In particular, the Cole-Cole model is the most used in the analysis of dielectric properties of biological materials, because both ε ′ and ε ′′ are proportional to (ωτ)1−α at the limit of high frequencies, simplifying the Cole-Cole function to a fractional power law. This is at the basis of the universal law of dielectric phenomena developed by Jonscher, Hill, and Dissado [52] for the analysis of the frequency dependence of dielectric data. Jonsher’s universal law can be summarized by the following dependencies for the normalized complex permittivity, for ω < ω p , ε ′′( ω) ≈ ω m and ε ′( ω) ≈ 1 − ε ′′( ω)

(2.66)

for ω > ω p , ε ′′( ω) ≈ ω n −1 and ε ′( ω) ≈ ε ′′( ω) ≈ ω n −1

(2.67)

where ωp is the loss peak radial frequency. The functional form for ε ′′(ω) is ε ′′( ω) =

A

(ω ω ) p

1−n

+ (ω p ω)

m

(2.68)

and its values can be determined numerically from the Kramer-Krönig relations. In 1999, Raicu found that neither approach was good enough over a wide frequency range and thus he proposed a model which combines features form Debye-type and universal dielectric response behavior [53],

42

Fundamentals of Electromagnetic Fields Interaction with Matter

ε$ = ε ∞ +

[

( jωτ)

Δ α

+ ( jωτ)

1−β

]

γ

(2.69)

where α, β, and γ are real constants in the range [0,1], τ is the characteristic relaxation time, and Δ is an adimensional constant, which becomes the dielectric increment (εS − ε∞) when α = 0. The Raicu expression reverts to the previous models for the appropriate values of α, β, and γ. For example, it reverts to Jonsher’s universal response model for γ = 1. Fixing α = 1 − β, in addition to γ = 1, the Raicu expression is β −1 Δ2 ⎛ ω⎞ $ , and becomes the constant phase angle model [54] ε$ = ε ∞ + ε ε = + j ⎜ ⎟ ∞ ⎝ S⎠ ( jωτ)1 − β when a scaling factor S = (Δ/2)1/(1−β)τ−1 is taken. Dissado’s model was successfully used to model the dielectric spectrum of a biological material over five decades from 103 to 108 Hz. More information about the models used to estimate the frequency response of the dielectric properties of matter, as the Debye equation and its variants, treated along this section, can be found in [55]. The objective of the previous models is to allocate dielectric properties to the various tissues of a man or animal model, at all the frequencies to which it can be exposed. These man and animal models have been produced by means of developments in the field of electromagnetic dosimetry. The level of details is such that over 40 tissue types can be identified, so these models have high resolution and are anatomically correct. The application of such models required a consensus on the dielectric data, which came with Gabriel’s project [12], geared towards this objective, in which three experimental techniques were used to measure the dielectric properties of tissue in the frequency range 10 Hz to 20 GHz. The dielectric measurements were performed using automatic swept frequency network and impedance analyzers. For the frequency range 10 Hz to 10 MHz, an HP4192A impedance analyzer was used. An HP8753C covered the frequency range 300 kHz to 3 GHz, and an HP8720 measured from 130 MHz to 20 GHz. Open ended coaxial probes were used to interface the measuring equipment with the samples in all cases. The technique used with the HP8700 series network analyzers has been reported in [56]. The agreement between measurements was particularly good when they were made on the same sample throughout. Over 20 tissue types were measured over the full frequency range and over 10 others measured down to 1 MHz only. Also, internal consistency between the three sets of data was demonstrated in the overlapping frequency regions. When measurements were made on the same sample throughout, the agreement between data sets was particularly good. Moreover, a comprehensive survey of dielectric data published over more than 45 years was carried out in [12] and presented for comparison purposes. The data obtained in the course of Gabriel’s study fell well within the vast body of literature data where available and bridges the gaps within it. Additionally, to facilitate the incorporation of the dielectric data in numerical solutions, their frequency dependence was modeled to a spectrum characterized by four dispersion regions. This model was successfully applied to the experimental data. Finally, the conductivity of tissues below 100 Hz was estimated from the measurements in [12], modified by data from the literature and used to estimate the conductivity of the whole body and of various body parts.

2.3 Dielectric Properties

43

The measurement techniques and associated instrumentation used in [12] gave random reproducibility of about 1% across the frequency range. This statement was based on multiple measurements carried out on standard samples of uniform composition. Biological tissues are inhomogeneous and show considerable variability in structure or composition and hence in dielectric properties. Such variations are natural and may be due to physiological processes or other functional requirements. The spread of values ranged from about ±5% above 100 MHz to ±15% at the lower end of the frequency scale. Care was taken to eliminate all known sources of systematic errors, however, in view of the assumptions made in correcting for electrode polarization it is possible that the dielectric parameters below 1 kHz may be undercorrected. This source of errors may affect the dielectric parameters by up to a factor of two. Three sources of materials were used: excised animal tissue, mostly ovine, from freshly killed sheep; human autopsy tissues; human skin and tongue in vivo. All animal tissues were used as fresh as possible, mostly within 2 hours after death; human material was obtained 24 to 48 hours after death. The conical probe used in conjunction with the impedance analyzer required relatively large samples, at least a cube of 5 cm linear dimension. In view of this requirement not all samples could be measured at low frequencies. As we have just seen, Gabriel extracted the dielectric properties of tissues from the literature of the last half of the past century, particularly from the work of H. P. Schwan and his collaborators [47], and from [32, 57–61] and compared it to the corresponding data from her own measurements. The purpose was to provide an objective basis for the evaluation of the experimental data and to reach a broad-based consensus on the subject. Moreover, data corresponding more closely to living human tissues were selected in preference to any other. Consequently, human tissue and in vivo measurements were selected in preference to animal tissue and in vitro measurements. For in vitro measurements, data obtained at temperatures closest to that of the body and nearest to the time after death were used when available. One of the aims in [12] was to derive models for the frequency dependence of the dielectric properties of the tissues investigated. The basis of the analysis is well-known dispersion mechanisms in the dielectric spectrum of biological materials and their expression as a summation of terms corresponding to the main polarization mechanisms, which have been described before. The spectrum extends from hertz to gigahertz and shows four dispersion regions. The complexity of the structure and composition of biological material are such that each dispersion region is broadened by multiple contributions to it and could be described by a Cole-Cole expression. The model corresponding to the whole spectrum is ε( ω) = ε ∞ +

4

Δε m

m =1

( jωτ m )

∑ 1+

1−α m

+ σi

( jωε 0 )

(2.70)

in which ε∞ is the permittivity in the terahertz frequency range and σi is the ionic conductivity; and for each dispersion region, τm is the relaxation time and Δεm is the drop in permittivity in the frequency range from ωτ << 1 to ωτ >> 1. With a choice of parameters appropriate to each tissue, (2.70) could be used to predict its dielectric behavior over the desired frequency range. The parameters of the model were

44

Fundamentals of Electromagnetic Fields Interaction with Matter

adjusted to correspond to a close fit between the model and the most comprehensive data set available for the particular tissue. This 4-Cole-Cole model can be used with confidence for frequencies above 1 MHz. At lower frequencies, where the literature values are scarce and have larger than average uncertainties, the model should be used with caution in the knowledge that it provides a “best estimate” based on present knowledge. It is important to stress the limitations of the model particularly where there is no data at all to support its predictions. The 4-Cole-Cole analysis was carried out on 44 tissue types and its results are presented in a self-explanatory manner in Table 2.2. Some examples of fitted dielectric properties, using the summation of 4-Cole-Cole expressions as reported in (2.70), are given in Figures 2.6 to 2.8. Dielectric properties of human tissues have also been measured by other authors. For example, human brain tissue was measured at frequencies from 800 to 2,450 MHz in [62]. This work presents results for the dielectric properties of human gray matter tissue based on a sample of 20 brains less than 10 hours postmortem.

Table 2.2 Modeling the Frequency Dependence of the Dielectric Properties to a Four-Dispersion Spectrum: Summary Table of Fitting Parameters

Extracted from [12].

2.3 Dielectric Properties

Figure 2.6

Dielectric properties of skin (dry), muscle, and bone (cortical) tissues.

Figure 2.7 tissues.

Dielectric properties of brain (white matter), brain (gray matter), and cerebellum

45

Compared to data from the literature [12], its results indicated a slightly higher conductivity of human gray matter at body temperature in the frequency range from 800 to 2,450 MHz, even though a closer look at the comparable data from the literature dealing with the dielectric properties of gray matter in the same frequency range shows the general trend that in vivo measurements in animals led to higher values of dielectric properties compared to measurements on excised tissue samples. This is in agreement with studies reporting a postmortem decrease of the dielectric properties of gray matter [63]. Regarding permittivity, it is interesting to note that no significant differences between [62] and published data could be observed; fur-

46

Fundamentals of Electromagnetic Fields Interaction with Matter

Figure 2.8

Dielectric properties of blood, thyroid, and testis tissues.

thermore, conductivity was much more affected by postmortem changes than permittivity. It is important to emphasize that measurement values of dielectric properties are significantly dependent on the origin, handling, and temperature of the tissue and the time when the measurements took place with respect to the time of death. In order to provide reliable dielectric data, which are essential for accurate RF dosimetry, it is therefore most desirable to take into account all the above-mentioned facts. Obtaining data based on human tissue measured as soon as possible after death in combination with corresponding in vivo investigations in large mammals seems to be the best approach for estimating dielectric data of living human body tissue. Application of such a procedure is of course advisable not only for brain tissue, but also for all other types of tissue such as human skull, which was investigated only very rarely in the past and which might play an important role regarding RF power absorption in the human head. Likewise, standard methods for measurement of SAR in order to evaluate the radio frequency safety of mobile phones, including recipes for tissue-equivalent dielectric liquids, have been recently the subject of discussion among international standards organizations. Standards currently recommend glycol-type liquids as tissue-equivalent liquids for frequencies above 1 GHz. Although the ingredients are specified in the recipes provided, some fundamental information, such as the stability of dielectric properties, remains unclear. 2.3.3 The Role of Tissue Dielectric Properties and Geometry on Electromagnetic Dosimetry

The change of dielectric properties with time and with temperature of tissue-equivalent liquids recommended in the standard documents and their effects on SAR has

2.3 Dielectric Properties

47

been measured and evaluated in [64]. The conductivity decreased with increasing temperature in all glycol-type specimens at a rate about 2% per degree. The permittivity, on the other hand, was almost constant. With the evaporation of water, the conductivity and the permittivity decrease, since the material reduces its dipolar nature, as Figure 2.9 shows for two different types of leather [65]. In this figure, the dielectric properties are represented versus the moisture content (dry basis) of the hides for 2.5 GHz. Experimental results in [64] proved that dielectric properties are affected by environmental conditions, and that it is inevitably necessary to adjust the dielectric properties regularly, through the addition of ingredients, in order to follow the standards. The SAR values, however, were not affected significantly by the change in dielectric properties [64]; thus, a larger tolerance of the dielectric properties may be acceptable in practical SAR measurements. Another important effect is the age-dependence of biological tissues, which is not normally considered and also applies to the tissue simulating liquids in measurements, although the latest degrade rather more rapidly that the ageing effects. Some information on age-dependence or simply the variability of dielectric properties is yet becoming available and has already proven to be an important factor for SAR assessment. For example, for small objects compared to the electromagnetic fields wavelength (i.e., wavelength inside material is greater than ten times the dimensions of the object) and for the special condition where permittivity values are proportional (i.e., ε ′ ≈ ε ′′), the whole-object averaged SAR is inversely proportional to the object permittivity [66, 67]. Even though variability in permittivity values do not substantially influence whole-body SAR values, localized SAR values for individual tissues are substantially affected by these changes [68]. Other authors found local differences in the internal field distribution and SAR value, comparing head models including or not an inner auditory system model, as depicted in Figures 2.10 and 2.11. This confirms that only through a tissue-specific and/or organ dosimetry, a better insight of the interactions between external electromagnetic fields and biolog-

Figure 2.9 Variation of dielectric properties with moisture content in leather. (Reproduced from [65] with permission from Elsevier.)

48

Fundamentals of Electromagnetic Fields Interaction with Matter

Semicircular canals

Cochlea Base 12 mm

Utricle 13 mm

Saccule

Apex 14 mm

Figure 2.10 IEEE.)

Modeling of a membranous labyrinth. (Reproduced from [69] with permission from

Near Vestibulus

Far Vestibulus

Figure 2.11 Head model including inner auditory systems. (Reproduced from [69] with permission from IEEE.)

ical structure can be achieved [69]. Likewise, an experimental investigation of the effects of ear shape and head size on SAR, using a cubical head model with various ear shapes [70], shows that the SAR distribution depends on the ear shape. Mochizuki et al. also concluded that there is a large difference (1.5 dB) between the maxima local SAR measured with the various ear models and a cellular-phone model, even though there is no significant difference between the values measured with a dipole antenna [71]. In [72], the different dielectric properties of 10 rat tissues at six different ages from 130 MHz to 10 GHz were measured. The results show that a general decrease in the permittivity and conductivity was found with age, with this trend accentuated in the brain, skull, and skin tissues, and less noticeable for abdominal tissues. The conductivity and permittivity values for a 10-day rat, compared to a 70-day rat, range from 20% to 100% higher.

2.3 Dielectric Properties

49

Moreover, the effect of the higher permittivity and conductivity values was a lower whole-body SAR, except for a region between 110 and 180 MHz. This inverse relationship between permittivity and SAR was also confirmed in [73], but only for whole-body normalized SAR, and when the tissue was muscle-like and around 2 GHz. Likewise, the dielectric properties of whole-brain, skin, and skull were determined experimentally in the frequency range 300 KHz to 300 MHz in [74]. Tissue samples were excised from 10-, 30-, and 70-day-old Wistar strain rats. The data were presented in graphical format and compared to previously published data in the frequency range 100 MHz to 20 GHz [72]. Good agreement was observed between the two data sets, since at frequencies in excess of about 100 MHz the permittivity and conductivity decrease monotonically with increasing age. It is noteworthy that at these frequencies, the γ dispersion is dominant, being that this region is dominated by the dielectric response of the aqueous component. Nevertheless, the opposite effect was observed at 500 MHz in [73]. When all permittivity values were multiplied by 0.5, a decrease on whole-body normalized SAR values was observed. Furthermore, when the multiplication was by a factor of 2.0 the whole-body SAR values increased. It is worth noting that this frequency was near the resonance frequency of the rat model, and also near the frequency range 300 KHz to 300 MHz, the site of the β dispersion, where a change in the frequency dependence of the dielectric parameters was observed in [74], which was most evident in the spectra for brain and skin. This was attributed to changes in the tissue structure. Results in [74], at frequencies from 27 to 2,000 MHz, reveal that the variation in the dielectric properties affect the whole body SAR by less than 5% with the most conservative value (i.e., the highest SAR), which was obtained when properties of the 70-day-old rat tissues were used. Also in [74], the dielectric properties of skin were affirmed to be an important determinant in the coupling efficiency and hence in the intensity of the exposure. This study stated that skin is an animal-specific organ, and thus researchers must exercise caution when using animal skin dielectric data in human exposure studies. Consequently, elaboration of the question of the exposure of children versus adults must await more appropriate dielectric data and also MRI-based numerical models of children. The scientific community is aware of this need, and it will be probably addressed in the near future. Regarding the exposure of children versus adults, it is worth mentioning that there is a controversy on the dosimetry in children’s heads for mobile telephones. Gandhi, et al. [75] reported a considerable increase of the spatial peak SAR in children’s heads, while Kuster, et al. [76] claimed that there was not a significant difference in the SAR between children and adults. In [77], the local peak SAR under the same conditions as those previously employed by Gandhi’s and Kuster’s groups is calculated. Compared to the local peak SAR in the adult head model, a considerable increase in the children’s heads was found when the output power of the monopole-type antenna was fixed, but no significant differences when the effective current of the dipole-type antenna was fixed. This finding suggests that the contradictory conclusions drawn by the above two groups may be due to the different conditions in their numerical peak SAR calculations. In addition, an approximation of the aging effect on dielectric tissue properties for SAR assessment of mobile telephones can be found in [78]. This study stated

50

Fundamentals of Electromagnetic Fields Interaction with Matter

that the dielectric properties for the child head models do not affect significantly the 1- or 10-g averaged spatial peak SAR, being the increased 1- or 10-g averaged spatial peak SAR within 10% even in an extreme case. This could be explained by the cancellation of the increased conductivity and decreased electric field penetrating into tissue. This occurred because of the same degree of increase between the conductivity and permittivity in children compared to adults, as reported in [78] (and since E ∝ 1/ε ′ [66]). Furthermore, the calculation of the penetration depth in child head models exhibits an almost same value as or somewhat smaller value than that in the adult model [78]. More controversy appears when, in [79], some comments are mentioned about different percentage deviations when changing the dielectric permittivity or the tissue conductivity. This study has some interesting conclusions, such as SAR changes are imperceptible for small dielectric constant changes. This is exactly the contrary of what was concluded in [67], wherein local SAR is found to vary greatly with permittivity values, even when whole-body average SAR values are not sensitive. An explanation of these differences could be the different operation frequencies used in each study. A lot of studies can be found in the literature about dependences of SAR on several factors as the dielectric properties themselves (i.e., dielectric constant and conductivity), aging, geometry, and so on. For example, in [80], 100 rats were exposed during a period of 2 years to a brain-averaged SAR of 2 W/kg for a so-called high-dose group, and 0.67 W/kg for a so-called low-dose group. The whole-body averaged SAR was less than 0.4 W/kg. An interesting conclusion is reached in this study, since a relatively large variation of the SAR could be found in the male high-dose group. This finding could be explained by the fact that the whole-body and brain-average SAR can be largely affected by the size or weight of the rats.

2.4

Heat Generation Once the electric field goes straight through the body tissues, the electromagnetic energy turns into heat due to dielectric losses as explained earlier. This means that, as long as the electric field travels across the human body, it decreases its energy and the surrounding tissues increase their temperature. If this energy interchange was isolated from other effects, there would be a direct relationship between electric field distribution within the human body and temperature increments. However, the temperature increase within the human body when electromagnetic energy is present is influenced by other phenomena such as thermal migration, blood perfusion, and convection. In this section we review the main models for estimating the temperature increase within the human body when it is irradiated with high frequency electromagnetic fields. 2.4.1

Bioheat Equation

The bioheat equation was first suggested by Pennes in order to determine steady-state tissue temperature-depth distributions [81]. Basing his analysis on the general differential equation of heat conduction,

2.4 Heat Generation

51

Cρ

∂T = K ⋅ ∇ 2 T + hm + hb ∂t

(2.71)

3

where C [J/(kg·K)] is the specific heat, ρ [kg/m ] is the tissue density, T [K] is the tissue temperature, K [J/(s·m·K)] is the thermal conductivity, hm [J/(s·m3)] is the rate of tissue heat production, and hb [J/(s·m3)] is the rate of heat transfer from blood to tissue. This equation simply equals the temperature increase per unit time multiplied by the thermal capacitance of 1 m3 of tissue, given by the product between the specific heat and the tissue density, to the heat accumulated per unit time and per unit volume in the body. Several papers deal with heat transfer in living tissue on the basis of the so-called bioheat transfer equation. In [82] a fundamental error in this equation is pointed out, arising from the incorrect formulation of the thermal transport by blood, demonstrating the futility of applying the equation, both by physical argument and a numerical example. The equation in question constitutes the local energy balance for a solid at rest. It includes a distributed volumetric source of metabolic heat generation, and a second distributed source accounting for the effect of blood perfusion. This second source term is the term of interest here and is allegedly based on Fick’s principle [83]. The equation is, at first pC

∂T = ∇ ⋅ ( K∇T ) + w b C b Tb , in − Tb , out + q m ∂t

(

)

(2.72)

and simplified, on the assumptions of Tb,in = Ta, Tb,out = T and constant thermal conductivity of the tissue, to yield the so-called bioheat transfer equation: ρC

∂T = K∇ 2 T + w b C b (Ta − T ) + q m ∂t

(2.73)

3

where wb [kg/(m ·s)] is taken to be the volumetric blood perfusion rate in mass of blood per unit volume of tissue per unit time, Cb [J/(kg·K)] is the specific heat of blood, Tb [K] is the temperature of blood, Ta [K] is the temperature of arterial blood, and qm [J/(s·m3)] is the volumetric metabolic heat generation rate. Wulff stated that the correct form of the bioheat transfer equation is ρC

r ∂T = K∇ 2 T − ρ b C bU h ⋅ ∇T + q m ∂t

(2.74)

r where U h is the local mean apparent blood velocity associated with enthalpy flux. r For the blood flowing in the averaged direction of the vector U h , the enthalpy flux enhances or opposes the conductive heat flux −K T, where ρ b hbU h =

1 ( ρ b hb u ) d ω 4π ∫Ω

(2.75)

ρb is the blood density, hb is the specific enthalpy of blood, and u is the actual blood velocity in capillary. In his opinion, the estimate of the local blood mass flux ρbUh

52

Fundamentals of Electromagnetic Fields Interaction with Matter

requires additional considerations, somewhat more complex than the oversimplified assumption of a volumetric blood perfusion rate wb. However, this bioheat equation evolved to a modified version [84], K∇ 2 T + A 0 + Q v − B(T − Tb ) = Cρ

∂T ∂t

(2.76)

In particular, the four terms in the first member of (2.76) represent different ways through which heat is accumulated inside the tissue, specifically: 1. 2. 3. 4.

Heat transfer through internal conduction (K[J/(s·m·K)]); Metabolic heat production (A0[J/(s·m3)]); Heat deposition due to the absorbed microwave power (Qv[J/(s·m3)]); Heat exchange mechanism due to blood perfusion, proportional to the heat-sink strength from tissue volume by blood perfusion (B[J/(s·m3·K)]) and the difference between blood and tissue temperature (Tb − T) [K].

To solve (2.76), a convective boundary condition is applied at the external surface of the body [81, 84, 85]. This condition is obtained imposing the continuity of the heat flow perpendicular to the surface of the body (heat reaching this surface from the interior of the body through conduction must equal the heat exchanged through convection with the surrounding medium or fluid),

[ ( s ⋅ m )]

⎛∂ T⎞ − K ⎜ ⎟ = H(Ts − Te ) J ⎝ ∂t ⎠ S

2

(2.77)

2

where H [J/(s·m ·K)] is the convection coefficient, Ts [K] is the surface temperature, and Te [K] is the fluid temperature. Starting from a SAR distribution, the corresponding induced heating profile could be evaluated by solving the bioheat equation, taking Qv = ρSAR [86]: K∇ 2 T − ρρ b C b m b T + ρSAR = Cρ 3

∂T ∂t

(2.78)

where mb [m /(kg·s)] is taken to be the volumetric perfusion rate of blood in volume of blood per unit mass of tissue per unit time, taking “normal” blood perfusion 3 −6 3 value equal to 40 cm /(100g·min) in his study, that is, 6.66 × 10 m /(kg·s) in the international system of units (IS). In the 26 years following its publication (1949-1974), Pennes’ paper [81] was cited an average of 1.7 times per year. Since 1990 (through 1996), the paper has averaged 25 citations annually [87]. Thus, the bioheat equation has been appearing in numerous publications, but with no significant changes until Bernardi [88], following [81], included a term for the respiratory heat losses in the lungs (RL [J/(s·m3)]) in the bioheat equation and a term to represent heat losses due to sweating in the boundary condition. A clear account of the bioheat equation used in this work can be found in [88].

2.4 Heat Generation

53

Likewise, Yang added a term to the bioheat equation [89] to account for the power density used for tissue internal water evaporation, QE [J/(s·m3)], yielding a modified bioheat equation, ρC

∂T = ∇ ⋅ ( K∇T ) + Q + Q B − Q E ∂t

(2.79)

where Q [J/(s·m )] is the microwave power density and QB = ρBCBωB(TB − T) [J/(s·m3)] is a term which accounts for the effects of perfusion, where ωB [1/s] is the blood perfusion rate and TB [K] is the ambient blood temperature before entering the ablation region. In his study, the metabolic heat generation term A [J/(s·m3)] was considered insignificant with respect to the rest of the heating terms and, therefore, ignored. Moreover, Yang related the power density used for evaporation to the change in water content of tissue as a function of time 3

Q E = −α

dW dt

(2.80)

where α is the water latent heat constant, which is 2,260 [kJ/kg], and W is the tissue water density [kg/m3], which is assumed to be only a function of temperature. From the chain rule, the derivative of W with respect to time is dW ∂W ∂ T = dt ∂T ∂t

(2.81)

Substituting this into (2.80), yields Q E = −α

∂W ∂ T ∂T ∂t

(2.82)

The modified bioheat equation then becomes ρC

∂T ∂W ∂ T = ∇ ⋅ ( K∇T ) + Q + Q B + α ∂t ∂T ∂t

(2.83)

Pulling the last term in the above equation to the left-hand side ∂W ⎞ ∂ T ⎛ = ∇ ⋅ ( K∇T ) + Q + Q B ⎜ ρC − α ⎟ ⎝ ∂T ⎠ ∂t

(2.84)

Examining the above equation, Yang defined an effective specific heat C′ = C −

α ∂W ρ ∂T

which yielded a new modified Pennes bioheat equation:

(2.85)

54

Fundamentals of Electromagnetic Fields Interaction with Matter

ρC ′

∂T = ∇ ⋅ ( K∇T ) + Q + Q B ∂t

(2.86)

Equation (2.86) is in the same format as the original bioheat equation, with an ∂W effective specific heat used instead of the normal specific heat. Since is 0 when ∂T evaporation does not occur and is negative when evaporation occurs, effective specific heat C ′ is never less than normal specific heat value C, which is consistent with it requiring more energy to raise the temperature during a phase change. Tissue effective specific heat [J/(kg·K)] is the only new term in (2.86). It is similar to the normal specific heat as it is defined as the amount of energy required to increase the temperature of a unit mass of tissue by 1K, and includes the water latent heat energy required if tissue water evaporation occurs. For this formulation Yang assumed that the change in tissue water content and tissue effective specific heat were only dependent on tissue temperature. In actuality it is more complex than this. However, Yang implemented a model which, while still not complete, was more accurate than the previous thermal model. Regarding the validation of the Pennes’ bioheat equation, Wissler’s calculations [90], when compared with Pennes’ measurements [81], demonstrate good agreement. This validation of the Pennes’ model is confirmed by other studies. The model has shown consistency with observations when applied to perfused phantoms [91] and to simulating temperature fields in the human brain [92]. Thus, consistency between predictions of the Pennes’ bioheat equation and measurements is truly remarkable when viewed in the context of the gross simplifications inherent to the model. For many practical applications, the simplicity of the Pennes model is appropriate to the required accuracy and the level of detailed anatomic knowledge available [93]. As mentioned above, a lot of papers use the bioheat equation to deal with heat transfer in living tissue. For example, in [94], a modified version of the Pennes bioheat equation is solved in order to evaluate temperature increase for all tissues in a human head model: ρ⋅cp

∂T = ∇ ⋅ ( kT ∇T ) + ρSAR + A0 + B(Tb − T ) ∂t

(2.87)

The in-house thermal model developed in [94] included heat diffusion and convection, metabolic heat production, and heat-sink from tissue volume by blood perfusion. Thermoregulatory control can be achieved in the model in real time, which can keep a constant temperature under no RF exposure but being slightly altered by the heat loss in the body surface due to intimate contact to air, as shown in Figure 2.12. Likewise, temperature results are shown for a hypothetical peak SAR equal to 2 W/kg for the entire head model, for several exposure times, in Figures 2.13 and 2.14. Furthermore, with this SAR, thermoregulatory control can be achieved in the model; that is, the time to rise to 90% of the steady state temperature under an exposure resulting in a hypothetical peak SAR of 2 W/kg is a bit longer than three-quarters of an hour. Both temperatures are shown in Figures 2.15 and 2.16.

2.4 Heat Generation

Figure 2.12

55

Temperature under no RF exposure.

(a)

(b)

Figure 2.13 Temperature after 6 minutes of exposure resulting in a hypothetical peak SAR of 2 W/kg (a) and the equivalent temperature increment over the steady-state temperature under no RF exposure (b).

As we can see, even with basal metabolism and blood flow, thermoregulatory control is achieved for a SAR under the basic restrictions, and steady state is reached. However, this should be different for a harsh exposure, with SAR greater than the maximum specified by the international safety standards, even if the thermoregulatory system is modeled with a variable metabolism and blood flow.

56

Fundamentals of Electromagnetic Fields Interaction with Matter

(a)

(b)

Figure 2.14 Temperature after 30 minutes of exposure resulting in a hypothetical peak SAR of 2 W/kg (a) and the equivalent temperature increment over the steady-state temperature under no RF exposure (b).

(a)

(b)

Figure 2.15 Steady state temperature under an exposure resulting in a hypothetical peak SAR of 2 W/kg (a) and the equivalent temperature increment over the steady-state temperature under no RF exposure (b).

2.4.2

Thermal Properties of Human Tissues

The bioheat equation shows that once the electromagnetic energy has been converted into heat due to dielectric losses this heat travels across the human tissues from hot spots to cold tissues [95]. This thermal migration is particularly important in hyperthermia tests and bioexperiments where high electromagnetic power levels and long exposition times are used [96]. In fact, Moros and Pickard [97] have shown that the thermometrically estimated SAR in tests is influenced by thermal conduc-

2.5 Conclusions

57

(a)

(b)

Figure 2.16 Temperature after the so-called time to rise (a) and the equivalent temperature increment over the steady-state temperature under no RF exposure (b).

tion to a large extent, and in this sense point SAR measurements performed with traditional thermometry methods are subject to significant errors due thermal diffusion [97]. Therefore thermal characteristics are of the utmost importance when trying to compute or infer SAR from temperature simulations or measurements. There are several sources where one can find thermal properties and perfusion properties for human or animal tissues, such as [88, 95, 98–109]. Table 2.3 shows the thermal data for human tissues and organs included in [88]. One can deduce from results that very different thermal properties are found for different tissues or organs due to their different composition, tissue disposition, and water content. Thermal properties of human tissues vary both with water content and tissue temperature. An example of this variation can be found in [109]. In that work, Valvano et al. presented an experimental method to measure the thermal conductivity and thermal diffusivity of biomaterials such as kidney, spleen, liver, brain, heart, lung, pancreas, colon cancer, and breast cancer at different temperatures. Self-heated thermistor probes, inserted into the tissue of interest, were used to deliver heat as well as to monitor the rate of heat removal. Thermal properties were measured for 65 separate tissue samples at different temperature ranging from 3°C to 45°C. The results showed that the temperature coefficient of biomaterials approximated that of water.

2.5

Conclusions Electromagnetic dosimetry establishes the relationship between an electromagnetic field distribution in free space and the induced fields inside biological tissues. Maxwell equations, which govern all electromagnetic phenomena, are the mathematical tools for a rigorous and accurate study of this interaction between electromagnetic waves and the human body. The final goal of dosimetric studies is to

58

Fundamentals of Electromagnetic Fields Interaction with Matter Table 2.3

Thermal Properties of Most Common Human Tissues Under Basal Conditions 3

3

K[J/(s·m K] A0 [J/(s·m ]

B0[J/(s·m · K]

3900

0.55

0

0

330

0.43

1600

9000

3900

0.0

0

0

Tissue/Organ

C[J/(kg K]

Bile Bladder Blood Bone marrow

2700

0.22

5700

32000

Cancellous bone

1300

0.40

590

3300

Cartilage

3500

0.47

1600

9000

Cerbellum

3700

0.57

7100

40000

Cerebro-spinal fluid

4200

0.62

0

0

Colon

3700

0.56

9500

53000

Cornea

4200

0.58

0

0

Cortical bone

1300

0.40

610

3400

Eye humor

4000

0.60

0

0

Eye lens

3000

0.40

0

0

Eye tissue

4200

0.58

0

0

Fat

2500

0.25

300

1700

Gall bladder

3500

0.47

1600

9000

Glands

3600

0.53

64000

360000

Grey matter

3700

0.57

7100

40000

Heart

3700

0.54

9600

54000

Internal air

1000

0.03

0

0

Kidney

3900

0.54

48000

270000

Liver

3600

0.51

12000

68000

Lung

3600

0.14

1700

9500

Mucous membrane

3300

0.43

1600

9000

Muscle

3600

0.50

480

2700

Nerve–spinal cord

3500

0.46

7100

40000

Pancreas

3500

0.54

7300

41000

Skin

3500

0.42

1620

9100

Small intestine

3700

0.56

13000

71000

Spleen

3700

0.54

15000

82000

Stomach

3600

0.53

5200

29000

Tendon

3300

0.41

1600

9000

Testis

3800

0.53

64000

360000

White matter

3600

0.50

7100

40000

Reproduced from [88] with permission from IEEE.

quantify the electromagnetic absorption of a given organ or the whole human body. This quantity is the specific absorption rate (SAR), defined as the time rate at which energy is deposited in any kind of material per unit of mass. Biological tissues and other materials that usually surround the human body do not have magnetic properties and, therefore, the interaction with electromagnetic fields depends mainly on the electric permittivity. This parameter is a complex number, with a real part (the dielectric constant) that models the capacity of the material to store electric energy,

2.5 Conclusions

59

and an imaginary part (the loss factor) that models the energy dissipation. This dissipation results in a heat generation in the tissue that can be explained by the friction of molecular and atomic dipoles when these dipoles try to follow the variations of the electric field. Therefore, the behavior of the different materials involved in the problem can be completely described by their respective electric permittivities. Alternative parameters like the electric conductivity or the loss tangent are used in the determination of the SAR, but they are strongly related to the electric permittivity. Therefore, it is necessary to estimate the electric permittivity of the different materials involved in the interaction by means of proper measurement techniques. The impedance analyzer and coaxial probe techniques are widely used in the tissue permittivity characterization. The impedance analyzer can be used at low frequencies while coaxial probes allow broader bandwidth measurements. Additionally, the coaxial probe can be used both for in vivo or in vitro measurements while the impedance analyzer is more suitable for in vitro characterization. Cavity resonant techniques can only obtain permittivity values at discrete frequencies and are better for estimation in low-loss materials such as fabrics, plastics, or glass. Inverse techniques for permittivity estimation are based on the comparison of simulating and measuring results. They need optimization algorithms in order to reduce the error between simulations and measurements until good correlations are obtained. However, these techniques should be used only when canonical shapes for the tissue under measurement cannot be obtained or when the tissue is a multilayer dielectric, since they need high computing times depending on the measuring scenario and the chosen optimization strategies. The application of high-resolution, anatomically correct man and animal models from medical imaging data requires the knowledge of the dielectric properties of the different tissues at all the frequencies to which the model is exposed. There was no consensus on these dielectric data until their frequency dependence was modeled by a spectrum characterized by 4 dispersion regions [12]. The main purpose of this model was to compile a database of dielectric properties of tissues for the use of the scientific community in solving electromagnetic interaction problems. This was achieved through measurement in the frequency range 10 Hz to 20 GHz and modeling the frequency dependence of the dielectric properties of over 30 body tissues to parametric expressions for inclusion in numerical solutions. Obtaining the electric field distribution and the resulting energy dissipation is only the first step in the dosimetric analysis, since other phenomena, such as heat conduction or blood thermoregulation must be evaluated. The bioheat equation, first suggested in 1948, takes into account these phenomena and has been evolving into modified versions. These improvements consist of the inclusion of terms to account for the sweating, heat losses in lungs, variable metabolism or blood flow, or even these last two triggered by temperature thresholds in the hypothalamus region.

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2.5 Conclusions

63

[59] Stuchly, S.S., Sibbald, C.L., and Anderson, J.M., “A new admittance model for open-ended waveguides,” IEEE Transactions on Microwave Theory and Techniques, Vol. 42, No. 2, pp. 192–198, 1994. [60] Foster, K.R., and Schwan, H.P., “Dielectric properties of tissues and biological materials: A critical review,” Critical Reviews in Biomedical Engineering, Vol. 17, No. 1, pp. 25–104, 1989. [61] Duck, F.A., Physical Properties of Tissue: A Comprehensive Reference Book, San Diego, CA: Academic Press, 1990. [62] Schmid, G., Neubauer, G. and Mazal, P.R., “Dielectric properties of human brain tissue measured less than 10h postmortem at frequencies from 800 to 2450 MHz,” Bioelectromagnetics, Vol. 24, pp. 423–430, 2003. [63] Burdette, E.C., et al., “In situ permittivity of canine brain: Regional variations and postmortem changes,” IEEE Transactions on Microwave Theory and Techniques, Vol. 34, No. 1, pp. 38–49, 1986. [64] Fukunaga, K., Watanabe, S. and Yamanaka, Y., “Dielectric Properties of Tissue-Equivalent Liquids and Their Effects on Specific Absorption Rate,” IEEE Transactions on Electromagnetic Compatibility, Vol. 46, No. 1, pp. 126–129, 2004. [65] Monzó-Cabrera, J., Díaz-Morcillo, A., Catalá-Civera, J.M., and de los Reyes, E., “Heat and Mass Transfer Characterisation of Microwave Drying of Leather,” Proceedings of the 12th International Drying Symposium, Noordwijk, Holland, 2000. [66] Jackson, J.D., Classical Electrodynamic, Second Edition, New York: Wiley, 1975. [67] Hurt, W.D., Ziriax, J.M., and Mason, P.A., “Variability in EMF Permittivity Values: Implications for SAR Calculations,” IEEE Transactions on Biomedical Engineering, Vol. 47, No. 3, pp. 396–401, 2000. [68] Gajšek, P., et al., “Parametric Dependence of SAR on Permittivity Values in a Man Model,” IEEE Transactions on Biomedical Engineering, Vol. 48, No. 10, pp. 1169–1177, 2001. [69] Parazzini, M., et al., “Modeling of the Internal Fields Distribution in Human Inner Hearing System Exposed to 900 and 1800 MHz,” IEEE Transactions on Biomedical Engineering, Vol. 54, No. 1, pp. 39–47, 2007. [70] Mochizuki, S., et al., “Effects of Ear Shape and Head Size on Simulated Head Exposure to a Cellular Phone,” IEEE Transactions on Electromagnetic Compatibility, Vol. 49, No. 3, pp. 512–518, 2007. [71] Kanda, M., et al., “Effects of ear-connection modeling on the electromagnetic-energy absorption in a human-head phantom exposed to a dipole antenna field at 835 MHz,” IEEE Transactions on Electromagnetic Compatibility, Vol. 44, No. 1, pp. 4–10, 2002. [72] Peyman, A., Rezazade, A.A., and Gabriel, C., “Changes in the dielectric properties of rat tissue as a function of age at microwave frequencies,” Physics in Medicine and Biology, Vol. 46, pp. 1617–1629, 2001. [73] Mason, P.A., et al., “Effects of Frequency, Permittivity, and Voxel Size on Predicted Specific Absorption Rate Values in Biological Tissue During Electromagnetic-Field Exposure,” IEEE Transactions on Microwave Theory and Techniques, Vol. 48, No. 11, pp. 2050–2057, 2000. [74] Gabriel, C., “Dielectric Properties of Biological Tissue: Variation with Age,” Bioelectromagnetics, Vol. 26, No. S7, pp. S12–S18, 2005. [75] Gandhi, O.P., Lazzi, G., and Furse, C.M., “Electromagnetic absorption in the human head and neck for mobile telephones at 835 MHz and 1900 MHz,” IEEE Transactions on Microwave Theory and Techniques, Vol. 44, No. 10, pp. 1884–1897, 1996. [76] Schoenborn, F., Burkhardt, M. and Kuster, N., “Differences in energy absorption between heads of adults and children in the near field of sources,” Health Physics, Vol. 74, No. 2, pp. 160–168, 1998. [77] Wang, J., and Fujiwara, O., “Comparison and Evaluation of Electromagnetic Absorption Characteristics in Realistic Human Head Models of Adult and Children for 900-MHz

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[78]

[79]

[80]

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[84] [85]

[86]

[87] [88]

[89]

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[95]

Mobile Telephones,” IEEE Transactions on Microwave Theory and Techniques, Vol. 51, No. 3, pp. 996–971, 2003. Wang, J., Fujiwara, O. and Watanabe, S., “Approximation of Aging Effect on Dielectric Tissue Properties for SAR Assessment of Mobile Telephones,” IEEE Transactions on Electromagnetic Compatibility, Vol. 48, No. 2, pp. 408–413, 2006. Monebhurrun, V., et al., “A Numerical Approach for the Determination of the Tissue Equivalent Liquid Used During SAR Assessments,” IEEE Transactions on Magnetics, Vol. 38, No. 2, pp. 745–748, 2002. Wake, K., et al., “An Exposure System for Long-Term and Large-Scale Animal Bioassay of 1.5-GHz Digital Cellular Phones,” IEEE Transactions on Microwave Theory and Techniques, Vol. 55, No. 2, pp. 242–250, 2007. Pennes, H. H., “Analysis of tissue and arterial blood temperature in the resting human forearm,” Journal of Applied Physiology, Vol. 1, No. 2, pp. 93–122, 1948. Wulff, W., “The Energy Conservation Equation for Living Tissue,” IEEE Transactions on Biomedical Engineering, Vol. 21, No. 6, pp. 494–495, 1974. Shepherd, A.P., Steinke, J.M., and McMahan, C.A., “Effect of oximetry error on the diagnostic value of the Qp/Qs ratio,” International Journal of Cardiology, Vol. 61, pp. 247–259, 1997. Bardati, F., Gerosa, G., and Lampariello, P., “Temperature distribution in simulated living tissues irradiated electromagnetically,” Alta Frequenza, Vol. 49, No. 2, pp. 61–67, 1980. Bernardi, P., et al., “SAR Distribution and Temperature Increase in an Anatomical Model of the Human Eye Exposed to the Field Radiated by the User Antenna in a Wireless LAN,” IEEE Transactions on Microwave Theory and Techniques, Vol. 46, No. 12, pp. 2074–2082, 1998. Riu, P.J., and Foster, K.R., “Heating of Tissue by Near-Field Exposure to a Dipole: A Model Analysis,” IEEE Transactions on Biomedical Engineering, Vol. 46, No. 8, pp. 911–917, 1999. Institute for Scientific Information, Inc., Science Citation Index 1956–1996, Philadelphia, PA: Institute for Scientific Information, Inc., 1997. Bernardi, P., Cavagnaro, M., Pisa, S., and Piuzzi, E., “Specific Absorption Rate and Temperature Elevation in a Subject Exposed in the Far-Field of Radio-Frequency Sources Operating in the 10–900-MHz Range,” IEEE Transactions on Biomedical Engineering, Vol. 50, No. 3, pp. 295–304, 2003. Yang, D., et al., “Expanding the Bioheat Equation to Include Tissue Internal Water Evaporation During Heating,” IEEE Transactions on Biomedical Engineering, Vol. 54, No. 8, pp. 1382–1388, 2007. Wissler, E.H., “Pennes’ 1948 paper revisited,” Journal of Applied Physiology, Vol. 85, pp. 36–42, 1998. Baish, J.W., Ayyaswamy, P.S., and Foster K.R., “Perfused phantom models of microwave irradiated tissue,” Journal of Biomechanical Engineering, Vol. 108, pp. 239–245, 1986. Stone, J.G., et al., “Direct intraoperative measurement of human brain temperature,” Neurosurgery, Vol. 41, pp. 20–24, 1997. Nelson, D.A., “Invited Editorial on ‘Pennes’ 1948 paper revisited,” Journal of Applied Physiology, Vol. 85, pp. 2–3, 1998. García-Fernández, M.A., and Sánchez-Hernández, D., “The merging of EM equations and thermal diffusion and convection and its consequences on current knowledge for human protection regarding exposure to EM fields,” Proceedings of the HES-07: International Symposium on Heating by Electromagnetic Sources Induction, Dielectric, Conduction & EMP, Padua, Italy, June 20–22, 2007, pp. 211–218. Samaras, T., Regli, P., and Kuster, N., “Electromagnetic and heat transfer computations for non-ionizing radiation dosimetry,” Phys. Med. Biol., Vol. 45, pp. 2233–2246, 2000.

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[96] Sullivan, D.M., “Three-dimensional computer simulation in deep regional hyperthermia using the FDTD method,” IEEE Transactions on Microwave Theory and Technology, Vol. 38, pp. 204–211, 1990. [97] Pickard, W.F., Straube, W.L., Moros, E.G. and Fan, X., “Simplified model and measurement of specific absorption rate distribution in a culture flask within a transverse electromagnetic mode exposure system,” Bioelectromagnetics, Vol. 20, pp. 183–193, 1999. [98] Grayson, J., “Internal calorimetry in the determination of thermal conductivity and blood flow,” Journal of Physiology, Vol. 118, pp. 54–72, 1952. [99] Chato, J.C., “A method for the measurement of the thermal properties of biological materials,” Thermal Problems in Biotechnology, J.C. Chato, (Ed.), ASME symposium series, American Society of Mechanical Engineers, New York, 1968. [100] Cooper, T.E., and Trezek, G.J., “Correlation of thermal properties of some human tissue with water content,” Aerospace Medicine, Vol. 42, pp. 24–27, 1971. [101] Balasubramaniam, T.A., and Bowman, H.F., “Thermal conductivity and thermal diffusivity of biomaterials: A simultaneous measurement technique,” J. Biomech. Engr., Vol. 99, pp. 148–154, 1977. [102] Drane, C.R., “The thermal conductivity of the skin of crocodilians,” Comp. Biochemical Physiology, Vol. 68A, pp. 107–110, 1981. [103] Dumas, A., and Barozzi, G.S., “Laminar heat transfer to blood flowing in a circular duct,” Int. Journal of Heat and Mass Transfer, Vol. 27, pp. 391–398, 1984. [104] Holmes, K.R., Ryan, W., and Chen, M.M., “Thermal conductivity and H2O content in rabbit kidney cortex and medulla,” J. Therm. Biol., Vol. 8, pp. 311–313, 1983. [105] Kvadsheim, P.H., Folkow, L.P., and Blix, A.S., “A new device for measurement of the thermal conductivity of fur and blubber,” Journal of Thermal Biology, Vol. 19, pp. 431–435, 1994. [106] Kvadsheim, P.H., Folkow, L.P., and Blix, A.S., “Thermal conductivity of Minke whale blubber,” Journal of Thermal Biology, Vol. 21, pp. 123–128, 1996. [107] McIntosh, R.L., Anderson, V., and McKenzie, R.J., “A Numerical Evaluation of SAR Distribution and Temperature Changes Around a Metallic Plate in the Head of a RF Exposed Worker,” Bioelectromagnetics, Vol. 26, pp. 377–388, 2005. [108] Valvano, J.W., Allen J.T., and Bowman, H.F., “The simultaneous measurement of thermal conductivity, thermal diffusivity, and perfusion in small volumes of tissue,” ASME 81-WA/HT-21, 1981. [109] Valvano, J.W., Cochran, J.R., and Diller, K.R., “Thermal conductivity and diffusivity of biomaterials measured with self-heated thermistors,” Int. Journal of Thermophysiology, Vol. 6, pp. 301–311, 1985.

CHAPTER 3

Far-Field Numerical Electromagnetic Dosimetry Antonio M. Martínez-González

3.1

Introduction Legislation regarding limitations of exposure of the general public to electromagnetic fields has been approved in most Western countries within the last 10 years [1–29]. Strong research efforts ever since have concentrated on determining accurate near- and far-field exposure assessment through simulation or measurement procedures for either the verification of compliance of wireless transmitting facilities or mobile handsets to these limitations or simply to find out accurate field values for exposure evaluation and/or planning parameters. The importance of an adequate exposure assessment and its standardization is without doubt considering that people can be exposed to the field radiated by transmitting stations for a long time or by wireless handsets. Yet, the exposure levels on urban streets from transmitting stations are generally much lower than those due to mobile handset antennas. In fact, exposure from base stations (BS) is rather different to that of mobile handset antennas. Several studies have found that specific absorption rate (SAR) values are found to be maximum at and around the human ear for mobile handsets [30–36], with reported temperature increases of the ear lobe between 1.0° and 2.4°C after a 20-minute talking phase depending on location and phone type (other phases were stand-by, ringing, and switching off). This heating was attributed not only to SAR, but also to heating from the electronic part of the device, with an important reduction in ventilation due to the presence of the device near the face. Temperature increases were located within the first 5 to 7 minutes, and then gradually decreased. For the case of wireless transmitting facilities, however, there are other regions in the human body like the neck, chest, ankles, knees, trunk, or the back wherein the highest SAR values have been experimentally observed [37–41], mainly due to direct exposure or reflections from the rear building walls. In fact, the highest whole-body SAR when the man model is exposed to a vertically polarized plane wave occurs at around 70 MHz, while in the frequency range from 200 to 600 MHz energy absorption is prominent in the regions surroundings the ankles, knees, and neck [41, 42]. Increasing the frequency augmented the amount of energy depos-

67

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ited on the skin, while the energy absorption within the brain is maximal between 600 to 800 MHz. The International Commission for Non-Ionizing Radiation Protection (ICNIRP) and other institutions have published guidelines to specify a number of basic restrictions on the amount of electromagnetic energy which can be absorbed by the human body without ill effects [43–48]. Basic restrictions on electromagnetic field exposure are also provided for both the general public and workers exposed in the workplace in terms of SAR values. Taking measurements of basic restriction values on volunteers is not always possible due to the ethical concerns regarding the implantation of deep body temperature probes and the scarcity of volunteers, and experiments on animals are a poor approximation to the “real” human scenario. In view of these difficulties, standardization bodies provide reference levels expressed in terms of electromagnetic field strengths, which are evaluated in the absence of a person. Specified reference levels are developed in a conservative way, in that they have been derived using worst case conditions of electrical coupling, so that by ensuring that the reference levels are not surpassed, providing that there is no focalized exposure, the basic restrictions are not surpassed either, or at least to the knowledge available at the time, as we will see throughout this section. These reference levels, however, are derived from plane-wave incidence exposure, which is limited to far-field situations, and some new discoveries to this effect will be highlighted in this chapter. In an urban scenario, with its rather complex environment, surrounding scattering objects, and multiple reflections and diffractions, the coupling mechanism for deferring reference levels may not occur even at far-field distances. Nevertheless, due to the narrow radiation pattern of most sectored base stations, evaluating compliance to safety limits is usually accomplished by evaluating field levels and comparing these to reference levels in the standards. Hence, the use of reference levels as magnitudes for compliance assessment of transmitting wireless facilities has to consider the fact that exposure does not have to be very localized within the human being subjected to the exposure. This happens at very close distances to the radioelectric sources, where a direct evaluation of basic restrictions is more appropriate. That is, when dealing with health issues in the near-field between 100 kHz and 10 GHz, and in order to prevent whole-body heat stress and excessive localized heating of tissues, it is usual to provide basic restrictions on SAR, described in Section 3.2. For the mobile handset scenario, the exposure region is typically the reactive near-field, and thus either simulations or measurements of SAR are required for evaluating electromagnetic field exposure and compliance to standard safety limits. This evaluation can be extended to the intimate proximity of base station antennas for diverse systems (GSM, UMTS, WLAN, etc.) or wireless devices, as we will also illustrate further on. For the handset scenario, dependence with distance from the source, orientation of the handset, frequency, technology, shape, size, and heterogeneity of the human model are critical parameters when energy absorption inside human tissue is going to be computed [30, 32, 34, 49]. Despite the vast number of publications on the issue, electromagnetic dosimetry is still the subject of many research efforts due to the large number of variables involved in the process and the tremendously wide range of realistic scenarios for handset use in mobile communications or for the wide diversity of base station antennas. In this chapter we will illustrate important issues for simulated far-field

3.2 Electromagnetic Exposure Evaluation and Compliance Testing

69

exposure assessment and compliance testing procedures generally due to transmitting facilities, including some critical parameters such as frequency, phantom and source modeling or numerical artifacts such as averaging and meshing. Some of the most recent developments will be outlined, specific procedures described, engineering rigorous technical recommendations provided, sources of inaccuracies identified, and recommendations for further review highlighted.

3.2

Electromagnetic Exposure Evaluation and Compliance Testing The prediction of exposure to electromagnetic fields emitted by wireless transmitting facilities is very similar to more conventional coverage prediction since both are intended to determine field intensities at a given point or area. The difference arrives when analyzing the intended assessment to be carried out since coverage refers to the offering of a wireless facility with an assigned quality over a given area, which is only investigated by determining whether the predicted field intensity is greater than a given minimum threshold related to the sensitivity of the mobile terminal [50]. Exposure evaluation, on the other hand, is related to the exposition of the human body to the incident electromagnetic field at each time by evaluating unperturbed electric and magnetic field strengths in the near-field and power density in the far-field. Since electromagnetic safety guidelines usually take into account the alternating nature of the fields and are based upon thermal effects, exposure is normally evaluated by averaging instantaneous incident field values in both time and space in the absence of a person. When these values are compared to existing averaged safety limits in order to determine whether the legal requirements to comply with these limits are satisfied, compliance testing procedures are performed. This means that if the purpose of the evaluation is to determine compliance testing, some approximations to either the prediction formulas or the measurements leading to overestimated values are acceptable [51]. Yet, should these approximations be considered, when compliance testing is not achieved, it does not necessarily means that safety limits are surpassed, and more accurate predictions or measurements are required. Simulation tools have a series of advantages over measurements for evaluating electromagnetic dosimetry, with the special ability to study specific individual effects of certain parameters by keeping others constant. Other advantages are an almost free set-up of the computational model for placement of gadgets and objects under study [52] and avoiding the ageing effect of tissue simulating liquids while the simulations run in the background. Early studies use simple uniform plane wave exposure scenarios and free-space formulas [53, 54], also known as spherical-wave models. Yet, simple free-space simulation engines are generally considered to underestimate real far-field values, and the influence of surrounding buildings cannot be neglected [50]. Moreover, although the use of far-field formulas (spherical-wave) for dosimetric analyses can be employed for distances from the source greater than 2D2/λ [55, 56], they also overestimate near-field values for GSM900 systems while underestimating far-field values, and can only be used for compliance testing [57, 58]. For GSM1800 systems, some authors claim that far-field formulas used for near-field distances also slightly overestimate real near-field values [50–57], while some other authors show that there is an underestimation for the

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far-field-based obtained radiated power using EIRP/4πr at distances within the 2 near-field range, but that measured values of an isotropic probe ( E / η) would accurate represent near-field values obtained using the Poynting vector [59]. Yet, both the cylindrical-wave (which will be described later) and spherical-wave models are included in the European basic standard [60, 61] and in other standards. This is so despite recent studies differentiating their ranges of applicability and limiting accuracy [57, 62]. Comparison between FDTD-cylindrical power density predictor for a 6 × 2 array panel at both 900/1800 MHz is shown in Figures 3.1 and 3.2. Therefore, several techniques have been reported to calculate the electromagnetic fields in the vicinity of wireless transmitting facilities and devices, including the method of moments (MoM) [58], finite-difference time-domain (FDTD) [40, 59, 63], finite integration technique (FIT) [64], generalized multipole technique (GMT) [65, 66], and finite element (FE) methods [58]. While FDTD is preferred for small electromagnetic dosimetry problems (i.e., near-field scenarios) [31, 34, 49, 67–69], 100

S (W/m2)

FDTD Far field approach Cylindrical approach

10

D 2/4λ

1

0.6D 2/λ

4

2

6 R (meters)

D 2/λ

8

10

Figure 3.1 Power density versus distance for a 6 × 2 array panel at 900 MHz. Comparison between results from FDTD, far-field, and cylindrical methods. Radiated power 100W. (Reprinted from [55] with permission from John Wiley and Sons.)

FDTD Far field approach Cylindrical approach

S (W/m2)

100

10

0.6D 2/λ

D 2/4λ

2

D 2/λ

4

6

8

10

R (meters)

Figure 3.2 Power density versus distance for a 6 × 2 array panel at 1,800 MHz. Comparison between results from FDTD, far-field, and cylindrical methods. Radiated power 100W. (Reprinted from [55] with permission from John Wiley and Sons.)

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its highly demanding computational requirements make it less efficient for large problems [70, 71], particularly when highly heterogeneous models like the human body are included in the computational domain together with the source. Even today, simulations for whole-body models may take up to days, and a common characteristic to all full-wave methods for exposure assessment is the large inherent computational cost and the need to accurately describe and model the array antenna geometry. Thus, full-wave methods are not usually employed for routine evaluation of compliance or for exposure assessment, and some approximations are usually employed to ease calculation.

3.3

Human Body and Source Modeling 3.3.1

Human Body Model

Measurement of SAR and other internal quantities that may give rise to biological effects which are inherently difficult to measure directly and studies to investigate compliance with the exposure restrictions are carried out using physical or numerical models referred to as phantoms [72, 73]. The physical and electrical characteristics of experimental phantoms are manufactured to represent as closely as possible the response of a person to an incident electromagnetic field. First, heterogeneous models of humans for measuring far-field exposure assessment were developed in the 1980s [53, 74, 75] after some measuring methods like the implantable probe technique [76–78] and the thermographic technique [79–81]. One of these first heterogenous models is depicted in Figure 3.3. The development of whole-body models was undertaken since large discrepancies were found between SAR calculated using separate blocks of the human body and measured values with whole-body phantoms [82, 83]. In these first tests the heterogeneous models provided higher SAR values than previous homogenous models. Later, it was proven that SAR values for whole-body models strongly depend on the parameters of the employed tissues and, more important, on the source and its effect on electromagnetic coupling. In some cases homogeneous models provided higher SAR values than heterogeneous models for the same exposure [40]. Moreover, these first tests already showed that the discrepancies for local SAR values were found to be large between heterogeneous and homogeneous models, which included the location of the maxima. A good example of this effect was the study about the fat-layer thickness of a full-scale human body model [84]. In [84] it was shown that in fact fat layers absorbed more power compared to other tissue types despite their lower conductivity due to its presence in a closer position to that of the exciting source (i.e., closer to the human body skin). When taking into account the human body model, lower peak SAR and peak SAR averaged values were obtained. The human body was therefore acting like an electromagnetic absorbent. By now we know that two effects were mixed up in the first studies (and still are in some) regarding the homogeneous and heterogeneous models. In [85] and [86] it was made clear that, despite the above-mentioned importance of source matching, the homogenous models tend to overestimate SAR values with respect to heterogeneous models only if appropriate muscle-like tissues are employed and only when just the head is modeled. Heterogeneous and, more specifically, anatomical models,

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Figure 3.3 An external view of the heterogeneous model of man. (Reprinted from [53] with permission from IEEE.)

on the other hand, provide higher SAR values than homogeneous ones (as high as double that in [86]) when the whole body is evaluated. Two other clarifying papers regarding matching fat-related effects have recently been published [86, 87]. In [86], it was anticipated that the fat at the body trunk was acting as a matching layer between free space and the other body tissues so as to allow increased energy transmission to those tissues and consequent Joule heating in those tissues. The overall matching effect has finally been discovered in [87] by analyzing 2D cuts of different regions in an anatomical body model (illustrated in Figure 3.4 and derived from the visual human project), particularly in the trunk and limbs regions, and their exposure to the near-field of dipole antennas. Through a tissue sequence study it was found that some tissue sequences lead to standing-wave effects and that the layered tissue could provide some impedance matching effects, which in turn allows a signif→

H

→

E

Skin

SAT

Muscle

→

k

Figure 3.4

Layered planar tissue model. (From: [87].)

Bone

Lung

3.3 Human Body and Source Modeling

73

icant amount of electromagnetic power to enter the tissue, or a constructive interference giving rise to a significant SAR increase in the skin layer. Depending upon the tissue structure and penetration depth, the standing-wave effect can also occur within the body, and this effect could not be compensated by a tissue simulating liquid. In [73], this effect was compensated with a tissue simulating 2/3-muscle, but only compared to a four-tissue head model. Electromagnetic matching was better achieved for a 2/3-muscle tissue homogeneous head phantom, and that translated into different input impedances for the source and higher power absorbed in the tissue than in any other situation for either 1.5- or 5-mm cell size. In fact, the 2/3-muscle situation was better matched for a 5-mm cell size (providing more absorbed power) than any other tissue even at 1.5-mm cell size due to a better representation of the source and a better matching to the heterogeneous model. In [87], the increase was more pronounced for plane-wave incidence at antenna distances at which far-field-like exposure can be assumed. In fact, the overestimation by homogeneous models in the head was confirmed for close distances, and the absorption in the layered model increases with the antenna distance, with a maximum of 200% to 250%, depending upon the frequency employed, which in fact is threatening the validity of tissue simulating liquids defined by current standards for compliance testing when far-fieldlike exposure conditions are evaluated. The increase of the SAR ratio begins at approximately λ/8, and the maximum is reached at a distance between the antenna and the body of approximately λ/3 for all frequencies. In other words, the body-antenna interaction is one single complicated problem, and each specific layered body (including the homogeneous) is a different electromagnetic problem, so that when the impedance of the antenna in the problem converged that of the free-space value, which strongly depend upon source modeling, body structure and body distance, the problem is matched at both ends and the energy coupling is maximum. Since power density decays strongly with distance, the largest SAR values are observed at the closest distance when the source impedance loaded with the body converges to its free space value. This may seem simple, but it was not published until 2006. In Figure 3.5, this effect is shown for 236 MHz, showing that maximum SAR is not yet achieved for an antenna distance of 300 mm (λ/3 ≈ 424 cm); the effect is maximum at around 50 mm at 2,450 MHz in Figure 3.6 (λ/3 ≈ 41 cm). In Figures 3.5 and 3.6, only 10-, 50-, 100-, 200-, and 300-mm distances were evaluated. The matching effect was also envisaged but it was not the object of the study in [88], wherein it was highlighted that the anatomical details of tissue layers located close to the body’s surface can have a significant influence on the whole-body SAR. The matching effect was also observed when measuring exposure values with probes in [89], wherein the relative deviation of measured probe impedance with respect to that of the free-space situation at the operating frequency was found to be larger when the separation between the measurement probe and the transmitting panel antenna was smaller. The variations were also much larger when both the length of the measurement probe and the transmitting antenna were larger than 0.45λ. By 2000, however, 6-mm whole-body models developed from partial head and neck models originally created in 1996 [30] were employed for testing the response

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Far-Field Numerical Electromagnetic Dosimetry 150

real homogeneous imag. homogeneous real layered imag. layered

Impedance in ohms

100

50

0

–50 0

50

150 200 100 Antenna distance in mm

250

300

Figure 3.5 Feedpoint impedance of the λ/2-dipole antenna at 236 MHz as a function of the distance. (Reproduced from [87] with permission from IEEE.)

150

real homogeneous imag. homogeneous real layered imag. layered

Impedance in ohms

100

50

0

–50

0

50

100

150

200

250

300

Antenna distance in mm

Figure 3.6 Feedpoint impedance of the λ/2-dipole antenna at 2,450 MHz as a function of the distance. (Reproduced from [87] with permission from IEEE.)

to a 835-MHz (typical of GSM) exposure [35]. Due to the required computational costs, original 2 × 2 × 3-mm resolutions were coarsen to get a 6 × 6 × 6-mm model, and the incident electromagnetic field was calculated based upon the assumption

3.3 Human Body and Source Modeling

75

that the mere presence of the body and its distance to the source did not significantly alter the radiation characteristic of the source in order to ease computational convergence. Other studies at the time used a 5-mm cell size human body model [90]. At that time, however, data from the Visible Human Project (VHP) [91, 92] (sponsored by National Institute of Health) and the Yale Human Project (YHP) (depicted in Figure 3.7 [93], and in which partial-body parts were incorporated from the VHP (legs and arms)), were available, both providing male and female 1-mm resolution (in x and y axes only for Yale, with 3.6-mm in the vertical direction) data extracted from the segmentation of the transmission computerized (CT) X-ray thermographs, ultrasounds, or magnetic resonance imaging (MRI) slices of human bodies. Some sort of classifying algorithm is used to differentiate between tissues and their properties of interest and under certain conditions allow for these properties to vary with the orientation of the tissue, wavelength, temperature, or other parameters. The VHP model consists of approximately 400 million voxels of 1 mm3 with 44 different tissue types. 3 More recently, finer resolutions of 3 × 3 × 3 mm [41] and 1.974 × 1.974 × 3 3 mm [94] of the VHP have been conducted, as well as new dielectric 2-mm anatomical models (DAM) with 7,880,380 voxels, wherein permittivity and conductivity vary with continuity even within the same tissue, thus reflecting the intrinsic realistic spatial dispersion of such parameters [95], which leads to higher SAR values than those obtained for VHP human body models [96]. In this last study it was also made clear that, on top of antenna and human body modeling, the distance between the whole-body model and the antenna has to be carefully evaluated, taking into account the specific shape and posture of the body model under consideration. Despite all efforts to numerically evaluate exposure due to transmitting facilities, high resolution (<1 mm) models are essential to resolve functional subregions of the brain, and experimental methods are required to verify the simulations and to iden-

Figure 3.7 IEEE.)

Three views of the Yale body model. (Reproduced from [93] with permission from

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Far-Field Numerical Electromagnetic Dosimetry

tify the possible shortcomings of the numerical model [97]. Some of the described models are depicted in Figure 3.8. A standardized human model for far-field evaluation is yet to be agreed upon. Considerable more attention has been paid to the development of human models for near-field evaluation of exposure, as will be described in Chapter 4. 3.3.2

Source Modeling

Simulating the coupling mechanism between an electromagnetic wave and a complete human body model for making a safety assessment has only been made possible recently by characterizing the source simultaneously and because of the current computing capacity of modern workstations. Likewise, the wide variety of possible sources makes the standard near-half-wavelength dipole array ideal as a generic source to calculate the power deposition in the human body and to allow for intercomparable studies. Should commercial antenna data be available, however, that would represent much better the electromagnetic field distribution incident on the human body model for that specific model, and thus several analyses have been performed employing arrays of conventional dipoles, cross-dipoles, and microstrip patches [85, 86]. Some close-form approximations have also been derived for specific sources. Circular loop wires were employed to investigate the power absorbed by a human body in the frequency range from 50 to 400 MHz [98], and were found to provide maximum SAR when the loop was x-oriented (human body vertical was z-oriented). A synthetic model and gain-based model were derived for vertical linear arrays using the principle that the field in the whole antenna can be well approximated by the superposition of the fields of subantennas constituting the antenna [99, 100]. In fact, when the source is assumed to be a uniform array, the fact that far-field exposure cannot easily be assumed when measuring or simulating in the vicinity of a base station is alleviated by the more accurate computation of power density on the surface of an imaginary cylinder that extends from the bottom of the lowest element to the top of the highest element [63]. The cylinder has a radius equal to the distance from the antenna at which estimates of power density are desired. The power density near such an antenna, but at distances at least above λ/2, decays with the inverse of the distance from the antenna and can be estimated with a cylindrical model which can be expressed by the relationship, S=

Prad 2 hπ R

(3.1)

Figure 3.8 Some anatomical full-body phantoms. (Reproduced from [72] and [93] with permission from Wiley and IEEE.)

3.3 Human Body and Source Modeling

77

where Prad is the total radiated power by the array (W) and Prad = P 10 , R is the radius from antenna (m), h is the height of aperture (m), and G is the radiating sector panel gain. Geometry is depicted in Figure 3.9. If G is not provided, it can be approximated by that of a uniformly illuminated rectangular aperture for a typical base station sector antenna panel by G(dBi)/10

G=

4π A ef λ2

(3.2)

where Aef is the effective area, which for an uniformly illuminated aperture (ηil = 1), A ef = A ⋅ η il

(3.3)

and, A is the physical area. Although not all the panel size is radiating, if we take A = a ⋅b

(3.4)

where a, b are the height and width of the radome, respectively, the obtained approximated gain value overestimates the antenna gain and hence is valid for compliance testing. Commercial panel antenna gain values range from 10 to 22 dBi.

Figure 3.9

Linear array antenna in cylindrical coordinates.

78

Far-Field Numerical Electromagnetic Dosimetry

To refine predictions of power density in the near-field of an antenna, and hence source modeling, a more sophisticated model is required. Hence, at high frequencies and very close to the array, but at least a half-wavelength away to avoid contributions from strong reactive fields surrounding the array elements [63], E ρ ( ρ, z ) << E z ( ρ, z )

(3.5)

with a power density, 1 1 Re⎧⎨ E z H *φ ⎫⎬ ≈ Ez η 2 2 ⎩ ⎭

2

(3.6)

Since for cylindrical waves radiated close to broadside, Ez ≈ η o H φ

(3.7)

it is possible to measure or compute real power density in an average sense by accurately measuring or computing the ⎪Ez⎪2 field at any distance from the array greater than ∼λ/2, which is orthogonal to the direction of propagation and in fact tends to 2 slightly overestimate the local power density taken as (1/2ηo)⎪Ez⎪ . This allows for a 2 valid measurement of ⎪Ez⎪ to properly assess compliance to guideline levels up until ∼λ/2 close to the radiating aperture [63, 101]. In [99], however, the minimum distance is estimated to be 3λ, and in [100], gain-based models were found to be accurate above 2λ. This is easily observed by simply simulating an array of cross dipoles fed in phase, depicted in Figure 3.10, as it is usual for mobile communications base station panel antennas, with the MoM NEC code. If we calculate the impedance of the propagating along the broadside direction, illustrated in Figure 3.11, we can see that at short distances the impedance behaves in a strange way (reactive zone), and that when we reach the transition zone a value higher than 120π is determined. This means that at those distances the antenna array is behaving as an “electrical” antenna, thus having a predominant Ez. As was expected, the further from the antenna we calculate the wave impedance, the closer it gets to the free space far-field value of 120π. Z

Y X Figure 3.10

The cross dipole antenna array used in the simulations.

3.3 Human Body and Source Modeling

79

390

385

Impedance (Ω)

380

375

370

365

360

Figure 3.11

20

10

0

30 Distance (m)

40

50

60

Calculated wave impedance along the broadside direction.

A closer look at the calculated power density, depicted in Figure 3.12, demonstrates the previous statements, but even in the far-field zone for a base station antenna the free space propagation impedance can differ significantly from 120π due to the destructive or constructive interference of the array elements [102]. Thus, by carefully analyzing and comparing simulated power density to that obtained simply by applying the free space E × H relationship for far-field, also shown in Figure 3.12, we can conclude that previous hypotheses are confirmed, particularly the 3λ distance, from which the difference between true power density and free space approximation is negligible. 1.2 E×H E2/120π

2

Power density (W/m )

1.0 0.8 0.6 0.4 0.2 0.0 0

1

2

3

4

5

6

7

8

9

Distance/wavelength

Figure 3.12 NEC-calculated power density versus far-field formula power density along the broadside direction.

80

Far-Field Numerical Electromagnetic Dosimetry

Yet, it is important to outline that for all these gain-based models that, while the main lobe is generally well matched for all subantennas, results at sidelobe directions may show some discrepancies to real measurements. Only when both the gain pattern of the subantennas and the power distribution of the array can be altered in the simulating model do the results provide excellent results inside the measurement sphere that includes all subantennas and for relatively large E field values [103]. There are yet two other spatial restrictions for the gain-based models. The first is the distance at which exposure is not considered very localized, and hence field evaluation and comparison to reference levels is valid according to ICNIRP guidelines and most standards. Simple and common sense defines the reactive field distance to define localized exposure [99]; that is, r 2 > 0385 . D3 λ

(3.8)

Thus, in order to consider ⎪Ez⎪ evaluation as valid for guidelines level compliance assessment, this must be performed at a distance greater than both 2

r≈ λ

(3.9)

r ≈ 06 . D3 λ

(3.10)

and

that is, whichever is greater. Hence, for a prediction for power density in the far-field of the antenna, the regulatory bodies recommend the use of simple formulas based upon an approximation using radiating apertures, plus a truly worst-case prediction of a power density reflection of incoming radiation at or near a surface. Since these equations are generally accurate in the far-field of an antenna but will overpredict power density in the near-field, they could also be used for making a worst-case or conservative prediction in the near-field, as will be discussed later. The power density can then be derived in this way by S=

PG 4πR 2

(3.11)

2

where, S is the power density (mW/cm ), P is the power input to the antenna (mw), G is the power gain of the antenna in the direction of interest relative to an isotropic radiator, and R is the distance to the center of radiation of the antenna (cm), or S=

EIRP 4πR 2

(3.12)

where, EIRP is the equivalent (or effective) isotropically radiated power, or S=

. ERP 0.41ERP EIRP 164 = = 2 πR 2 4πR 4πR 2

(3.13)

where, ERP is the equivalent radiated power referred to a half-wave dipole radiator.

3.3 Human Body and Source Modeling

81

For a truly worst-case prediction of power density at or near a surface, such as at ground-level or on a rooftop, the U.S. Federal Communications Commission (FCC) [104] assumes a 100% reflection of incoming radiation, resulting in a four-fold increase in (far-field equivalent) power density, S=

(2 )

2

PG

4πR 2

=

PG EIRP = πR 2 πR 2

(3.14)

The Australian Communications Authority [105, 106], on the other hand, recommended until 2003 the prediction of power density emitted by the antenna with S=

2.56EIRP 4πR 2

(3.15)

where the 2.56 factor is the power density increase due to the ground reflection, obtained by assuming a maximum factor of 1.6 in field strength, which in terms of power density yields a 1.6 × 1.6 = 2.56. Yet, this is only an approximation that overestimates the near-field real power density for free-of-obstacles radiating apertures, and the previous equations will considerably over-predict the power density produced by an antenna when the point of interest is not in the far-field of the antenna and the near-field is not free of obstacles. When in the near-field of the antenna, the gain of the antenna is effectively reduced. Additionally, the power density decays directly with increasing distance from the antenna rather than the square of the distance as suggested by previous equations. Other authors employ generic sources using omnidirectional in azimuth and vertically symmetrical radiation patterns for predicting exposure values [50], which for far-field values may be sufficient considering that adjacent sector antenna diagrams usually overlap in order to render the resulting field strength level uniform, as it does for an omnidirectional antenna. Despite the radiation pattern employed, when using array elements some field nonuniformities are inherently expected [58, 108]. In most outdoor dosimetry studies, the highest field levels are obtained on nearby buildings on the main beam direction, and they also show a large nonuniformity on field distribution. A simple way to examine field uniformity for typical panel array antennas like the ones depicted in Figure 3.10 is to evaluate the field uniformity using NEC. This is the same simulation that was performed to get Figures 3.11 and 3.12, but this time calculating the field uniformity along the array axis versus distance from the array in the broadside direction (i.e., the x-z plane in Figure 3.10 is shown in Figure 3.13). From Figure 3.13 one can observe that moving ±1.5m away from the array center in the array axis makes calculated E values depend strongly with distance in the z-axis (away from broadside). At a distance of 12m the variation is not so big, which means that should exposure assessment of compliance testing have to be taken close to the source, a vertical (since panel antennas are normally mounted vertically) spatial uniformity factor has to be considered. In fact, most standards specify that should simulated or measured time-averaged field values vary less than ±10%, a single spatial measurement set at a vertical height of 1.5m to 2m (depending upon the specific standard) from the floor, or an equivalent to the human chest height in other possible situations with no floor, has

Far-Field Numerical Electromagnetic Dosimetry

E (V/m)

82

Offset (m)

Figure 3.13 NEC-calculated field uniformity variation versus distance from the source in the broadside direction.

to be considered. Otherwise, a vertical spatial averaging procedure has to be introduced for proper assessment between 1m and 2m or over an area equivalent to the vertical cross-section of the human body. In this way, the maximum field strengths are evaluated along the main axis of the body in the area of head, chest, and pelvis, at the minimum. It is important to remark that these conclusions and assumptions are valid for a typical antenna array panel, and that for other antennas (i.e., omnidirectional) care must be taken. Field uniformity is further enhanced by environmental reflections [90]. Current base-station antennas can adopt a wide variety of technologies (microstrip, coplanar waveguides, wires, etc.), shapes, beam widths, and polarizations. Thus, the strong dependence of SAR on source characteristics, recently confirmed by measurements in [109], has prompted the need to use simple common generic antennas [96, 110], such as the 0.45λ dipole antenna, to ease comparison between studies, as was commented earlier. Finite-size metal reflectors [35, 58, 100], flanges [96], or other artifacts have also been added to the simple dipole in order to search for specific antenna-related results.

3.4

Simulation Techniques As has been mentioned before, the simplest approximation is to assume far-field exposure, which is called the spherical-wave far-field model, but this is not always the situation and the direct application of far-field patterns to compute near-field power density values also underestimates real magnitudes [59], and more developed refinements are required. Thus, using the far-field formula may be sufficient for compliance testing since far-field formulas tend to overestimate the radiated power density when employed in the close range of the antenna [111], but it is not accurate enough for exposure assessment. For this situation the FCC recommends the use of a cylindrical-wave model [104], which assumes that spatially averaged plane-wave power density values from omnidirectional antennas are equivalent to those provided by dividing the delivered input power by the surface of an imaginary cylinder

3.4 Simulation Techniques

83

surrounding the length on the antenna. For directional antennas, the cylindrical-wave model divides the power by the portion of a cylindrical surface area corresponding to a certain beam width value of the antenna pattern in azimuth. The cylindrical model, however, fails to accurately predict power density values at far-field distances, and some crossover point validation between the two models have been published [111], resulting in crossover validity distances for vertically polarized arrays being dependent upon directional properties of the antenna and its height. A variety of the cylindrical model is the hybrid prediction method which takes advantage of those situations wherein colinear arrays are used as radiating elements to approximate the field by the superposition of the fields of subantennas constituting the antenna, which is described in [50] and [90]. This technique can speed up the simulations and approach validity ranges for as close as nearly one wavelength. Another way to reduce full-wave resources is to combine the spherical waves triples [112] and antenna models [99] with 3D ray tracing propagation models to accurately predict field strength levels in and around the near-field region [113], or use a mixed FDTD-integral equation approach to couple stored FDTD-computed impulse responses of the human body to incident electromagnetic field measured on-site [35]. When accounting for reflections and diffractions, ray-tracing simplification techniques are also useful [114, 115] to be combined with FDTD [90, 116, 117], although their validity is generally limited to the far-field region of the antenna under consideration. Another possibility is to simplify the nearly impossible work of deriving either a close-form or an integral-form expression of the Green’s function for the problem by assuming the exposure to be similar to that of a plane of sources incident on the human body just in front of it, grazing the toes, and calculate the Green’s functions numerically due to a set of spatially narrow pulses selected on the plane of incidence of the field or the source plane [35], as depicted in Figure 3.14. Nevertheless, hybrid simulation engines using full-wave methods combined with ray-tracing or the integral equation [35] for exposure evaluation also tend to overestimate field values, which can be sufficient for compliance testing but rather poor for exposure assessment [50]. This is so despite the combination with ray-tracing still being required to limit the number of reflections and/or refractions to be taken into account and using the far-field radiation pattern of the source and the second with inherent ±10% accuracy. On top of this, ray-tracing techniques also require detailed description of the dielectric properties of materials within the analyzed volume for a correct evaluation of the exposure conditions [90]. Some hybridization between ray-tracing and other techniques for overcoming these drawbacks have been published [50, 90]. Some of the results published in [90] are reproduced in Figure 3.15. Yet, their validity is always limited for distances over the reactive field region; that is, r>>λ and r<2D2/λ. Although hybridized ray-tracing techniques used in the near-field or in the intermediate-field (near- to far-field) regions provide more accurate results than far-field formulas used in the near-field, they still overestimate real near-field values [50]. One good example of this hybridization is the spherical wave concept combined with ray-tracing techniques and the uniform theory of diffraction (UTD) [118] in order to account for building reflections, diffraction, and transmission

Far-Field Numerical Electromagnetic Dosimetry

Layer no.

84

Layer av. SAR (mWkg)

Figure 3.14 Layer average SAR (6-mm human body model) for a plane-wave exposure obtained by FDTD simulation and sum of previously stored impulse responses. Frequency: 835 MHz; Einc = 61.4 V/m rms. (Reproduced from [35] with permission from IEEE.)

6m

Antenna

8m (a)

Antenna 6m

2m

30m (b)

6m

Antenna

30m

20m 10m

(c)

Figure 3.15 Environment geometry for the three cases studied. Dashed lines represent planes not considered in the simulations. (a) Case I: subject on the building roof. (b) Case II: subject on the balcony. (c) Case III: subject on the street. (Reproduced from [90] with permission from IEEE.)

3.4 Simulation Techniques

85

Base station antenna

Human body z

Distance d

x

Figure 3.16

Hybridized exposure scenario in [88]. (Available at http://www.ursi.org.)

(multipath) for near- to far-field (intermediate) regions, performed with good accuracy [50]—yet, always with some overestimation of real intermediate-field values. Another possibility for accurate predictions in the near-field is to use the spherical wave triplets model [50] combined with geometrical optics (GO) and UTD [107] to account for the different contributions of sections of dipoles and the effect of antenna reflection and diffraction for each point source, which has been employed successfully in [50], but still limited to avoid near-field scenarios with or without obstacles. Thus, hybridized ray-tracing techniques are useful to speed up the simulations when carefully accounting for their inherent drawbacks, particularly their limitation in the near-field region and their overestimation in the intermediate-field region. Today hybrid tools are commonplace for simultaneously solving both the nearand far-field problem of electromagnetic exposure, as in [88], where the hybrid method employed in [119] with the finite element method (FEM), the boundary element method (BEM), and the uniform theory of diffraction is combined with FDTD by the discrete formulation of the equivalence principle inside the Yee-mesh of the FDTD method, as depicted in Figure 3.16.

References [1] [2]

[3]

[4] [5]

Decision 473/85 of the Finish Council of Ministers on high-frequency equipment and control thereof, Finland, 1985. Telecommunication Technology Council (TTC) for the Ministry of Posts and Telecommunications, “Radio-Radiation Protection Guidelines for Human Exposure to Electromagnetic Fields,” Deliberation No. 89, Japan, 1997 (in Japanese). Environmental Health Directorate. Health Protection Branch. Canada, Safety Code 6. “Limits of human exposure to radiofrequency electromagnetic fields in the frequency range from 3 KHz to GHz,” 99-EHD-237, 1991. Decision 1474/91 of the Finish Ministry of Social Affairs and Health on limiting exposure to nonionising radiation, Finland, 1991. BG-Vorschrift, Elektromagnetische Felder (BGV 13), Berfsgenossenschaftliche Vorschrift für Sicherheit und Gesundheit bei der Arbeit, Fachausschu Elektrotechnik’’ der BGZ, Fachausschuentwurf, Dezember 1998 (in German).

86

Far-Field Numerical Electromagnetic Dosimetry [6] Österreichisches Normungsinstitut ÖNORM S 1120, “Microwave and radio frequency electromagnetic fields - Permissible limits of exposure for the protection of persons in the frequency range 30 kHz to 300 GHz,” Austria, VORNORM, July 1992. [7] Ordinance of the Ministry of Environment, “EMF in living and natural environment,” Slovenia, 1996 (modified in 2004). [8] Ordinance 61/284 of the Prime Minister, “Factors Harmful for Health in Work Environment,” Poland, 1996 (modified by 124/789 in 1997 and 8/108 in 2000). [9] Telecommunication Technology Council (TTC), “Radio-Radiation Protection Guidelines for Human Exposure to Electromagnetic Fields,” TTC Deliberation No.38, Japan, 1990 (in Japanese). [10] Decreto Ministero dell’Ambiente 10/09/1998 n. 381. “Reglamento recante norme per la determinazione dei tetti di radiofrequenza compatibili con la salute umana,” Gazzeta Ufficiale della Repubblica Italiana, Serie Generale n. 257, Nov. 1998 (in Italian). [11] EMEL 1998. “Guidelines for Limiting Exposure to Time Varying Electric, Magnetic and Electromagnetic Fields in the Frequency Range up to 300 GHz,” Department of Health, Directorate Radiation Control, South Africa, 1998. [12] Ordinance 814.710 sulla protezione dalle radiazioni non ionizzanti (ORNI) (relating to Protection from Non-Ionising Radiation (ONIR)), Switzerland, Dec. 1999. [13] Common Ministerial Decision Act No.1105 of the Ministries of Development, Transport and Communications, Health and Welfare and Environment, Physical Planning and Public Works, “Protection measures for the exposure of the general public to all land based antenna stations,” Greece, Sept. 2000. [14] Ordinance 9/2000 of the Ministry of Transportation and Telecommunications, “Installation process of base stations,” Hungary, May 2000 (withdrawn in 2002). [15] Ordinance 32/2000 of the Ministry of Health, “Reference levels of RF emitted by the radio communication masts,” Hungary, 2000 (withdrawn in 2004). [16] Grand-Duche de Luxembourg, Ministère de l’Environnement and Ministère du Travail et de l’Emploi, “Normes les plus strictes en Europe en matière de radiations en provenance des émetteurs de téléphonie mobile,” Luxemburg, Dec. 2000. [17] Ministerio de la Presidencia, Spain, “Real Decreto 1066/2001, de 28 de septiembre, por el que se aprueba el Reglamento que establece condiciones de protección del dominio público radioeléctrico, restricciones a las emisiones radioeléctricas y medidas de protección sanitaria frente a emisiones radioeléctricas,” Boletín Oficial del Estado (BOE), 29 September, 2001, pp. 36217–36227 (in Spanish). [18] Royal Decree, “Koninklijk besluit van 29 april 2001 houdend de normering van zendmasten voor elektromagnetsiche golven tussen 10 MHz en 10 GHz,” gewijzig door het Koninklijk besluit van 21, Belgium, Dec. 2001 (canceled by the State Council on Dec. 2004). [19] Nationaal Antennebeleid NAB (National Antenna Policy), The Netherlands, 2001. [20] General Advice SSI FS 2002:3, “Allmänna råd om begränsning av allmänhetens exponering för elektromagnetiska fält (Advice on the Limitation of Exposure of the General Public to Electromagnetic Fields),” Sweden, 2002. [21] ARIB STD-T56, “Specific absorption rate (SAR) estimation for cellular phone,” Association of Radio Industries and Business, v2.0, January 2002 (in Japanese). [22] Ordinance 294/2002 on limiting exposure of the general public to non-ionising radiation, Finland, 2002. [23] Decree 2002-775, “Implementation of Article L. 32 of the Posts and Telecommunications Code concerning threshold values for public exposure to electromagnetic fields emitted by telecommunication networks equipment and wireless installations,” France, May 2002. [24] Telekommunikationsgesetz BGBl I Nr. 70/2003, Austria, 2003. [25] Decree 2003-961, “Evaluation of the conformity of terminal telecommunication equipment and wireless equipment, as well as conditions for start-up and use,” France, Oct. 2003.

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[26] “Radiocommunications Electromagnetic Raditaion - Human Exposure Standard 2003,” Australian Communications Authority, March 2003. [27] Law 2004-669, “Electronic communications and audio-visual communications service (Health safety into telecommunications legislation),” France, July 2004. [28] Law 2004-809, “Public health policy (Enhancing the information and dialogue),” France, Aug. 2004. [29] Ordinance 63/2004 of the Ministry of Health, Social and Family Affairs, “Limits of EMF exposure between 0 Hz- to 300 GHz,” Hungary, July 2004. [30] Gandhi, O.P., Lazzi, G., and Furse, C.M., “Electromagnetic absorption in the human head and neck for mobile telephones at 835 and 1900 MHz,” IEEE Transactions on Microwave Theory and Tech., vol. 44, pp. 1884–1897, 1996. [31] Okoniewski, M., and Stuchly, M.A., “A study of the handset antenna and human body interaction,” IEEE Transactions on Microwave Theory and Techniques, vol. 44, no. 10, pp. 1855–1864, Oct. 1996. [32] Jensen, M.A., et al., “EM Interaction of Handset Antennas and Human in Personal Communications,” Proceedings of the IEEE, vol. 83, no. 1, pp. 7–17, January 1995. [33] Balzano, Q., et al., “Electromagnetic Energy Exposure of Simulated Users of Portable Cellular Telephones,” IEEE Transactions on Vehicular Technology, vol. 44, no. 3, pp. 390–403, August 1995. [34] Hombach, V., Meier, K., Burkhardt, M., Kühn, E., and Kuster, N., “The dependence of the EM energy absorption upon human head modeling at 900 MHz,” IEEE Transactions on Microwave Theory and Techniques, vol. 44, pp. 1865–1873, Oct. 1996. [35] Lazzi, G., et al., “A mixed FDTD-integral equation approach for on-site safety assessment in complex electromagnetic environments,” IEEE Trans. Antennas and Propagation, vol. 48, no. 12, pp. 1830–1836, 2000. [36] Vander Vorst, A., et al., “Cellular telephones: Hazards or not?” 2000 IEEE International Symposium on Microwave Theory and Techniques, pp. 937–940. [37] Bernardi, P., Cavagnaro, M., Pisa, S., Piuzzi, E., “Power absorption and temperature elevations induced in the human head by a dual-band monopole-helix antenna phone,” IEEE Transactions on Microwave Theory and Techniques, vol. 49, no 12, pp. 2539–2546, 2001. [38] Lautru, D., et al., “Calculation of the power deposited in a phantom close to a base station antenna using a hybrid FDTD-MoMTD approach,” 30th European Microwave Conference, Paris, pp. 304–307, 2000. [39] Bahr, A., et al., “Occupational safety in the near field of GSM base stations,” 2000 International Millenium Conference on Antennas & Propagation (AP-2000), Davos, Switzerland, 2000. [40] Catarinucci, L., Palazzari, P., and Tarricone, L., “Human exposure to the near field of radiobase antennas—A full-wave solution using parallel FDTD,” IEEE Transactions on Microwave Theory and Techniques, vol. 51, no. 3, pp. 935–940, March 2003. [41] Mason, P.A., Hurt, W.D., Walters, T.J., D’Andrea, J.A., Gajšek, P., Ryan, K.L., Nelson, D.A., Smith, K.I., and Ziriax, J.M., “Effects of frequency, permittivity, and voxel size on predicted specific absorption rate values in biological tissue during electromagnetic-field exposure,” IEEE Transactions on Microwave Theory and Techniques, vol. 48, pp. 2050–2058, Nov. 2000. [42] Durney, C.H., Massoudi, H., and Iskander, M.F., “Radiofrequency Radiation Dosimetry Handbook,” 4th Ed., USAFSAM-TR-85-73, Brooks AFB, Texas, 1986. [43] IRPA, “Guidelines on limits of exposure to radiofrequency electromagnetic fields in the frequency range from 100 kHz to 300 GHz,” 1988. [44] National Radiological Protection Board (NRPB), “Electromagnetic fields and the risk of cancer, Report of an Advisory Group on Non-ionising Radiation,” Doc. NRPB, 3, No.1, pp.1–138, 1992. [45] UNEP/WHO/IRPA, “Electromagnetic fields (300 Hz to 300 GHz),” Environmental Health Criteria 137, World Health Organization, Geneva, 1993.

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Far-Field Numerical Electromagnetic Dosimetry [46] International Commission on Non-Ionizing Radiation Protection (ICNIRP), “Health issues related to the use of hand-held radiotelephones and base transmitters,” Health Physics, vol. 70, pp. 587–593, 1996. [47] International Commission on Non-Ionizing Radiation Protection, “Guidelines for limiting exposure to time-varying electric, magnetic, and electromagnetic fields (up to 300 GHz),” Health Physics, vol. 74, pp. 494–522, 1998. [48] European Council, “Council Recommendation of 12 July 1999 on the limitation of Exposure of the General Public to Electromagnetic Fields (0 Hz – 300 GHz),” Official Journal of the European Communities, L199, pp. 59–70, July 30, 1999. [49] Watanabe, S.I., Taki, H., Nojima, T., and Fujiwara, O., “Characteristics of the SAR distribution in a head exposed to electromagnetic fields radiated by a hand-held portable radio,” IEEE Transactions on Microwave Theory and Techniques, vol. 44, pp. 1874–1883, Oct. 1996. [50] Barbiroli, M., Carciofi, C., Degli-Esposti, V., and Falciasecca, G., “Evaluation of exposure levels generated by cellular systems: Methodology and results,” IEEE Trans. on Vehicular Technology, vol. 51, no. 6, pp. 1322–1329, 2002. [51] Simunic, D., “Measurements of RF and far fields,” Proceedings of the WHO International Seminar on Biological Effects, Health and Consequences and Standards for Pulsed Radiofrequency Fields, Nov. 1999. [52] Golombeck, M.A., Dössel, O., Staubert, A., and Tronnier, V.M., “Numerical models of the human body applied to EMC-problems in the surgery room for the future,” Compendium of the 4th European Symposium on Electromagnetic Compatibility, pp. 193–198, Sept. 2000. [53] Stuchly, S.S., Kraszewski, A., Stuchly, M., Hartsgrove, G., and Spiegel, R.J., “RF energy deposition in a heterogeneous model of man: Far-field exposures,” IEEE Transactions on Biomedical Engineering, vol. 34, pp. 951–957, Dec. 1987. [54] Gandhi, O.P., Gu, Y., Chen, J.Y., Bassen, H.I., “Specific absorption rate and induced current distributions in an anatomically based human model for plane-wave exposure,” Health Physics, vol. 63, pp. 281–290, Sept. 1992. [55] Martínez-Búrdalo, M., Nonídez, L., Martín, A., and Villar, J., “Using a combination of FDTD with a surface integration method for electromagnetic scattering analysis in large regions,” Microwave and Optical Technology Letters, vol. 22, pp. 74–78, 1999. [56] Martínez-Búrdalo, M., Nonídez, L., Martín, A., and Villar, J., “A combination of time-domain versions of PO and PTD with the FDTD method to evaluate human exposure to an electromagnetic field in an urban environment,” Microwave and Optical Technology Letters, vol. 31, pp. 371–374, 2001. [57] Martínez-Búrdalo, M., Nonídez, L., Martín, A., and Villar, J., “On the calculation of safety distances for human exposure to electromagnetic fields from base-station antennas,” Microwave and Optical Technology Letters, vol. 34, no. 5, pp. 364–367, 2002. [58] Meyer, F.J.C., Davidson, D.B., Jakobus, U., and Stuchly, M., “Human exposure assessment in the near field of GSM base-stations antennas using a hybrid finite element/method of moments techniques,” IEEE Trans. on Biomedical Engineering, vol. 50, no. 2, pp. 224–233, Feb. 2003. [59] Blanch, S., Romeu, J., and Cardama, Á., “Near field in the vicinity of wireless base-station antennas: An exposure compliance approach,” IEEE Transactions on Antennas and Propagation, vol. 50, no. 5, pp. 685–692, May 2002. [60] European Committee for Electrotechnical Standardization (CENELEC), EN50361:2001, “Basic standard for the measurement of specific absorption rate related to human exposure to electromagnetic fields from mobile phones (300 MHz – 3 GHz),” Sept. 2001. [61] European Committee for Electrotechnical Standardization (CENELEC) EN50360:2001, “Product standard to demonstrate the compliance of mobile phones with the basic restrictions related to human exposure to electromagnetic fields (300 MHz – 3 GHz),” Sept. 2001.

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[62] Karwowski, A., “Evaluating exposure to radio-frequency emissions from base station antennas,” Proceedings of the IEEE Microwaves, Radar and Wireless Communications, International Conference, pp. 1877–1881, 2002. [63] Faraone, A., Roger Yew-Siow Tay, Joyner, K.H., and Balzano, Q., “Estimation of the average power density in the vicinity of cellular base station collinear array antennas,” IEEE Transactions on Vehicular Technology, vol. 49, no. 3, pp. 984–996, 2000. [64] Cooper, J., Marx, B., Buhl, J., and Hombach, V., “Determination of safety distance limits for a human near a cellular base station,” Proceedings of the 22nd Annual Meeting of the Bioelectromagnetics Society, pp. 16–17, June 2000. [65] Hassanin, A.I.M., “Biological effect of mobile telephone inside the human brain,” Proceedings of the 2001 IEEE Antennas and Propagation Society International Symposium, Vol. 2, pp. 88–91, 2001. [66] Jakobus, U., Ruoss, H.-O., Geisbusch, L., and Landstorfer, F.M., “Hybridisation of MoM and GMT for the numerical analysis of electromagnetic sources radiating in the vicinity of persons with implanted cardiac pacemakers,” Proceedings of the 2nd IEEE AFRICON Conference, vol. 2, pp. 1041–1044, Oct. 1999. [67] Meier, K., Hombach, V., Kästle, R., Tay, R.Y.S., and Kuster, N., “The dependence of electromagnetic energy absorption upon human head modeling at 1800 MHz,” IEEE Transactions on Microwave Theory and Techniques, vol. 45, pp. 2058–2062, Nov. 1997. [68] Lazzi, G., and Gandhi, O.P., “Realistically tilted and truncated anatomically based models of the human head for dosimetry of mobile telephones,” IEEE Transactions on Electromagnetic Compatibility, vol. 39, pp. 55–61, Feb. 1997. [69] Bernardi, P., Cavagnaro, M., Pisa, S., and Piuzzi, E., “Evaluation of human exposure in the vicinity of a base station antenna using the multiple-region / FDTD hybrid method,” IEEE International Symp. on Microwave Theory and Techniques, pp. 1747–1750, 2002. [70] Yee, K.S., “Numerical solution of initial boundary value problems involving Maxwell’s equations in isotropic media,” IEEE Transactions on Antennas and Propagation, vol. 14, pp. 302–307, May 1996. [71] Taflove, A., Advances in Computational Electrodynamics: The Finite Difference Time Domain Method, Norwood, MA: Artech House, 1998. [72] Christ, A., Chavannes, N., Nikoloski, N., Gerber, H.U., Pokovic, K., and Kuster, N., “A numerical and experimental comparison of human head phantoms for compliance testing of mobile telephone equipment,” Bioelectromagnetics, vol. 26, pp. 125–137, 2005. [73] Fayos-Fernández, J., Arranz-faz, C., Martínez-González, A.M., and Sánchez-Hernández, D., “Effect of pierced metallic objects on SAR distributions at 900 MHz,” Bioelectromagnetics, vol. 27, pp. 337–353, 2006. [74] DeFord, J.F., Gandhi, O.P., and Hagmann, M.J., “Moment-method solutions and SAR calculations for inhomogeneous models of man with large number of cells,” IEEE Transactions on Microwave Theory and Techniques, vol. 31, pp. 848–851, 1983. [75] Spiegel, R.J., “A review of numerical models for predicting the energy deposition and resultant thermal response of humans exposed to electromagnetic fields,” IEEE Transactions on Microwave Theory and Techniques, vol. 32, pp. 730–746, 1984. [76] Stuchly, M.A., Kraszewski, A., and Stuchly, S.S., “Exposure of human models in the nearand far-field – A comparison,” IEEE Transactions on Biomedical Engineering, vol. 32, pp. 609–615, 1985. [77] Stuchly, S.S., Kraszewski, A., and Stuchly, M.A., “Energy deposition in a model of man in the near-field,” Bioelectromagnetics, vol. 6, pp. 115–130, 1985. [78] Stuchly, S.S., Stuchly, M.A., Kraszewski, A., and Hartsgrove, G., “Energy deposition in a model of man: Frequency effects,” IEEE Transactions on Biomedical Engineering, Vol. 33, pp. 702–711, 1986. [79] Guy, A.W., Chou, C.K., and Neuhaus, B., “Average SAR and SAR distribution in man exposed to 450 MHz radiofrequency radiation,” IEEE Transactions on Microwave Theory and Techniques, vol. 32, pp. 752–762, 1984.

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antenna,” Proceedings of the IEEE International Symposium on Microwave Theory and Techniques, pp. 1449–1452, 2004. Kuster, N., Schuderer, J., Christ, A., Futter, P., and Ebert, S., “Guidance for exposure design of human studies addressing health risk evaluations of mobile phones,” Bioelectromagnetics, vol. 25, pp. 524–529, 2004. Chen, W.-T., and Chuang, H.-R., “Numerical computation of the Em coupling between a circular loop antenna and a full-scale human-body model,” IEEE Transactions on Microwave Theory and Techniques, vol. 46, no. 10, pp. 1516–1520, 1998. Bizzi, M., and Gianola, P., “Electromagnetic fields radiated by GSM antennas,” Electronics Letters, vol. 35, no. 11, pp. 855–857, 1999. Altman, Z., Begasse, B., Dale, C., Karwowski, A., Wiart, J., Wong, M.F., and Gattoufi, L., “Efficient models for base station antennas for dosimetric analysis,” IEEE Transactions on Electromagnetic Compatibility, vol. 44, no. 4, pp. 588–592, Nov. 2002. Balzano, Q., and Faraone, A., “Peak and Average RF Safety Compliance Levels near Radio Base Station Antennas-Prediction Formulas and Numerical Validation,” Proceedings of the International Symposium on Electromagnetic Compatibility, vol. 2, pp. 780–785, 2001. Olivier, C., and Martens, L., “A more accurate method to define exclusion zones,” Proceedings of the IEEE Radio and Wireless Conference (RAWCON), pp. 107–110, 2000. Adane, Y., Gati, A., Wong, M.F., Dale, C., Wiart, J., and Hanna, V.F., “Optimal modeling of real radio base station antennas for human exposure assessment using spherical-mode decomposition,” IEEE Antennas and Wireless Propagation Letters, vol. 1, pp. 215–218, 2002. Federal Communications Commission, OET Bulletin 65, “Evaluating Compliance with FCC Guidelines for Human Exposure to Radiofrequency Electromagnetic Fields,” Ed. 97-01, 1997. “Radiocommunications (Electromagnetic Radiation — Human Exposure) Standard 1999,” Australian Communications Authority, 1999. “Human Exposure to Radiofrequency Electromagnetic Energy,” Information for licensees or operators of radiocommunications transmitters: Evaluation of compliance with the ACA standard, Australia, September 2000. Kouyoumjian, R.G., and Pathak, P.H., “A uniform GTD for an edge in perfectly conducting surfaces,” Proceedings of the IEEE, vol. 62, pp. 1448–1461, Nov. 1974. Sánchez-Hernández, D., and Martínez-González, A., “Aspectos técnicos susceptibles de mejora sobre el protocolo de medición de estaciones base de telefonía móvil: Los trabajos de normalización de CENELEC y JRC-ISPRA en el seno de la Comisión Europea,” Proceedings of URSI National Symposium, 2002 (in Spanish). van Wyk, M., Bingle, M., and Meyer, F.J.C., “Antenna modeling considerations for achúrate SAR calculations in human phantoms in close proximity to GSM cellular base station antennas,” Bioelectromagnetics, Vol. 26, pp. 502–509, 2005. Chen, J.Y., and Gandhi, O.P., “RF currents induced in an anatomically-based model of a human for plane-wave exposures (20 – 100 MHz),” Health Physics, vol. 57, pp. 89–98, 1989. Karwowski, A., “Numerical modeling calculations for evaluating exposure to radio-frequency emissions from base stations antennas,” Proceedings of the IEEE Microwaves, Radar and Wireless Communications, International Conference, pp. 809–812, 2002. Carli, E., Gianola, P., Lombardi, G., Mania, L., and Vescovo, R., “Antenna models for field level evaluation in proximity of GSM base stations,” EPMCC’99, Paris, March 1999. Barbiroli, M., Carciofi, C., Falciasecca, G., and Frullone, M., “Analysis of field strength levels near base station antennas,” Proceedings of the IEEE International Conference on Vehicular Technology, vol. 1, pp. 156–160, 1999. Liang, G., and Bertoni, H.L., “A new approach for 3-D ray tracing for propagation prediction in cities,” IEEE Transactions on Antennas and Propagation, vol. 46, pp. 853–863, 1998.

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CHAPTER 4

Near-Field Numerical Electromagnetic Dosimetry Antonio M. Martínez-González

4.1

Phantom and Source Modeling 4.1.1

Phantom Developments

The RF energy deposition in biological tissue has been studied with a large variety of human and animal models. Homogeneous and heterogeneous models of man were reviewed in 1984 [1], and complemented and improved in 1987 [2] with a CT scan of an anatomically correct model developed from a skeleton with all major bones. Partial anatomically correct models based on the skull were also available in the 1980s [3], depicted in Figure 4.1, and have also been employed until recently, such as the basic layered anatomical shaped model (BLAS) [4], where four different tissues have been incorporated: muscle, brain, cartilage, and humor vitreous. Other examples are the 5-tissue model in [5] extracted from an anatomy atlas with 6.56-mm spatial resolution, the 5-tissue models M4, E1, E2, and E3 in [6], or the 7-tissue head and hand model in [7], also depicted in Figure 4.2. Despite the early availability of partially anatomical models, in the first studies a simple sphere of homogeneous tissue and 105.5-mm radius or a semi-infinite cylinder were considered to represent a simplified average adult head [9, 10] or body [4, 11, 12] model, respectively, and even with an appropriate tissue selection, also considered to provide more conservative results than more detailed models [6, 10, 13–15]. Models tabulated to a 6% at 900 MHz and a 15% at 1,800 MHz can also be found in [16]. Recent studies still use this simple model, but mainly reduced to algorithm validation or comparison purposes since SAR values are not directly linked to head size [17], as in [8] with its entire plain interaction (EPI) model, [18], or [19]. Today, the choice of the equivalent tissue for the homogeneous sphere is still the subject of research [21, 23], since early studies use muscle or 2/3-muscle tissue [11] whereas CENELEC [20] recommends a head simulating liquid (HSL) similar to the brain for compliance testing. This selection is justified by the fact that, for a source position at or above the ear, brain constitutes the most relevant tissue and provides the highest absorption values [22]. Recent studies have demonstrated that the conservative character of the simple sphere can only be valid with appropriate tissue selection if just the head is considered [24] and not for all possible situations

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(a)

(b)

Figure 4.1 Head models used in the experiments in [3] with eye-equivalent tissue placed in eye sockets, and muscle-equivalent tissue placed at appropriate locations on skull surface. Radio with 1/2-wave antenna in tilted position (a), and radio with 1/4-wave antenna in vertical position (b). (Reproduced from [3] with permission from John Wiley & Sons.)

z

y

x

Figure 4.2 The Basic Anatomical Layered Shaped model (BLAS) in [8], the 5-tissue head models (E1, E2, and E3) in [6], and the 7-tissue head and hand model (ATLAS) in [7].

and models [25]. Therefore, more detailed and realistic models have been developed. Other canonical shapes employed include the rectangular box, which is typically used to simulate the human torso [26].

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Simple, full-scale human body models have also been employed [27, 29], but their use has been limited. Much more detailed 3D human body models developed from nuclear magnetic resonance imaging were soon made available. The Herschey Medical Center (USA) developed a 132 × 84 × 390 grid of 5-mm cells including 23 different biological tissues, named the REMCOM model since it was adopted by this software brand; and the U.K. National Radiological Protection Board (NRPB) phantom, NORMAN, was derived from a series of continuous partial body (head, thorax, abdomen, thighs, knees, and feet) MRI scans of a single subject. NORMAN (NORmalized MAN) was made by Noah Clinch of Fairfield Imaging (USA) in 1995, and was first interpreted into 38 tissue types and structured in a 3D array of cells and ~2-mm voxels [28] and normalized to be 1.76m tall and 73 kg in weight. These were the values for the reference man of ICRP 66 [30], with tissues extracted from [31] and 4-Cole-Cole dispersion models. NORMAN was later fine-tuned to include organs, which were not discovered in the primary segmentation, such as the prostate or the male breast, and to differentiate diverse organs such as the stomach from its contents: bladder from urine, gall bladder from bile, esophagus from air, and lungs from air. Some secondary segmentation of NORMAN was due to the results obtained with its predecessor, based upon a survey of 20 colleagues [32]. For instance, NORMAN ankles and lower legs, which were rather thick, were tapered and skin and subcutaneous fat were separated from an original solo tissue. NORMAN was also rescaled to reproduce the heights and masses of reference 10, 5, and 1-year old children [33]. The sagittal slices of NORMAN are depicted in Figure 4.3, while Figures 4.4 and 4.5 reproduce the isolated and grounded conditions, respectively, demonstrating that while ~35-MHz resonance frequencies are found for grounded conditions, this is shifted up to ~65 MHz when the model is isolated. Some other MRI-based models were also available in 1995, such as the original Gent head model [34], which had a resolution of 3.9 × 3.9 × 4.7 mm3 (5 mm in the 3 vertical direction), and was later enhanced to 1.1 × 1.1 × 1.4 mm (1.7 mm in the vertical direction) and 26 tissues at Yale University (named the Yale head model [14]), and to a 3-mm head model by Salt Lake City University [36] employing 15 tissues. The University of Utah also developed an anatomical model, originally named 3 Model A and employing a resolution of 1.974 × 1.974 × 3 mm [36]. Model A was later enhanced (Model B) to a resolution of 0.9375 mm for each of the cubical 3 voxels (0.987 × 0.987 × 1 mm ) of 15 different tissue types [37] and a pinna thickness of 14 mm [46]. The Brooks digital anatomical man model employed 3-mm resolution slices [18]. The European female model (FEM40Y-CE) was created from a 40-year-old female volunteer with the ear slightly compressed (4 mm thick). In the ear region, the slices have a thickness of 1 mm, while 3 mm are used elsewhere. A 25-year-old version of the European female model (FEM25Y-CE) was developed by Ericsson Research, but with a slightly compressed pinna thickness of 10 mm and 2-mm slices all throughout the model. Some anatomically correct human body models have also been provided with MRI scans in the Visible Human Project [38, 39], including the adult male head phantom (VHAD) provided by Motorola Corporate EME Research Laboratory, which includes 40 different tissue types, as well as some scaled-down versions, all with 1 × 1 × 1 mm3 resolution. More realistic 3- and 7-year-old children head models obtained from real scanned images of children have also been reported [40–42].

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Figure 4.3 Sagittal slices of NORMAN. (Reproduced from [33] with permission from Institute of Physics Publishing.)

0.10

SAR, mW kg

−1

0.08

0.06

0.04

0.02

0.00 10

100

1000

Frequency, MHz

Figure 4.4 Whole-body averaged SAR for adult NORMAN under isolated conditions. (Reproduced from [35] with permission from Institute of Physics Publishing.)

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0.10

SAR, mW kg

−1

0.08

0.06

0.04

0.02

0.00 10

100 Frequency, MHz

1000

Figure 4.5 Whole-body averaged SAR for adult NORMAN under grounded conditions. (Reproduced from [35] with permission from Institute of Physics Publishing.)

European children head models [40] consisted of 15 different tissues and a spatial resolution of 1 mm with pinna thickness of approximately 4 mm. The Japanese 7and 3-year-old children head models [42], illustrated in Figure 4.6, were scaled down from an adult head model (provided by the Department of Electrical and Computer Engineering of the Nagoya Institute of Technology in Japan). The Japanese adult head model was derived from a 23-year-old Japanese adult male head and segmented into 17 different tissues of a 2-mm spatial resolution model. The Japanese scaled-down children versions, named “childlike” by some authors, employed different scaling factors for different parts of the head, which provided a more realistic approximation of the child’s head than the uniform scaling used in the visible human head models [42], but are also limited by their inherent nonuniform growth of organs [43]. The reason for providing children models was that there was some contradictory findings regarding the possibility of children absorbing more RF energy than Head breadth Bizygomatic breadth Vertex-pupil height

Adult head Bigonial breadth

Scaled head with 7-year-old database

Head length

Pupil-stomion height Stomion-gnathion height

Scaled head with 3-year-old database

Figure 4.6 Japanese anatomical head models in [42]. (Reproduced from [42] with permission from IEEE.)

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adults [19, 36, 40–42, 44, 46], which lead to a COST281 short-term mission and a joint WHO/EMF-NET/COST281/ICNIRP workshop in 2004. It was concluded in the 2004 workshop—a summary of which has been published as a special issue of Bioelectromagnetics—that there is no direct evidence that children are more vulnerable to EMF. The workshop also concluded that there is little research addressing the issue, which was also stated in [47], and identified this as a key gap in various research agendas worldwide. Collaboration between the National University of Singapore and Johns Hopkins University also produced an anatomical model of the Sprague-Dawley man previously described in [48, 49] but using the VHP images with larger voxel sizes of 3 and 5 mm3 and 39 different tissue types. In 2001 a standardized anthropomorphic head phantom, the specific anthropomorphic mannequin (SAM), was developed to be included in the two different recommended measurement techniques for determining peak spatial-average SAR from wireless communications devices, EN 50361 and IEEE 1528 and 1529. Prior to SAM, the generic twin phantom (GTP) [16] was formerly used for compliance testing [17]. The GTP model was developed from statistics taken from 52 male and female adult volunteers, and its ear is represented by a lossless spacer with a radius of 15 mm and a thickness of 2 mm positioned at the location of the auditory canal, leading to an overall shell thickness of 4.7 mm in the ear region. Except for the ear protrusions, SAM was derived from a subset of the 90th percentile dimensions from a survey of U.S. Army male personnel [44]. The model, which was intended to be used in measurements with a tissue simulating liquid, was considered conservative at the time, yet today several studies are questioning its validity, particularly since new wireless applications with diverse positioning, sometimes away from the head, are becoming commonplace [50]. Some studies found that SAM underestimated SAR by a factor or two or more [46], while others found that SAM overestimated SAR [51, 52]. In 2005 it was demonstrated that results for compliance testing using SAM represented a more conservative approach than those performed with the GTP [17]. A recent study [41] has demonstrated, however, that there were other factors that strongly influenced most previous studies. These include the treatment of the pinna, phone positioning, and the SAR averaging algorithm, among others. Despite these discrepancies, and comparing SAM to other 14 different anatomical models, SAM cannot always be considered a conservative estimate in accordance with ICNIRP guidelines which require inclusion of the pinna in the SAR evaluation or should the evaluation be conducted for contiguous tissue and not for a 10g cube [41]. Similar discrepancies between cube or contiguous (any) 10g tissue averaging methods were found in [53]. SAR values using any 10g averaging volume nearly doubled those using the 10g cube, and even within the same cube the allowed percentage of air inclusion within the averaging tissue strongly affects SAR values [55]. This suggests a maximum permissible air inclusion of 5% to 20% [54], but also states that the cubic-volume method may not define well the mass-averaged SAR at tissue points around a complex shape containing air. This may happen in the exterior layers of various internal human cavities (maxillary or ethmoidal sinus) or small volume regions such as fingers [56]. Different results were also found in [41] depending upon the normalization performed, either to the feed point current or to the power. Some advanced averaging methods have also been proposed [57].

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99

Some French anatomical models of adults (FTRD, COMOBIO) are also available [43], derived from the VHP, and illustrated in Figure 4.7. The French ADONIS program of the RNRT research network is working towards the development of age-dependent children anatomical head models with eight tissues and a millimetric resolution. Other described anatomical models are also depicted in Figure 4.8. In many of these models, pinna is a source of controversy, and this was recently the subject of a detailed intercomparison study between 14 different realistic head phantoms [41] since the definitions in diverse standards diverge. The pinna is defined as the largely cartilaginous projecting portion of the outer ear consisting of the helix, lobule, and antihelix. According to IEC [59, 60], for instance, the exciting source has to be located directly above the ear reference point (ERP), that is, at a lateral distance of 15 mm from Tragion (entrance to the ear canal, EEC). Although only [61] provides a relaxation of limits for the pinna, it also states that this relaxation has to be considered without violating the general provisions. This definition, however, may sustain different physical interpretations. It has been published that if the limited SAR values for the head tissue are met, the values for the pinna treated as

Figure 4.7 Anatomical FTRD adult, childlike, and children head models. (Reproduced from [43] with permission from John Wiley and Sons.)

Figure 4.8 Anatomical head models developed from MRI scanning. (Reproduced from [58] with permission from John Wiley and Sons.)

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an extremity are intrinsically met as well [17, 58]. Yet, it has also been published that a 6-mm thick smooth plastic pinna, such as the one available in SAM, results in a calculated peak 10g averaged SAR that may be up to two or more times smaller than realistic anatomical models for SAR compliance [50]. To minimize pinna discrepancies when performing the simulations, some models employ an ear completely attached to the head—what has been called “compressed” or “collapsed” pinna. This happens, for example, in the BLAS model in [62] since it was also found that a very thin spacer or no ear would overestimate the exposure in the area above the ear [22] and that when using various ear-connection structures and a thin lossless dielectric spacer to emulate the actual human anatomical condition, the effect on 1g averaged peak SAR was negligible [64]. In this way, the losses in the outer ear are compensated in the measurements by the replacement of the low-loss structure of the inner ear, including bony structure and air cavities, through the lossy tissue simulating material [22]. It has to be mentioned, however, that spatial-peak SAR values averaged over a cube of 10g are much less sensitive to the modeling of the ear and no underestimation on these values is produced due to ear modeling as a spacer in [22]. The spacer is the technique used in the measurement setup for SAM in DASY4. The underestimation of peak SAR averaged over 1g when using a spacer to simulate the ear could be as high as 1 dB [22]. Pinna treatment is the subject of current research and a source of discrepancy between guidelines. Today, a 2-mm resolution is considered sufficient for compliance testing, but sub-millimeter resolution models are available. Cell dimensions as small as 0.5 mm [65], 0.4 mm [63], or 0.25 mm [66] have been published, although these are limited to specific organs. The availability of these models, however, has allowed a very detailed simulation of the eye’s vascularization and its capacity to cope with excess heat. The inherent capabilities of the eye to transfer excess heat away have been found to be higher that initially supposed [66]. Figure 4.9 shows analytical and numerically computed temperature in a 10 cm diameter cylinder exposed to a plane wave of power density 10 mW/cm2. 4.1.2

Source Modeling

The high frequency employed for commercial digital wireless communications systems may require a rather large number of cells for whole-body modeling, creating large computational problems; yet accurate modeling of the source is essential for proper electromagnetic coupling characterization and hence accurate exposure assessment and SAR calculation. Since third generation (3G) systems employ even higher frequencies than 2G systems, this modeling problem is emphasized. Adaptive meshing is sought as the appropriate technique to comply with conflicting requirements of accurate source modeling at an as-low-as-possible computational cost with uniform meshing within tissues for adequate SAR averaging procedures. This has called up again the need for alternatives to FDTD such as the method of moments (MoM) combined with the coupled integral equations (CIE) [27] or coupled to the FEM method [67]. The FEM alternative, however, has a trade-off between its typical tetrahedral representation versus the cubical form of FDTD, which provides less computational requirements for low-frequency problems, and its need to refine the model as frequency increases, which can lead to a factor of eight increase in memory

4.1 Phantom and Source Modeling

101

Figure 4.9 Temperature distribution in the test cylinder at 2-MHz irradiation. Comparison of analytically and numerically computed temperature.

and solution time, while FDTD may remain the same [67]. This has left FEM basically for small-size near-field problems or for hybridization techniques. Special care has to be taken into account when increasing the mesh size around the antenna so that the thin-wire model employed does not appear as an infinitely thick wire. This could stimulate important deviations in resonance frequency and in local SAR values since when employing the thin-wire model these are 18% to 20% higher than those predicted using the thick-wire model [68]. A ∼λ/2 dipole antenna is the most commonly employed source for SAR evaluation [2] in the near-field at diverse positions, orientations, and distances from the human model and with different input powers. For handset exposure, SAR is usually normalized to 1W of antenna input power [2], and since base station antennas can handle different output powers, normalizing to 1W is also useful for these situations [24]. The choice of the ∼λ/2 dipole antenna is due to the necessity to simplify the source structure, since mobile phone design is continuously changing and nowadays it is possible to find a large variety of shapes and sizes for handsets. In fact, a typical exposure for mobile phones does not exist [16]. Other reasons for using the ∼λ/2 dipole antenna is to select a source position with respect to the head that is repeatable and enables interexperimental comparison [69], and to minimize discrepancies of measured values for different phantoms sizes [42] and for differences between homogeneous and heterogeneous head models due to the antenna [70]. Moreover, substituting commercial handset antennas with the dipole allows for a detailed knowledge of antenna impedance and reflected power, which represents a crucial parameter for proper SAR distribution validation and can be directly compared to measurements with the same antenna using the available near-field scanners, which will be described further on.

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The distance between the antenna and the human head model is also another important parameter. When the antenna is mounted on a metal box, this can significantly change depending upon the antenna selection (helix, monopole, integrated, etc.) and its relative position. In fact, axial ratios have been reported to increase with the presence of the human head when circularly polarized antennas such as circular or square helices are used [5]. Additionally, the metal box model is not an accurate model for modern mobile phones, with RF currents differing considerably from real mobile phones, and a simple generic mobile phone model was agreed upon with members of the Mobile Manufacturers Forum (MMF). The generic mobile phone, reproduced in Figure 4.10 [41] is composed of a solid plastic box of 102 × 42 × 21 mm3 with the PCB modeled as a 1-mm thick plate representing a perfect electrical conductor (PEC) embedded in the body of the generic mobile phone. The agreement upon a generic mobile phone is of extreme importance since when no standard dipole source is chosen and the simulation has to be evaluated with the antenna mounted on the phone box, it has been demonstrated that the box size and other parameters have a significant effect on SAR values [37]. It is known that special care has to be taken to accurately evaluate the antenna output power since its settings can constitute a large uncertainty component [68]. Some studies use a sinusoidal current of 250 mA peak amplitude as a feeding signal. Others employ a sinusoidal voltage of 18 volts. The purpose is to get a ∼2W radiated power at the antenna in CW mode, which is similar to the maximum theoretical power radiated by a commercial GSM phone (without considering the time-multiplexing scheme of GSM) and represents the maximized spectral power required for the signal characteristic which will provide conservative peak spatial average SAR values as described in [69]. There is however a large diversity of nomi-

Z Y

40 mm 42 mm Width

21 mm

102 mm 100 mm

Height

X

LA

Z

Depth

Figure 4.10 Generic mobile phone designed for the intercomparison protocol in [71]. (Reproduced from [71] under the Creative Commons Attribution License. Available at http://www.biomedical-engineering-online.com/content/3/1/34.)

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nal output powers from handsets for the different systems and classes allowed on these systems, as illustrated with some examples in Table 4.1. Consequently, other works try to simulate the 0.24W GSM typical operation and do not use the 250-mA feed current. Yet, by employing a constant feed point current or voltage and normalizing all values to radiated power, the effect of impedance mismatch for diverse scenarios on the evaluation of different parameters is avoided. A CW excitation is then used to carry out a simulation at a fixed frequency with the peak E-fields being found during the final cycle of the simulation, which has to have a stable condition—that is, when transient effects have decayed. Such CW exposure also allows for future biophysical interpretation [69], although conclusions for commercial systems require specific signal postprocessing such as discontinuous transmission (DTX) for GSM or pilot power measurements (RSCPCPICH) for UMTS, among others [72]. In contrast, antenna lengths chosen slightly shorter than a quarter wavelength can also achieve acceptable input impedance next to different head models, and this has demonstrated to provide higher peak 1g averaged SAR than longer antennas [37, 73].

4.2

Simulation Techniques Numerical simulations for the closest proximity to a base station antenna formed by four metal dipoles, including distances within the reactive near-field region, were performed in [24] at 935 MHz using the finite integration technique (FIT) employed in the commercially available MAFIA software code [74]. A Visible Human Project human body model was placed facing base station antenna dipoles at diverse distances, as depicted in Figure 4.11, and the simulations for this heterogeneous body model showed the antenna-body distances for which the whole-body and maximum local SAR values fell below both the occupational and general public electromagnetic exposure threshold levels for both ICNIRP and the IEEE standard in force at the time. A recent alternative for using a full-wave simulator in the near-field problem was proposed in [67], wherein FEM, which can model efficiently the heterogeneous human body, was coupled to the MoM, which is efficient for calculating antenna problems involving metallic plates and wires. This hybrid was previously applied successfully to internal dosimetry problems using handsets [75, 76]. Unlike the cubical cells typically used in FDTD, FEM could employ tetrahedral meshing, with its inherent variable element size, and although dense matrices were obtained no 3D Table 4.1 Maximum Nominal Output Powers for GSM900, GSM1800, UMTS, and TETRA Systems Power Class

GSM 900

GSM 1800

UMTS

TETRA

1

N/A

1W (30 dBm)

1W (30 dBm)

30W (45 dBm)

2

8W (39 dBm)

0.25W (24 dBm)

0.25W (24 dBm)

10W (40 dBm)

3

5W (37 dBm)

4W (36 dBm)

0.125W (21 dBm)

3W (35 dBm)

4

2W (33 dBm)

—

0.01W (10 dBm)

1W (30 dBm)

5

0.8W (29 dBm)

—

—

0.3W (25 dBm)

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Figure 4.11 Geometry of base station antenna model and VHP model in [24]. (Reproduced from [24] with permission from John Wiley and Sons.)

space had to be discretized with the hybrid approach. The problem size makes it impractical to use FEM alone [67], but with the hybrid FEM/MoM, only the base station antenna and its coupling to the FEM enclosure are modeled by the MoM while the FEM is used to solve the field problem in the heterogeneous model, avoiding the need to discretize the relatively large space between the antenna and the human body. So far, only half-body studies have been presented with this technique, leading to lower exposure values in the near-field than those obtained with free-space formulas, and thus more accurate results than any other previous simulation technique, but its similarity to real near-field values is yet to be evaluated. Instead of hybridizing the full-wave approach to ease computational demands, one can make use of readily available parallel computing, as was done in [77], where a single-instruction multiple-data (SIMD) platform using a multiprocessor architecture was able to calculate the near-field problem of base station exposure taking almost 2 GB of RAM and 104 GFlop in less than 1 hour. Yet, in this study it was also demonstrated that for intimate distances to the antenna (30 cm or less) large discrepancies (up to 40%) were encountered, associated with the diverse human phantom models employed. A good example of the effect of these factors on final values can be illustrated by searching in the literature the SAR values encountered for similar commercial base station antennas. One typical brand used in the literature is Kathrein, and in particular its vertically polarized “Eurocell panels” [78]. In [79], the Kathrein 730370 panel antenna is analyzed with a simplified calculation model, consisting of an array of four collinear dipoles placed in front of a perfectly conducting 1,280 × 240-mm reflector and with three horizontal conducting separators employed to reduce mutual coupling between cells (one cell per dipole), along with an electrically homogeneous phantom in the form of a 70-cm high by 40-cm wide by 20-cm thick rectangular box with εr = 42 and σ = 0.97 S/m, roughly that of the trunk size of an adult man, and separated at a 15-cm distance from the panel antenna array in the broadside direction. In [77], the Kathrein 730678 panel at 900 MHz was evaluated instead and the use of a full-wave solver using parallel computing was emphasized as

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necessary for a liable health-risk evaluation. The panel is very similar to the previous one, yet only three cells are employed and each one contains two dipoles separated by λ/4, leading to a largest dimension D = 30 cm. A complex Yale human phantom model [114] with torso and head downsampled to 4 × 4 × 4 mm3 voxel size was employed both with its heterogeneous nature and filled homogeneously with a dielectric of εr = 42 and σ = 0.83 S/m. The eight-element panel of Kathrein 739662, downtilted by 6º, was analyzed in [81] in the absence of a phantom, and a commercial six-element vertically polarized dipole array with a gain of 17 dBi at −3-dB beamwidths of 65º and 8.5º in the horizontal and vertical planes, respectively, was studied in [114] coupled to the VHP model and the DAM model described previously. In [79] it was clear that whole-body averaged SAR was a critical parameter for evaluating SAR at small body separation distances, thus making phantom models of the outmost importance. Likewise, large differences in absorbed power (40% to 20%) were found for different separation distances (50 cm to 5 cm) but within the reactive field region, thus making the coupling mechanism and hence antenna modeling highly important as well. Normalized to an input power of 1W in the Kathrein 730370, a maximum SARave10g of 0.005 W/kg was found for a separating distance of 15 cm. The importance of the phantom model was also outlined in [77], wherein with the same normalized input power value, at a distance of 20 cm, Kathrein 730678 achieved a maximum SARave10g of 0.597 and 0.462 W/kg for the homogeneous and heterogeneous Yale phantoms, respectively. A safety distance of approximately 2.7m was found for the Kathrein 739662 with an input power of 30W [81], while 20 cm was determined as a safety distance for several GSM1800 base station antennas using dosimetric assessment equipment and a 10W CW input power at the antenna connector in [83]. The importance of human body model shape, position, and posture was outlined in [114] by the different values obtained with diverse phantoms and free-space situations. Finally, the evaluation of safety distances using both the reference levels and the basic restrictions was performed for several dipole arrays and 30W output power in [84] employing the commercial XFDTD simulator and human body model by REMCOM Inc. at 900, 1,800, and 2,170 MHz. Safety distances similar to others previously published were found, and the fact that no compliance with reference levels does not mean no compliance with basic restrictions was confirmed, but an important issue was revealed [84]: The safety distances for dipole array antennas, usually located in the near-field, calculated upon the reference levels was shorter than compliance distances calculated upon basic restrictions at 2,170 MHz; therefore, reference levels are not always conservative since this may depend on frequency and human body models. Likewise, for near-field distances both the electric and magnetic fields have to be evaluated, and magnetic fields were identified as the limitation when calculating safety distances for certain frequencies within the near-field [84]. The Urban 120 base station antenna was analyzed in [24] with both simulations and measurements. Among the interesting findings in [24] it is worth mentioning here that calculated SAR without time averaging is sensibly different for the diverse standards under analysis. The local IEEE limit over 1g valid until 2006 was found to be the dominant one, but within the ICNIRP standards the SAR averaged over 10g

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was defining the limit only for distances below 10 cm, while at greater distances the exposure limit was set by the whole body SAR, as illustrated in Figure 4.12. In fact, the minimum safety distance for the different limits in the IEEE 1999 standard was set to 0.65m, while 0.1m was determined for the ICNIRP 1998 guidelines, suggesting [24] that an inconsistency existed between the maximum local and whole-body SAR safety limit values specified in the IEEE 1999 standard and in the ICNIRP 1998 guidelines, which was earlier suggested in [85]. In [24] it was also demonstrated that safety distances calculated from free space spatial maximum power density, although not applicable at 935 MHz, were substantially larger than those derived from SAR values. This is in some contrast with [84] and with [35], wherein the restriction on whole-body averaged SAR was found to be the critical condition requiring the lowest external field value in the head and torso of the NORMAN body model when exposed to a vertically aligned electric field plane-wave exposure, except for the peak SAR averaged over 10g value foe the ICNIRP occupational exposure limit, which was the critical condition at 2,450 and 3,000 MHz when evaluating it in the head, and when the narrow part of the leg and ankle were evaluated for the grounded NORMAN adult model against the NRPB restrictions [86]. In [87], several commercial base station antennas were analyzed for German legislation, which imposes specific restrictions for occupational exposure, including labeling [88, 89]. In this publication it was possible to compare panels only differentiated in their horizontal or vertical beamwidths, and it was concluded that horizontal focusing of the main beam increases the whole-body SAR, whereas vertical focusing has almost no influence on the whole-body SAR. Table 4.2 summarizes some base station antenna scenarios and results. It has to be said, however, that some studies calculate safety distances for specific SAR limits, sometimes pinna treatment is not specified, others estimate the

Figure 4.12 Base station power values required for the corresponding local and whole body SAR values to reach the respective occupational limits of Allgon Urban 120 panel antenna against distance at 935 MHz. (Reproduced from [24] with permission from John Wiley & Sons.)

4.2 Simulation Techniques Table 4.2

[24]

[90] [79] [77] [81]

[114]

[83]

[87]

[84]

Some Base Station Exposure Scenarios and Results

107

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maximum output power for a certain distance to be below exposure limits, or just SAR is evaluated at certain distances with diverse output powers. Sometimes both occupational and general public limits compliance are evaluated for diverse output powers. All these considerations make a direct comparison of the diverse studies in Table 4.2 somewhat difficult [71]. From these results, and unlike the situation for handsets where a recent IEC standard has been approved [60], it is clear that the lack of a worldwide harmonized protocol for evaluating safety distances of base station antennas is providing large heterogeneities in the obtained results. A novel approach to avoid these inaccuracies is to use simulation techniques to directly obtain temperature increase within the human body with the bioheat equation (BHE) and FDTD so as to avoid comparison to reference levels, which, in theory, already have an overestimation character [90]. The full potential of this method, which also includes the human thermoregulatory mechanisms, is yet to be obtained, but some preliminary results are questioning the initially predicted safety factors of reference levels [91, 92]. Emulating the human thermoregulatory system, however, is a complex issue unlikely to be determined from quantitative experimentation [1]. Thermal-derived safety factors for electromagnetic maximum permissible exposure (MPE) in an adult human brain of 7.5 [114], 10 [93], 18 [94], 20 [96], 34.5 [94], and 40 [95] have been reported. MPE levels produced a thermal safety factor in an adult eye of 5 [65], while safety factors down to 3.5 [97] have been reported for commercial system realistic use eye exposure. Moreover, thermal safety factors of skin in adults for EM realistic exposure to commercial GSM devices of 0.5 [98], 4.3 [99], 6.6 [102], and 9 [103] have been reported, while realistic EM GSM exposure has shown a thermal safety factor in the brain of 30 [101, 102] and 17.4 [95]. AMPS safety factors of 12.5 [104], 2.2 [99], and 1.7 [100] have also been reported. Realistic thermal safety factors evaluated using different commercial phones have also provided large divergences [96, 105, 106]. Some human head and thermoregulatory models cope well with the excess heat stress at MPE levels [96, 107, 108]; others take at least 20 minutes [101, 104], 30 minutes [109, 110], or 45 minutes [111] to achieve steady state and allow a certain degree of temperature increase [104], and in others thermal breakdown allows temperatures to rise continuously [91, 113]. Moreover, in some studies thermal increments were not found to be directly proportional to local SAR [96], while others found a correlation which was linearly proportional to peak spatial-averaged SAR [94, 114]. A weak correlation between peak SAR and temperature rise, which does not have a clear normalization reference, is generally observed when thermoregulation is modeled. Good correlation values of antenna output power and temperature rise are only observed for low exposure values [115], for which thermoregulatory activity may not be active. Consequently, the validity of the simulated approach to obtain exposure field values to be compared to reference levels in the guidelines is always a subject of concern since the near- and far-field situations depend upon specific antenna arrays employed in the base stations, for which there exist a wide range of commercial elements, and on both human body and source modeling, which is of extreme importance. Alternatively, the specific thermoregulatory model plays an important role in defining existing thermal safety factors. Moreover, tissue-specific required data, uncertainty, variability and artifact analyses, ambient fields and temperature load have prompted as important requisites for proper exposure evaluation, making

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109

measurements still essential to achieve consistent interpretation of results. Three other important factors for final exposure values calculated in the near-field are the averaging and meshing techniques and the inaccuracies in the determination of the dielectric tissues or their variability with age, temperature, or moisture content. The last effect has been commented on in Chapter 2. The other two will be treated next. 4.2.1

Averaging Strategies

Another important aspect to be considered when evaluating SAR is the averaging procedure. The standards from the United States and the European Union define an average operation both in time and space. When the feeding signal is a uniform sinusoidal current signal, it provides the same SAR values for any period of time under consideration. This can be taken as a worst case scenario, but results have to be considered accordingly. The spatial average SAR values are defined over volumes of tissue of 1g and 10g of mass of contiguous (or cube) tissue cells [56, 116]. Some studies have found that large differences can occur depending upon the averaging procedure, especially at 1,800 MHz [117, 118]. According to [119], averaging cubes have to be expanded until the required averaging mass is reached within 10%. The required cube should always be larger than individual cells so as to allow the overlapping averaging to be performed in all organs. The peak SAR at each cell in the cube is summed up and then divided by the number of cells within the cube. The process is completed by displacing the cube cell by cell to conform to [119] and [20]. The translation of the 10g cubic contiguous cells all over the computational domain was the averaging method suggested in [21] as a way of obtaining the first set of local maxima. A refinement to provide final maximum peak SAR averaged was also suggested in [21] by 3D rotation of the cube at detected local maxima locations and a few of their contiguous neighboring points. More elaborated averaging methods include noncubic volume shapes [56] and contiguous volume techniques [120], which are more important for more realistic head models with mouth and nasal cavities wherein the ratio of air inclusion acquires great importance [55]. Instead, a complicated averaging method is employed in SEMCAD [121]. The cubical volume centered at each location for SEMCAD averaging is expanded in all directions until the desired value for the mass is reached, with no surface boundaries of the averaging volume extending beyond the outermost surface of the considered region of the model. In addition, the cubical volume should not consist of more than 10% of air. If these conditions are not reached then the center of the averaging volume is moved to the next location. Otherwise, the exact size of the final sampling cube is found using an inverse polynomial approximation algorithm, leading to very accurate results. Average SAR values are assigned to the centered location in each valid averaging volume. All locations included in an averaging volume are marked to indicate that they have been used at least once. If a location has been marked as used but has never been in the center of a cube, the highest averaged SAR value of all other cubical volumes which have used this location for averaging is assigned to this location. Only those locations that are not part of any valid averaging volume are marked as “unused.” For the case of an unused location a new averaging volume is then constructed with the unused location centered at one surface of the cube and expanding the other five surfaces of the cube evenly in all directions until the

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Near-Field Numerical Electromagnetic Dosimetry

required mass is enclosed within this volume, regardless of the amount of included air. Of the six possible cubes with a surface centered on the unused location, the smallest cube which contains the required mass is used. No metal cells are included in SEMCAD averaging processes. These and other reported averaging differences were the stimulation for the development of annexes in the IEEE standard in 2003 and 2004 [61, 122], wherein it was specified that the E-field has to be calculated in the center of a cube as the average over the E-field along the 12 cube edges. 4.2.2

Meshing Strategies

According to [69], for proper exposure studies SAR must be calculated in all tissue regions exposed to electromagnetic radiation by antennas. A cell size of 1 cm or less ( λε/10) is required to have a good accuracy for calculating the electric field within human tissues in a phantom at 900 MHz [9, 21]. In order to study the effect of meshing on accuracy, a deep study was performed with a canonical sphere model (EPI) and SEMCAD in [8]. Several simulations with four different solo tissues and homogeneous cell sizes of 1.5, 2.5, and 5 mm were performed. Two-thirds muscle tissue provided the highest exposure values and behaved best for different meshing strategies, with the lowest deviation ratios, very closely followed by volume weighted tissue with a 1.5-mm cell size, as illustrated by Figures 4.13 and 4.14. Figure 4.13 depicts the different absolute exposure results for scenario b, showing that 5-mm 2/3 muscle provides the highest values for all 5-mm meshing situations and for some of the 1.5-mm ones, closely followed by the volume weighted tissue with a 1.5-mm cell size, thus representing a conservative approach. A deeper study of Figure 4.13 for the effect of a 5-mm meshing strategy with EPI and SEMCAD compared with a more detailed 1.5-mm cell size mesh is illustrated in Figure 4.14. In this figure, the deviation represents the difference in percentage between simulated values for each

25.00

SAR (mW/g)

20.00

15.00 Muscle 1.5 mm

10.00

5.00

2/3 Muscle 1.5 mm HSL 1.5 mm Volume weighted 1.5 mm Muscle 5 mm

2/3 Muscle 5 mm HSL 5 mm

Volume weighted 5 mm

0.00 SARpeak

SAR1g

SAR10g

Figure 4.13 Simulated exposure values with different tissues and meshing strategies for scenario b in [8]. (Reproduced from [8] with permission from John Wiley & Sons.)

4.2 Simulation Techniques

111

0

–5

Deviation (%)

–10 Muscle 2/3 Muscle

–15

HSL Volume weighted

–20

–25

–30 SARpeak

SAR1g

SAR10g

Figure 4.14 Effect of homogeneous tissue type and meshing strategies for scenario b in [8]. (Reproduced from [8] with permission from John Wiley & Sons.)

tissue and that of the maximum SAR value for a cell size of 1.5 mm with the same tissue, all extracted from Figure 4.13. It is clear from Figures 4.13 and 4.14 that higher SAR values are obtained for all tissues when meshing accuracy is increased. Similarly, decreasing cell size allows for a better modeling of the source and thus higher power factors, providing higher both absorbed power and absorbed to radiated power ratios. Smaller high resolution cell sizes (1 mm) would be required if functional subregions, like the brain thalamus, have to be evaluated [69], whether SAR within small animals is to be calculated [123] or should localized effects be under investigation. A smaller mesh size will generally increase peak SAR observed [14]. This effect was also observed in [8].

References [1]

[2]

[3]

[4]

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[121] SEMCAD Reference Manual, bundled with SEMCAD, available at: http://www.semcad. com/downloads_free/SEMCAD_RefManual.pdf. [122] IEEE Standard 1528-2003, “IEEE Recommended Practice for Determining the Peak Spatial-Average Specific Absorption Rate (SAR) in the Human Head from Wireless Communications Devices: Measurement Techniques,” 19 December 2003. [123] Leveque, P., Dale, C., Veyret, B., and Wiart, J., “Dosimetric analysis of a 900-MHz rat head exposure system,” IEEE Transactions on Microwave Theory and Techniques, Vol. 52, No. 8, part 2, pp. 2076–2083, 2004.

CHAPTER 5

In Situ Measured Exposure Assessment and Compliance Testing Antonio M. Martínez-González and José Fayos-Fernández

5.1

Introduction As the nature of the fields and characteristics of particular sources differ considerably, it is not possible to apply a unified exposure assessment method across the spectrum, and both measurement procedures and prediction tools are fundamental for evaluating compliance testing or exposure values [1]. It is for this reason that, although a superposition level (SL) is proposed in [2] for non-GSM signals, published procedures are solely dedicated to the assessment for the verification of compliance of GSM900, GSM1800, and Universal Mobile Telecommunication System (UMTS) mobile communication base stations to diverse worldwide guidelines since these are the systems wherein concerns concentrate. The development of some measurement methods specially designed for AM or FM stations radiating at lower frequencies to those of mobile communication systems is under development at CENELEC and other standardization bodies. To ensure that the public or workers are not exposed to radiofrequency radiation higher than the reference field levels proposed by the guidelines, the concept of an exclusion zone (EZ) around the base station (BS) is used [3, 4]. Since the behavior in the near-field is much more complex than on the far-field, it would be easy to include the near-field volume in the exclusion zone. While simple formulas can be derived for prediction of far-field values under free space propagation conditions, the near-field is relatively difficult to predict since there is no direct relationship between electric and magnetic fields in this area. The diverse guidelines, when referring to near-field scenarios, establish SAR-based exposure limits. In the near-field, three orthogonal components of both electric and magnetic fields exist with arbitrary relative phases and amplitudes. For digital mobile communications systems, the E-field is elliptically polarized in an arbitrary plane and the H-field is, in general, also elliptically polarized in another plane. The boundary between near- and far-field zones is associated with the transmitting wavelength ( ) and the largest dimension of the antenna (D), and it is depicted in Figure 5.1. The reactive near-field region is characterized by its reactive character and thus the concept of power density does not have a physical meaning, and both electric

121

122

In Situ Measured Exposure Assessment and Compliance Testing Distance (m) Fraunhofer region

Reactive field

Fresnel region

Transition Radiating near field

Radiating far field

Distance < 0.053m at GSM900 Use SAR values to determine exposure Distance ∈ [0.53, 3.75]m at GSM900 Measure electric E and magnetic M fields separately (using power density S approximation could overestimate) Distance > 3.17m at GSM900 Approximate point source; use power density S for exposure characterization

Distance (m) Radiating source GSM900 Base Station Frequency 900 MHz Dimension of antenna 2.3m

Far field

Near field Far field Far field Figure 5.1

Far field

Field regions for exposure assessment.

and magnetic fields have to be evaluated. The radiating near-field region may not exist if D is much smaller than the wavelength, as in the case of miniaturized antennas [5]. In practice, setting the far-field as the borderline of the exclusion zone would lead to an exclusion zone radius of typically 54m at 900 MHz for an antenna with D = 3m, and 27m at 1,800 MHz for an antenna with D = 1.5m, which makes the installation of new facilities very difficult in densely populated areas. Yet, simple far-field formulas are usually employed to determine the parallelepiped exclusion zone, which is in fact larger than the refine far-field of a typical BS sector antenna [6]. Consequently, these theoretical calculations to define the exclusion zone will suffice to determine compliance of a base station only in those situations where there are no scattering objects within the exclusion zone and where the restriction of access to the general public is inherently viable. In this sense, for BS located in a free-space area like rural zones where obstacles are not present and where the field level is maximum at distances of about a few hundreds of meters aligned with each sector panel, the predictions of the simple formulas may be sufficient [7–10]. The calculated far-field distances for GSM900 and GSM1800 are just an approximation, and assume a total down tilt of 5º to 10º and a vertical bandwidth of 5º to 10º. An example is observed in Figure 5.2. While simulations are limited in size and approximations are taken to alleviate the electromagnetic problem, there are some situations, however, where for proper assessment theoretical calculation will not suffice, and additional measurements both inside and outside the exclusion zone (EZ) are required in order to determine the compliance boundary (CB). In fact, it has been demonstrated that the size of the

5.1 Introduction

123

2 S = 2.56 ×10,000 = 0.03 mW/cm 2 π54

Direction of maximum radiation 54m 50m 20m

EIRP = 10 kW

Figure 5.2

Typical rural BS scenario (fences omitted).

exclusion zone is highly dependent on the surrounding scenario, including the geometrical characteristics of the near-field environment and obstacles and both the radiating near-field and far-field buildings, which can make the EZ increase three times that of the case neglecting the existence of surroundings buildings when using concrete wall or 1.56 times when using perfectly reflecting (metal) walls [11], as depicted in Figure 5.3. A compliance boundary defines a volume outside which any point of investigation is deemed to be compliant. In any case the points of investigation outside the compliance boundary shall be in compliance with the limits. Thus, the compliance boundary defines the volume outside which the exposure levels do not exceed the basic restrictions irrespective of the time of exposure for the specific operating conditions of the transmitting facility. The compliance boundary is determined via a procedure where sufficient points of investigation are assessed. The shape of the

m

16 14

E limit = 20 V/m, 4 carriers d3 d2 d1

12 10 8 6 4 2 0

normbuild

metbuild

Rural, mast, free-space

Figure 5.3 Size of the keep off volume around the antenna for different environments. d1: Roof of building, d2: mast, d3: free space. (Reproduced from [11] with permission from IEEE.)

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In Situ Measured Exposure Assessment and Compliance Testing

compliance boundary shall be accurately described in the assessment report. The compliance boundary may have a simple parallelepiped, sphere or cylinder (as in the Italian regulation), or a more complex shape. Moreover, since the field levels within the near-field are not necessarily above the reference levels, more refined prediction models have been proposed [4, 6, 8], and measurements become of the outmost importance. With narrowband measurements, the CB may be made smaller than the EZ. In order to properly account for all factors, code-domain analyzers [12], 24 hr/week statistical measurements [13], or full-volume full-wave electromagnetic simulation tools have been suggested. The cumbersome option of weekly statistical analyses may be useful for extrapolation techniques based on TDMA technologies, although their usefulness for UMTS WCDMA systems is yet to be demonstrated. Although electromagnetic safety standards require field measurements, limited field values are specified regardless of the wireless technology, and no details are usually provided so as to perform repetitive and accurate measurements. A relatively recent proposed method to accurately calculate compliance testing for base station antennas is to compute it from the standard spherical near-field measurements typically used to calculate far-field patterns by antenna designers and manufacturers [14]. Unfortunately, the method has proven excellent for solo antenna arrays without any object in their near-field (no sources are required in the measurement points, and due to Huygens’ Principle any object in the near-field could be a potential source), which do not cover all possible installation scenarios. Another possibility is to measure panel antennas in the near-field with the automated dosimetry scanners which will be describe in Chapter 6. While in [15], three different user positions were studied, always at far-field distances, yielding maximum SAR values of 12.9, 8.2, and 2.45 mW/kg, averaged over 1g, 10g, and the whole-body, respectively, which is well below guideline levels, a safety distance of 20 cm was determined for several GSM1800 base station antennas using dosimetric assessment equipment and a 10W CW input power in [16]. Measurements were taken with a dummy located directly in front of the transmitting antenna, but a standard for evaluation of panel antenna SAR for compliance testing is yet to be addressed in most standardization bodies. In this chapter we will refer to frequency domain measurements only, although some attempts have been performed to use time domain measurements for characterizing electromagnetic emissions [17]; its Achilles’ heel remains the open-air test environment due to required dynamic ranges (in excess of 100 dB) and response time problems, making time-domain measurements somehow promising but still unusable for electromagnetic evaluation of exposure or compliance testing.

5.2

Preevaluation Before properly evaluating exposure values, it is important to evaluate potential hazards other than RF exposure, such as high voltage sources, X-ray hazards from high-power tubes, dc magnetic fields, indirect hazards, electroexplosive devices, thermal burns or flammable materials to electromagnetic fields, or others. An assessment of the impact of potential interference problems should always be made before beginning any exposure evaluation. Measurements must be planned so as to

5.2 Preevaluation

125

limit exposure of all personnel to levels below those specified in the guidelines. If survey personnel are exposed to field strengths in excess of those specified in the guidelines for continuous exposure, they should be accompanied by someone who can ensure that the exposure duration does not exceed the time recommended in the relevant exposure guides or standards for exposure to higher level fields. In such situations, it may be desirable to conduct the measurements with radiation-emitting equipment operating at a reduced power level and use power scaling to compute the corresponding field levels that would exist during full-power operation. Alternatively, radiation protecting clothing or an alarm equipment for radiation excess over a specific value can be used by the surveyor. A flow chart diagram for the complete measurement procedure is desired, like the one depicted in Figure 5.4 for compliance testing. A preliminary study has to collect all possible data of the typical characteristics of the transmitting facility, its radiating sources, and their propagation performance. This knowledge will be useful for a good estimation of the expected electromagnetic fields levels and it will indicate the most appropriate selection of test instruments and procedures [7, 18]. Should these data not be supplied, then the survey personnel have to undertake estimation actions. The aim of any preevaluation stage of a measurement procedure is to determine the exclusion zone, the appropriate assessment technique through a theoretical calculation and the specific instruments to be employed in the evaluation.

Selection of a calibration antenna

Selection of the electromagnetic measurement probe

Simulation of the free-space field

Simulation of the voltage at the terminals of the probe produced by the electromagnetic field of the calibration antenna

Calibration procedure simulation

Determination of the antenna factor of the probe

Measurement configuration simulation

Selection of the source under test

Simulation of the voltage at the terminals of the measurement probe produced by the electromagnetic field of the source under test

Simulation of the free-space field

Determination of the “measured” electromagnetic field using the antenna factor of the probe

Comparison of the free-space field and the “increased” field

Figure 5.4

Example of a flow chart for a compliance testing procedure.

126

5.3

In Situ Measured Exposure Assessment and Compliance Testing

Instrumentation for Measurement The instrumentation and measuring techniques for far-field exposure is much different to that engineered in near-field ranges, and it is usually employed for compliance testing. Regarding uncertainty, the instrument should be provided with specifications for overall field strength measurement uncertainty (frequency response + isotropicity + linearity + temperature + calibration + uncertainty due to other environmental influences) in percentage of actually indicated measurement value. These specifications must be traceable to national/international standards, and the overall measurement uncertainty shall be calculated using the following formula: Δ meas = 2

(

1 2 Δ freq + Δ2isotr + Δ2lin + Δ2temp + Δ2cal + Δ2envirn 3

)

(5.1)

This overall uncertainty is expressed as an interval with a level of confidence of 95% [19, 20]. The individual uncertainties are given linearly and the specifications of the instrument shall include the sensitivity of the instrument to frequencies beyond the intended useful range (out-of-band response, response to powerline related frequencies). A meter sensitive to out-of-band or powerline signals should not be used in an environment where such fields may be present. 5.3.1

Broadband Probes

The electromagnetic exposure assessment of a wireless transmitting station through measured field values can be performed with the use of broadband probes, which are considered to overestimate real exposure values and provide an upper limit. Broadband instruments for field strength or power density measurements consist of two main parts: the probe and instrumentation. Field sensing elements are included in the probe. The probes may be fixed as shown or be attached to the meter using flying leads. Leads really act as transmission lines, and care must be taken when in use for an accurate evaluation of field values. Physically three orthogonal small dipoles are used in electric field sensors and physically small loops in magnetic field sensors. The detection of RF voltage usually takes place in the probe and the detected dc-voltage is processed and displayed in the instrument. Directional probes contain only one dipole, whereas isotropic probes contain three orthogonal dipoles. Since with broadband probes not only the base station signals are measured, if a single dipole is used, three measurements should be performed in three orthogonal directions to obtain the different components of the field. The total E-field would be given by the following formula: E=

(E

2 x

+ E y2 + E z2

)

(5.2)

Moreover, these probes usually measure the resultant field strength as the root square sum (rss) value, which is obtained as a square summation of three individual field strength values measured in three orthogonal directions x, y, and z without 2 considering the individual phases, giving a reading proportional to ⎪E⎪ . Conse-

5.3 Instrumentation for Measurement

127

quently, broadband probes are only valid for compliance testing within the exclusion zone but at least λ/2 away from the radiating aperture since E=

E x2 + E y2 + E z2 ≥ E z

2

(5.3)

Three axis probes should be used unless there is good reason to use single-axis meters (e.g., the determination of the polarization and/or the maximum value of the field or the determination of the resultant field of slowly changing fields). Some isotropic meters provide single-axis readout in addition to the nominal resultant field strength capability. The display of the meters is usually given in W/m2, although some more appropriate units give the results in V2/m2, because the power density is calculated from field values using far-field formulas, and that is not valid for measurements which are not made in the far-field. This measurement is not trivial given the sensitivity of most probes to their orientation respect to incident E-field. It can then be concluded that a two- or three-axis E-field sensor in the probe is more suitable for the measurements of ⎪E⎪2 with isotropic probes. When the instrument is switched on, it shall indicate the parameter according to the probe type (V/m for electric field probes, A/m for magnetic field probes). The other parameters are usually derived under far-field conditions from the field quantity being measured and of limited value under near-field or reactive field applications. Recommended further functions are [21] as follows: •

•

•

•

•

A maximum-hold function which indicates the maximum measured value during the measurement period; Derived field quantities which calculate the derived quantities from the measured quantity under far-field assumption; Alarm function that is proportional to the measured field strength and/or an audible indication that a preset level has been exceeded; A function which allows averaging over multiple spatial measurement points. This is important to assess RF fields that vary substantially with location and is required under some exposure standards; A function which allows averaging over defined periods of time. At least a 6-minute averaging time is recommended.

To avoid field disturbances by connecting leads and to allow reproducible measurements, the probe should preferably be connected directly on the instruments. Where leads are used, care should be taken of additional measurement inaccuracies and calibration validity. These leads have to be nonperturbing, and hence the lead has to be orientated so as to be parallel to propagation direction. For exact measurements, the user should be an appropriate distance to the measurement equipment (i.e., the probe should be placed on a tripod and connected to the instrument by a fiber-optic link). The probes may be fixed as shown or be attached to the meter using flying leads. The exact position for the maximal values has to be carefully tested with the broadband probe. If the device takes into account the variation of the limit according to the frequency and integrates the percentage of power density relative to the limit at the given frequency, the result is a percentage of the limit of exposure. Alternatively, if the device integrates the power density and the result is a

128

In Situ Measured Exposure Assessment and Compliance Testing

power density, then the worst case situation should be tested; that is to say that this result should be compared to the minimum of the limits over the frequency range considered. The engineer has to bear in mind that the broadband probe has the drawback of being a nonselective frequency measurement instrument. There is no possibility of knowing the frequency or frequencies responsible of the absolute value registered. Measurement of a broadband probe is a superposition of all electrical fields that are present in the point of measurement ranged in the bandwidth of the probe. Moreover, it does not provide values for the worst case scenario (i.e., full activity of the BS), and an adequate postprocessing of measurements is required for correct compliance testing. Likewise, sensitivity is worse for broadband probes than for narrowband equipment, but their low size and weight make them ideal for a quick and portable evaluation. Moreover, the point where the broadband equipment detects maximum radiation is not necessarily the point at which the station under test produces maximum signal levels since, due to the isotropic nature of the probe, we might be picking up strong signals from other stations. It is important to mention, however, that inherent errors will be present when measuring multiple-sources, multiple-frequency scenarios with electric field meters [22]. Despite the abovementioned precautions, when a measurement is performed, the measurement probe will disturb the field that has to be determined, and instead of measuring true field, the disturbed field will be measured. In principle, the calibration should take into account the disturbance of the probe [23], but this is only true if the disturbance being calibrated is the same than that observed in the measurement setup, which in practice is not always possible. In addition, there is a trade-off between disturbance of the probe and its sensitivity: the smaller the disturbance, the smaller the sensitivity. Moreover, the size of the probe provides an averaging effect on measured value. A detailed study from 600 to 2,000 MHz of these effects on dipoles was performed in [23], and it was concluded that the relative deviation of fields measured by the probe with respect to the true field was below 1% for far-field distances and high sensitivity probes, but the relative disturbance increases fast with decreasing distance when entering the near-field zone, making the use of different probes for different distances necessary, with smaller probes required in the near-field providing higher AFs than probes in the far-field but low enough to measure the higher values in the near-field. The relative deviation found for different dipoles are reproduced in Figure 5.5. Two other important effects were also observed in [23]. First, the probe termination effect was more important with decreasing antenna-body distances and when the dimension of the probe is larger, but it can be kept below 5% for small probes. Secondly, it was demonstrated that large loop antennas not only measure the magnetic field, but also the electric field, and this behavior is worse with increasing operational frequency. Therefore, using smaller loop probes, split-shield loop probes, or simply measuring the dominant component in the case of linear polarization has to be considered for these probes. 5.3.2

Narrowband Equipment

In the broadband measurement procedure, data is surveyed and acquired to monitor the exact absolute values for the electrical field and registered for a 6-minute sliding

5.3 Instrumentation for Measurement 12

129

Relative deviation at 1800 MHz: average Relative deviation at 1800 MHz: point Relative deviation at 900 MHz: average Relative deviation at 900 MHz: point

10

8 Far-field distance of 15 cm dipole at 900 MHz

ℑ [%] 6

Far-field distance of 15 cm dipole at 1800 MHz 4

2

0

0

10

20

30

40

50

60

70

Distance from source [cm] Figure 5.5 Relative disturbance of the 7.5-cm measurement dipole as a function of distance in [23]. (Reproduced from [23] with permission from IEEE.)

window averaging period with an isotropic broadband probe. It is useful to ascertain from local groups if there are any particular locations around the survey site that give cause for concern, so that narrowband analyses are performed. The narrowband measurement is made by means of either a spectrum analyzer (SA) or a tuned receiver with a broadband antenna. To adapt signals before the SA and avoid SA damage and saturation errors, it is recommended to use preselectors, which normally include preamplifiers and/or attenuators. The narrowband measurement establishes the direction of the emission and field levels at each separately frequency and is carried out along with a postprocessor stage where an extrapolation of level fields is achieved to obtain the worst case situation. The method is also appropriate in a multiple frequency scenario, even when the sources are placed in different directions, for a dual-band BS or for a site that is shared by two or more operators. A certain amount of engineering judgment, experience, and tact will need to be applied in order to obtain the best results. Verification or a check on instrument function is intended to show that the instrument is stable, and this should be performed before and after each extended period of use in the field. This practice is particularly important when there are logistical problems in returning to the measurement location at a later time. The verification can be performed in any convenient manner and should show that the scale factor of the instrument has not changed appreciably since its last calibration. 5.3.3

Antennas

The selective measurement device’s immunity to electromagnetic fields [24] must be known and exceed the maximum measured field strength. Where this condition is not fulfilled, it must be checked on the individual frequencies of the measurements

130

In Situ Measured Exposure Assessment and Compliance Testing

without an antenna and with the antenna cable terminated by the nominal impedance is at least 20 dB below the respective measured value. Antennas that can be used are monopoles, half-wave dipoles, broadband dipoles, biconic, log-periodical, and bilog-periodical, or similar. It should be taken into account that these antennas can be large compared to the wavelength and hence are not suitable for differentiating very close spatial distribution of fields. Thus, it is recommended to use a wavelength-small antenna. The antenna factor (AF) is the parameter that is used in the calculations of field strength during radiated emissions measurements. The AF, which is determined by calibration, relates the voltage output of a measurement antenna to the value of the incident field producing the voltage,

(

E( dBμV m) = V ( dBμV ) + AF dBm −1

)

(5.4)

For base station assessment, it is important to calibrate the antenna with the free-space method, so as to get a free-space antenna factor that provides an acceptable average [25] of all different antenna factors due to different polarizations, nonplane illumination nature of waves, separation distances, and so on, as is recommended by ANSI, CISPR, IEC, and other international standards. If more precise measurements are desired, specific calibrations can be performed as suggested in [23] so that the calibrated disturbance of the probe is the same as that in the measuring setup. Since EMC testing antennas are calibrated individually at different distances, small errors may be incurred if the AF is not free-space but the three-antenna method according to ANSI C63.5. Figure 5.6 depicts the small differences that may be found for a typical bicon-log hybrid AF obtained using the ANSI C63.5 standard site method. Figure 5.7 depicts several AFs for different dipoles calibrated in [23] to illustrate the trade-off described above. From this figure it is observed that the shorter the dipoles are, the higher the AFs are, and consequently the lower the sensitivity will be. The operation of movable or scanning antennas should be done with full allowance for safety precautions. These precautions range from avoiding injury from 20 Free-space AF

18

h1=1, H-pol h1=2, H-pol

16

h1=1, V-pol h1=1.5, V-pol

AF (dB/m)

14 12

10 8 6 4 30

80

130

180

230

Frequency (MHz)

Figure 5.6

Numerically calculated bicon-log hybrid AF.

280

330

5.3 Instrumentation for Measurement

131

1.8 mm 0.9 cm 1.5 mm

1.8 mm 1, 3, 7.5, and 15 cm

Z

3.5 cm

Y

X

length = 1 cm length = 3 cm length = 7.5 cm length = 15 cm

75 70 65

AF [dB(1/m)]

60 55 50 45 40 35 30 25 600

Figure 5.7 IEEE.)

800

1000

1200 1400 1600 Frequency [MHz]

1800

2000

Probe dimensions and AFs used in [23]. (Reproduced from [23] with permission from

bodily collision with rotating or moving structures, to avoiding start-up operation of RF generators with antennas pointed in the direction of personal. Antennas should not be pointed toward metal structures, and metal objects should not be inadvertently located close to antennas. These not only create scattering and multipath situations, but are also a potential source of RF burns. However, if the normal area of transmission includes such objects, measurements should be conducted in those areas with the objects in place. The presence of secondary structures such as towers, guy wires, fences, and reflecting surfaces can enhance the fields and produce RF hot spots. Allowance for such effects should be made when undertaking an evaluation. The base station antenna is referenced by the center of the rear

132

In Situ Measured Exposure Assessment and Compliance Testing

reflector, in case of panel antennas, and by the center of the antenna in case of omnidirectional antennas. 5.3.4

Digital Mobile Communications Measuring Instrument

The information related with the physical sources such as carrier frequencies or transmitted power can be easily obtained from operators. Yet, in order to make the test procedure completely independent of the operators, a digital mobile communications measuring instrument (DMCMI) is recommended. Several commercial units are available. The functions provided by DMCMIs serve many different purposes, although our interest is concentrated on its capability to be used for verification of transmitting systems, operation and maintenance of networks, and as an aid in the cell planning/network tuning process. This system usually consists of a modified handset and a computer program, which record data frames between the mobile station (MS) and the transmitting station.

5.4

Volunteer Studies Despite meticulous evaluation of thermal effects on animals, this represents a poor approximation of the real human scenario [26]. Experimental data recorded on human volunteers exposed to electromagnetic fields is scarce and in some countries specific permission has to be granted, but some examples can be found in the literature. These works on human volunteers have demonstrated that large physiological differences exist between the human body and other mammals [27], and that at or around MPE levels are easily counteracted by normal human thermophysiological mechanisms. These experiments are yet limited to skin temperature measurements, a limited number of frequencies, and modest levels of whole-body EMF exposure. The principle for this evaluation is to determine localized SAR values using temperature changes measured by implanted thermal probes or superficial infrared thermography [28–30]. The problem with this technique is that linear extrapolation from the rate of temperature change has to be performed only during the linear portion of the heating curve using SAR = ( ΔTc )t −1

(5.5)

where SAR is expressed in watts per kilogram, T is temperature (ºC), t is the time of the sampling period, and c is the specific heat for the tissue of interest. That is, under ideal nonthermodynamic circumstances without any heat loss by thermal diffusion, heat radiation, or thermoregulation (blood flow, sweating, etc.) [30]. Some studies have identified this linear portion, corresponding to the first 20s of exposure [31], but it is really a subject of current research. In [32] subjects were naked, sitting on a chair, and irradiated from the back with a vertically polarized almost uniform-wave at 450 MHz, with an incident power density of 24 mW/cm2 during 45 minutes, as illustrated in Figure 5.8. Results were measured by acquiring surface temperature at various skin locations and in the esophagus of the irradiated subjects, as well as sweating rates at the back and chest

5.4 Volunteer Studies

133

Figure 5.8 Exposure scenario in [32]. (Available at: http://www.ha.osd.mil/afeb/meeting/ 0417slides/AFEB%20Briefing%20Effects%20of%20RF%20Radiation%20on%20Humans%20Dr% 20Adair.ppt.)

surfaces. Thermoregulatory mechanisms maintained the esophagus temperature nearly constant and prevented it from exceeding 37ºC, representing a good estimate of body core temperature; an average 0.5ºC increase was observed in the high and low back positions, but with high individual variations which were attributed to the different sweating rates since high sweating increases the evaporative cooling of the back, bringing its temperature down. Chest temperatures, on the other hand, showed an average of 0.2ºC decrease, attributed to the sweating effect on the chest temperature since the chest was not being directly irradiated. Although with some intersubject variability, sweating rates increased considerably due to the exposure session. Figure 5.9 reproduces the results found in [32]. Today, advanced simulation techniques reproduce the same measured results [33], and thus extrapolation for both in vivo and in vitro studies can be performed using simulations. Yet, adverse health effects of a physical agent can only be effectively assessed in human volunteer studies, and since EMF has recently been classified as a physical agent over which risk assessment has to be performed to protect workers within the EU [34], more detailed guidelines and procedures are expected in the future. When using exposure setups with volunteers, in vivo or in vitro studies, some guidelines are readily available to avoid making insufficiently designed experiments which may lead to contradictory results [35–37]. In [38] and [35], guidance for exposure design of human volunteer studies concerning mobile phones and effects on the brain and auditory organs is provided to minimize exposure intersubject variability and to achieve consistent interpretation of results. It is obvious, however, that invasive SAR measurements cannot be performed in volunteers, and detailed compliance testing and exposure evaluation methods without volunteers are required. Some parameters for MRI imaging that have to be considered for patient safety are already available [39, 40].

134

In Situ Measured Exposure Assessment and Compliance Testing

Figure 5.9 Temperatures and sweating rates recorded in the chest and in the high back of an 2 exposed subject at 450 and 2,450 MHz with P inc = 24 mW/cm in [32]. (Available at: http://www. ha.osd.mil/afeb/meeting/0417slides/AFEB%20Briefing%20Effects%20of%20RF%20Radiation%20 on%20Humans%20Dr%20Adair.ppt.)

5.5

Accurate Far-Field Compliance Testing for 2G Measurements 5.5.1

Measurement Campaigns

Power classes of various GSM-type digital cellular base stations can be observed from Table 5.1. Due to the increasing concerns, there is a vast number of measurement campaigns developed all over the world. Previous measurements of heterogeneous man models in the far-field at 915 MHz showed that E-polarized wave exposure provided maximum SAR values consistently in the human neck, closely followed by the torso and the eye [41]. In Spain, the Technical University of Catalonia [42] measured 24 BS, and power density levels measured at 10m distance from the BS were found to be 850 times below the EURC levels. Yet, no details where provided for its measuring protocol, and hence no reliable conclusion can be taken from these measurements. In Portugal, a GSM indoor measurement campaign was performed with Test Mobile Station (TEMS) equipment [43], and maximum measured instanta-

5.5 Accurate Far-Field Compliance Testing for 2G Measurements Table 5.1

135

Power Classes of Various GSM-Type Digital Cellular Base Stations

GSM 900

DSC 1800

Cell Type

Power Class

Power (W)

Cell Type

Power Cell

Power (W)

Macro

1

320–640

Macro

1

20–40

2

160–320

2

10–20

3

80–160

3

5–10

4

40–80

4

2.5–5.0

5

20–40

6

10–20

7

5–10

8

2.5–5.0

M1

0.08–2.50

M1

0.5–1.6

M2

0.025–0.080

M2

0.16–0.50

M3

0.008–0.025

M3

0.05–0.16

P1

0.02–0.10

P1

0.04–0.20

Micro

Pico

Micro

Pico

neous power density values were found to be 35 dB below the EUCR levels. No BS activity factor was considered. In France, France Télécom Mobiles and Bouygues Télécom performed several measurements and simulations for l’Agence Nationale des Fréquences (ANFR) and the group of experts that had to write a report for the French Ministry of Health [44]. In this report, the importance of the absence of a harmonized protocol for assessment at either the national or international level was outlined, and although some figures were provided, it was clearly stated that these could not be used for comparison or to draw conclusions until such a protocol is obtained. In fact, results were found to be highly different depending upon the selected measuring method (isotropic probe, frequency selective equipment, etc.). Nine popular Paris locations were selected by France Télécom, while three locations within 100 elementary schools in Paris with a nearby BS were selected by Bouygues Télécom. A maximum of a 14% of the EUCR limit was found and safety distances were calculated. Yet, only TV, FM radio, GSM900, and GSM1800 signals were considered, and the activity factor is not mentioned since only instant root mean square (rms) levels were accounted for. Results are reproduced in Figure 5.10. Likewise, the results of 118 measurements performed in the United Kingdom by the National Radiological Protection Board (NRPB) have also been published [45]. The authors sustained that isotropic probes were not sensitive enough and that selective measurements with the use of a spectrum analyzer with a sensitivity of 1 µW/m² and a good selectivity with a measuring uncertainty of about 3 dB had to be employed. A frequency range of 30 MHz to 2.9 GHz was used, and both indoor and outdoor measurements were performed. Results were dispersing, and at very close distances from the antennas, the maximum EURC levels could be encountered. Yet, averaged street power density levels were found to be between 5.5–6 and 18–6 times the maximum permissible ICNIRP reference levels. In this survey, no activity factor was considered. In Poland, the Institute for Working Medicine evaluated several BS [46], and measured power density levels were found to be higher than those specified in the

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Figure 5.10 Exposure levels measured in France. (Reproduced from [44] with permission from Bouygues Télécom, France.)

Polish standard but lower than those in the EURC (Polish levels are 40 to 90 times lower than EURC levels). The survey redirected the reader to a Polish Protocol. In Austria, a set of measurements was presented to Congress [47]. A total of 102 rural and 100 urban BS were tested with a narrowband spectrum analyzer. Eight measurement results were higher than 1 mW/m² (0,6 V/m), 40 were found between 0.1 and 1 mW/m², 43 between 0.01 and 0.1 mW/m², 61 between 0.01 and 0.001 mW/m², and 50 were below 0.001 mW/m². Maximum instant rms values were not found higher than 1% of the EURC levels. In Sweden, a summate of all three components (x, y, and z) to the total electric field strength were measured during 50 seconds with a spectrum analyzer for BS radioelectric emissions compliance assessment [48]. The analyzer was used in the peak-hold mode, and a total of 26 stations were analyzed from 30 to 2,000 MHz. A worst-case approach was used but not clearly explained in the paper so as to account for the empty slots when measuring. The total mean value for all sites was 0.5 mW/m2, and the EURC level was not exceeded in any site. The highest exposure measured at any of the 26 sites was 0.07% of the reference EURC level. Outside the European Union, field survey measurements performed at 14 stations throughout Australia [10] investigated not only the EMF emission levels from GSM BS, but also from other sources, including AMPS, VHF TV, UHF TV, AM radio, FM radio, and paging. The results clearly demonstrated that the RF radioelectric emissions from GSM BS were several orders of magnitude below the maximum permitted limit in Australia at the time [49, 50]. In the Australian survey a protocol was set up in order to account for all broadcast sources other than mobile communications BS, recording all signals with power densities greater than 1% of the observed maximum for each frequency band. Likewise, a field survey in and around five Vancouver schools in Canada [9] yielded similar results, in this case with levels well below Canada’s Safety Code 6 limits [51].

5.5 Accurate Far-Field Compliance Testing for 2G Measurements

137

Similar tests on diverse base stations with several testing methods have also been performed in Germany, and results were also found to be below current limits [52]. In Israel, a field survey performed by Cellcom Israel Ltd. across the country outlined the importance of both broadband and narrowband measurements [53]. Although averaged exposure of 40 surveyed BS yielded 9.6% of the ICNIRP highest general public permissible exposure level (HPL) and a standard deviation of 11.4%, with a 24-hour surveying period to account for BS activity, there was one urban station where nonshaped broadband measuring equipment yielded an exposure of 272% that of ICNIRP HPL and narrowband measurements were required. Narrowband measurements demonstrated that 99% of the radio electric emissions were due to an HF source located in a neighboring building, exceeding ICNIRP HPL at HF by 600%. In Italy, the regional agency for environmental protection of Tuscany (ARPAT) monitored base stations of TACS, GSM900, and GSM1800 systems for 3 days each using a Wandel & Golterman EMR 300 radiation monitor equipped with a triaxial electric field probe type 8.2 (100 to 3 kHz) connected to a personal computer [13]. The obtained charts demonstrated the usual human activity for each day, characterized by the lowest values during the night and by two maxima during the day, the first in the 10 a.m. to 1 p.m. time band and the second one in the 6 p.m. to 10 p.m. time band, as illustrated in Figure 5.11. Two different base stations were also identified, those wherein maximum hourly average E-field values were found in the morning, named “business,” and those wherein maximum hourly average E-field values were found in the evening, named “residential.” Week studies also showed that weekends had less traffic than week days. In fact, there have been many EMF monitoring activities in Italy, including one at the national level through ARPAT and others at regional levels (Catania, Pescara, Emilia-Romagna, Tuscany, etc.) [54]. In Spain, the Technical University of Carthagene performed a measurement campaign in the Region of Murcia on 45 municipalities and 55 base stations of 37 different sites [55, 56]. The results of this study provided that 8% of all base stations (about 12% of all sites) must limit people access to the intimate contact of the antennas, but with these restrictions all sites were found to conform to the Spanish regulation, identified to the ICNIRP guidelines assumed by the EU, as it is depicted in Figure 5.12. These and other measurements campaigns worldwide have demonstrated that the street level of radio electric emissions in urban scenarios are well below the guideline safety levels, but that if access to a very close proximity to the antennas is permitted, there may be compliance boundary issues, because maximum levels are surpassed. It is then required for national regulations to allow for access restrictions to the diverse installations, ensuring compliance to guideline levels. The Spanish and Italian regulations, among others, use this restriction. 5.5.2

Measurement Procedures

Unfortunately, although standards provide a limit for electromagnetic exposure values across the spectrum and also some procedures and techniques for evaluation of compliance testing, there are just a few published procedures with detailed information so as to properly evaluate exposure assessment for specific digital mobile

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In Situ Measured Exposure Assessment and Compliance Testing 2.2

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communications systems [2, 11, 57–60]. Most measuring campaigns do not use these procedures, thus making it impossible to conduct a comparable study. Due to the need for obtaining comparable results, the COST244bis Action “Biomedical

5.5 Accurate Far-Field Compliance Testing for 2G Measurements

Figure 5.12

139

Total exposure quotients of base stations in the Region of Murcia (Spain).

Effects of Electromagnetic Fields” management committee decided to perform a short term mission, “Mobile telecommunication base stations – exposure to electromagnetic fields” to compile data from some European nations on the exposure levels from base stations and, if possible, to draw conclusions with regard to comparability of the data from different sources and countries, usability of these data as a source for information of the public, the establishment of a future common database, and the identification of gaps of knowledge concerning the data and the procedure by which they are obtained. The short term mission (STM), solely dedicated to NMT450, GSM900, and GSM1800 systems, was initiated at the COST244bis meeting in Zurich, Switzerland in February 1999, with Austria, Belgium, France, Germany, Hungary, and Sweden as participating countries. Unfortunately, unlike the recommendations by scientific papers [2, 58, 61], far-field conditions were assumed and therefore, measured electric fields were converted to power densities while measurements were performed using wideband antennas connected to a spectrum analyzer in the peak-hold function of the analyzer; that is, only compliance testing analyses were performed. The final report of COST244bis STM is on the Web (www.cost281.org) and was presented at the September 2001 European Bioelectromagnetics Association (EBEA) meeting in Helsinki (Finland). This

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In Situ Measured Exposure Assessment and Compliance Testing

STM was continued in COST281 by another mission on “Base station monitoring” during 2002 and 2003 in order to collect experience and develop adequate protocols and methods for exposure assessment projects. While in COST244bis it was concluded that: •

• •

Exposure levels may vary by several orders of magnitudes due to BS setup and measuring factors; Exposure levels were often found lower in rural than in urban areas; Despite all variations and uncertainties, exposure levels were well below the reference levels of the ICNIRP guidelines in all these measurements, performed in areas accessible to the public.

In COST281, more efforts were devoted to develop contributions for a rigorous evaluation method. In fact, maximum GSM exposure in [62] was 47.6 mW/m2 or about 1% of the ICNIRP exposure limits for the general public, although only exposure evaluation measurements were performed and no compliance testing criteria (i.e., worst-case scenarios using extrapolation techniques) was adopted. The large variation in exposure levels for diverse BS was attributed to several factors like the input power of the antenna, the type of the antenna, the location of the examined position with respect to the antenna and several environmental factors. In view of this need, the EU Commission adopted Standardization Mandate M/305 to CEN, CENELEC, and ETSI (October 2000) for defining requirements to protect humans beings from hazardous effects which may be caused by EMF emitted by electrical apparatus. This mandate follows within the scope of the Low Voltage Directive 73/23/EEC and the Radio Equipment and Telecommunications Terminal Equipment Directive 99/5/EC. Under this mandate CENELEC TC106X is currently preparing three standards (basic, product, and in situ) for the evaluation of electromagnetic fields of wireless transmitting facilities. While these standards are being consensuated, several authors have proposed [2, 61] an in situ measuring procedure to evaluate compliance which is practical, rigorous, and repetitive. The procedure has to be practical because of the large number of potential BS that have to be measured and rigid to guarantee that any point in the coverage area of an installation is below the exposure limits fixed in the guidelines when evaluating compliance. The procedure also has to be repetitive to ensure that no variations are encountered in two different assessments to the same BS, as long as the equipment installed in the BS has not been altered. Since broadband techniques evaluate all possible sources within the probe frequency range, conformance to guideline levels by means of broadband measurements can guarantee compliance, whereas should the broadband measurement results not be conformed to guideline levels, it does not mean that the BS does not conform to them, and additional narrowband measurements are required to provide both exposure assessment and/or compliance testing. 5.5.3

Base Station Activity Determination

In GSM systems, each conversation is assigned to a 0.2-MHz channel that is shared with seven other conversations (slots) through the same transmitter. Information is transmitted with pulses, one 576-μs-long pulse every 4.6 ms—namely, with a pulse

5.5 Accurate Far-Field Compliance Testing for 2G Measurements

141

repetition frequency of 217 Hz. Communication is rapidly reconstructed after coding, in a time interval short enough to give a sense of continuity to the conversation. For most BS there is a maximum of 32 time slots for any sector, which means that all (typically four as a maximum) transmitters are operating (each transmitter can handle up to eight simultaneous phone calls). The traffic that flows through a mobile communications BS depends upon human activity, and hence radio electric emission are expected to be higher at diurnal hours than at night, but there are other human patterns that affect BS traffic and hence radiation. For example, at Spanish islands and coastlines the activity in summer time is greater than in winter due to the large number of tourists. But also the date or prices can affect to the BS activities. This important variable has not been taken into account in several campaigns presented earlier, and hence no reliable conclusion can be taken from these measurements. Hence, since mobile communications signals are transient and partially random in their occurrence and distribution, the measurements for compliance testing has to account for the BS activity so as to increase the measurement repeatability and to achieve a reference point for comparison and extrapolation. Activity factors could be accounted for by using a long-term average value for each location, which is obtained by continuously recording the number of simultaneous active time slots for a single carrier during 24 hours or even during several days. Such a surveying time is not practical and yet does not guarantee for complete assessment. Yet, obtaining a general formula valid for all BS that account for BS activity is extremely complicated, and hence we propose to determine the activity of each individual BS by using the DMCMI equipment. GSM is based on the time-division multiplex access (TDMA), allowing up to eight users to share the same frame (carrier). GSM900 uses the 935 to 960 MHz (extended) for BS-to-MS link, while GSM1800 handsets receive in the 1805 to 1880-MHz band. Carrier spacing is 200 kHz, and frequency hopping is often used in both GSM900 and GSM1800 networks. A burst is the unit of a GSM900 transmission in the radio environment. A burst is sent in a time window called a slot. A TDMA frame consists of a set of eight slots, as shown in Figure 5.13, where the slot time is 577 μs and its frequency is 217 Hz. Moreover, not all frames are used for conversation purposes, and a dedicated channel traffic/full speech (TC/FS) also contains signaling information about the transmission and idle frames for handover 577 μs

4.6 ms

TDM frame

Traffic channel Figure 5.13

Control

GSM TDMA frame and super frame.

Time slot

IDLE

SID or traffic

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In Situ Measured Exposure Assessment and Compliance Testing

processes, among others. TDMA frames are grouped together in one or two ways as multiframes. A 26-frame multiframe, with a duration of 120 ms, consist of 24 TC timeslots of 577 μs each, one slow associated control channel (SACCH) timeslot, and one idle timeslot. Four (8/2) consecutive TC timeslots form a TC block which contains 20-ms speech. Four SACCH timeslots form a SACCH block which holds a complete SACCH message; that is, system information 5 or 6 on the downlink channel (BS to MS) and measurement report on the uplink channel. A 51-frame multiframe can also be formed with a duration of 235.4 ms, exclusively for control channels. The last level of the frame structure is termed the hyper frame, consisting of 2,048 super frames, and has a duration of 3h 28m 53s 760 ms. For each SACCH multiframe, the DMCMI sends a dedicated mode report to the PC, including measurements values for serving and neighboring cells measured during the latest SACCH multiframe and system information. Other parameters that affect radio electric emission levels from GSM BS are the power control and discontinuous transmissions. The output power emitted by a GSM900 or GSM1800 handset and by the BS antenna (BSA) depends upon network parameters and mainly to the power control (PWC) and to discontinuous transmission (DTX). The distance from the BS to the active handsets, the velocity of active handsets, and the conversation rate influence the PWC and the DTX. By using PWC, both the handset and the BS transmitter can reduce or increase their transmitting power depending upon the distance between the mobile and the BS. By using DTX, the radio transmitter can be switched off during speech pauses, wherein synthetic noise similar to background is delivered to the listener, known as silence descriptor speech frame (SID). Thus, DTX means that not all TDMA frames are really transmitted. In practice, DTX can induce a handset power reduction of about 30%, while PWC may induce variations in the handset emitted power level of some 30 dB [63]. Due to the large numbers of variables involved into the characterization of the exposure to electromagnetic emissions, a statistical approach is normally used, unless a worst-case scenario can be derived. Although it may seem that exposure is rather difficult to be rigorously evaluated with all these factors, it is important to know, however, that neither DTX nor PWC can be applied on the broadcast control channel (BCCH) carrier, on which we propose to obtain the activity factor k. Consequently, the base station activity factor k has to be determined to properly assess repetitively in the test. The digital mobile communications measuring instrument (DMCMI) will provide the required information to determine k by specifying which channels of a specific sector are active and which ones are available, and by referring received RF channel powers to the received power of the BCCH carrier. The BCCH carrier broadcasts general information on an individual basis (e.g., information used for cell selection and for describing the current control channel structure). The DMCMI must provide at least the base station identity code (BSIC), the serving cell BCCH ARFCN (SC), the cell traffic channels (TC), the mobile network code (MNC), the neighbor cell BCCH ARFCN (BA list), the currently used frequencies (CA list), and the type approval code (TAC) of the international mobile station equipment identity (IMEI). Should a DMCMI not be available to the surveyor, a worst-case scenario has to be assumed only for compliance testing purposes, and for a single base station,

5.5 Accurate Far-Field Compliance Testing for 2G Measurements

k=

1 MNC

143

(5.6)

where, MNC is the maximum number of possible carriers at any sector within the base station. 5.5.4

Broadband Measurements

When the environment outside the exclusion zone surrounding a specific installation is not free of obstacles, the direction of maximum radiation has to be identified for each sector of each radiating system at the BS for compliance testing. As it has been extensively explained, several simulation tools can be employed to do that [64], but the great variety of scenarios where a BS can be located and the complexity of urban environment involved in the geometry in each case make it inappropriate, extensive, time-consuming, and quite complex [58]. Figure 5.14 depicts a prediction of the surroundings of a typical BS. A more both practical and realistic way of detecting the position and direction of maximum level spots is through the use of an isotropic broadband probe. Three axis probes should be used unless there is good reason to use single axis meters (e.g., the determination of the polarization and/or the maximum value of the field or the determination of the resultant field of slowly changing fields). Some isotropic meters provide single axis readout in addition to the nominal resultant field strength capability. This measurement is not trivial given the sensitivity of most probes to their orientation with respect to incident E-field. A two- or three-axis E-field sensor 2 in the probe is more suitable for the measurements of E with isotropic probes.

Figure 5.14

Prediction of field levels in the surroundings of a typical BS.

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In Situ Measured Exposure Assessment and Compliance Testing

These leads have to be nonperturbing, and hence the lead has to be oriented so as to be parallel to propagation direction. The exact position for the maximal values has to be carefully tested with the broadband probe. The broadband probe has the drawback of being a nonselective frequency measurement instrument. Likewise, sensitivity is smaller for broadband probes than for narrowband equipment, but their low size and weight make them ideal for a quick and portable evaluation. Moreover, the position where the broadband equipment detects maximum radiation is not necessarily the position at which the station under test produces maximum signal levels since, due to the isotropic nature of the probe, we might be picking up strong signals from other sources. 5.5.5

Data Acquisition and Evaluation of Compliance with Broadband Probes

A first record for the absolute field level in those points where field levels have been found maximum, over a 6-minute long sliding window averaging period has to be registered and compared with the safety limits. Here, it is important to mention that 2 although measured E z can suffice for compliance of the base station (as it has been explained before), since with broadband probes many other sources are accounted for, we recommend using E for compliance testing purposes, which will provide an overestimation for the base station. A broadband field probe has a typical frequency range from a few kilohertz to tens of gigahertz. If the value registered with the broadband probe is below the most restrictive limit in this frequency range—taking into account the BS activity and the uncertainty of the measurement—then additional narrowband measurements are not required to properly asses the compliance of the site. Care has to be taken in the acquisition (when making use of the previous sentence) when employing shaped broadband probes, which employ hardware filters to weight contributions according to the frequencydependent limits. The activity for a specific BS depends upon several factors, as has been explained before. An additional protection factor then has to be included for evaluating conformance to the limit to guarantee the accomplishment of the exposure level when measurements are done with an isotropic broadband probe. For a BS broadband assessment procedure, the final proposed equation to be applied to the limit to guarantee that electric field levels are below the safety guidelines limits with a flat-response broadband probe is HPL = k ⋅ MRL − U

(5.7)

where k refers to the BS activity and ranges from 0 to 1; MRL is the most restrictive limit in the frequency band of the isotropic broadband probe described in the guidelines (V/m); U is the measurement uncertainty (V/m); and HPL is the highest permissible limit to be applied for broadband measurements (V/m) Hence, for flat-response probes, if L > HPL

(5.8)

5.5 Accurate Far-Field Compliance Testing for 2G Measurements

145

where, L refers to the measured E (V/m) for the worst-case scenario after the required averaging. Then an additional narrowband assessment is required. Else, the BS can be declared conformed to guideline levels and a final report stage has to finalize the assessment. Yet, when employing isotropic shaped broadband probes, which use hardware filters to weight contributions according to the frequency-dependent limits, (4.21) is transformed to HPP = k ⋅ 100 − U

(5.9)

where, k refers to the base station activity and ranges from 0 to 1; U is the measurement uncertainty (V/m); and HPP is the highest permissible percentage to be applied for broadband measurements (V/m). Hence, for isotropic shaped-response probes, if, P > HPP

(5.10)

where P is the measured percentage for the worst-case scenario after averaging, then an additional narrowband assessment is required. Else, the base station can be declared conformed to guidelines levels and a final report stage has to finalize the assessment. A typical broadband measurement records for a BS working at 50% of its capability is depicted in Figure 5.15. Measurements were performed between 10:00 and 12:00 a.m. on a sunny Tuesday morning. The BS had no wavelength-comparable obstacle within the exclusion zone. The evolution of the electric field magnitude has been recorded over a 2-hour period and averaged over a 6-minute long sliding window period and compared to the EU recommended safety limits (EURC). The measured mean value is 10.0 V/m, while the maximum is 11.7 V/m and the minimum value registered 9.2 V/m. Total uncertainty for the measurement was U = ± 1.1 V/m. The limit to which measurements are compared to assess conformance is that of (31) with k = 0.5. Limits for different activity factors are also included in Figure 5.15 for comparison purposes. Observing Figure 5.15, where P = 10.0 V/m and HPL = 12.9 V/m, one can conclude that the BS under evaluation conforms to EURC. In the field measuring campaign we have performed in Spain, the averaged measured Ez contributed to over 70% of the total measured electric field with (5.2). If we consider that not only the base station signals are being recorded with the broadband probe, this confirms the hypothesis described previously.

30

Limit for k=0.58 Limit for k=0.5 Electric field

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In Situ Measured Exposure Assessment and Compliance Testing

5.5.6

Narrowband Measurements

Additional narrowband measurements may be required to characterize the base station or for a more detailed study in certain sensitive areas, should the testing site fail the broadband measurement testing, or simply to identify individual operators’ contribution to overall electromagnetic exposure. The narrowband measurement is made by means of either a spectrum analyzer (SA) or a tuned receiver with a broadband antenna. Since different operators have been licensed different parts of the spectrum, the only way to accurately know which of them contributes a certain exposure percentage over the total exposure is by means of a frequency selective measurement. Moreover, it is usual to find areas where total exposure is the contribution of several base stations of different operators. At points where exposure has been found maximal with the broadband probe, the percentage of contribution to the total exposure originated by each source can be determined by measuring with the frequency selective instrument. Different signal levels into the whole bandwidth at each frequency are determined. Likewise, the incident direction of signals can be detected by slightly turning the antenna to see if the signal level decreases, and by comparing measured frequencies with national assigned values to each operator. In narrowband measurements, the different carriers and power levels used in a specific cell sector must be monitored and the exact source at which it corresponds is directly identified, so as to determine the BS activity during the surveying period. In order to ensure compliance with radio regulations outside the band, a guard band of 200 KHz is required between the two edges of the bands and the first and last carriers. This gives 174 possible carriers defined for the uplink and downlink in GSM900 as follows: Fu(n ) = 8902 . + 02 . (n − 1) MHz for 1 ≤ n ≤ 124

(5.11)

Fu(n ) = 8902 . + 02 . (n − 1023) ΜHz for 975 ≤ n ≤ 1024

(5.12)

Fd (n ) = Fu(n ) + 45 MHz

Fd (n ) = Fu(n ) + 45 MHz

Because of the energy in a GSM modulated signal ring outside the nominal 200-KHz band, it is recommended that, to protect other services, carriers 1, 124, and 174 will not normally be used, except by local arrangements. This does not represents a one-to-one mapping between radio channels and carrier frequency, and the concept of frequency hopping allows for a hop between radio carriers in some defined way. For GSM1800 systems, Fa(n ) = 17102 . + 02 . (n − 512 ) MHz for 512 ≤ n ≤ 885

Fd (n ) = Fa(n ) + 95 ΜΗz

(5.13)

A postprocessor stage where an extrapolation of level fields is achieved is required to obtain the worst-case situation for compliance testing. The method is also appropriate in a multiple-frequency scenario, even when the sources are placed in different directions. When the analyses concentrate on 2G systems, compliance

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testing requires a superposition level (SL) for non-GSM/DCS signals [2]. A set of measurements has to be performed around the BS under test and at the locations where GSM electromagnetic field levels have been found maximum, and this must be averaged over a 6-minute sliding window period. Although SL is just an approximation and does not guarantee maximum measured levels on non-GSM signals, it provides for an additional value useful to determine compliance. Should measured SL level be over the maximum level determined by the guidelines, no further tests are required, and the BS has to be declared as not conformed, whatever the projected transmitting power, due to saturated environment. Otherwise, this level (SL) will be subtracted from the highest permissible limit (HPL) so as to account for at least: • • •

Low frequency signals (AM radio): 10 kHz to 30 MHz; Very high frequency signals (FM radio, VHF TV): 30 to 320 MHz; Ultra high frequency signals (UHF TV, trunking): 320 to 890 MHz.

5.5.7 Data Acquisition and Evaluation of Compliance with Narrowband Probes

An overall uncertainty for narrowband measurements must be calculated taking into account the diverse contributions of the different measuring elements to the total error, and at least: • •

Measurement uncertainty of the antenna factor; Measurement uncertainty of cable losses.

Within the exclusion zone, the maximum electric field strength has to be evaluated. It may be helpful to divide the total area where measurements have to be done in subsections and to evaluate the maximum field strengths for each subsection. The maximum field strengths have to be evaluated approximately along the main axis of the body in the area of head, chest and pelvis. If the field is nearly uniform the field strengths can be measured at a height of 1.5m above ground. Likewise, multipath reflections may create highly nonuniform field distributions, particularly at frequencies in excess of 300 MHz. To judge the level of exposure at any specific location, a series of measurements should be made over a square area whose sides are approximately 1m or 2m long. Maximum field values must also be evaluated throughout an imaginary axis corresponding to the height of the head, chest, and pelvis of a human body. The spatial average of the field within that area should be considered as the appropriate level for comparison with guidelines. Measurements near metallic objects should be made with the edge of the antenna/probe at least three “probe/antenna lengths” (e.g., 20 cm) from the object. Special care must also be taken when selecting the measurement resolution bandwidth, which must not introduce noise into the system. For example, if a wide filter is used and two equal amplitude input signal are close enough in frequency, then the two signals will appear as one. Signal resolution for an SA is determined by the intermediate frequency filters. Resolution bandwidth (RB) establishes the width of these filters. Generally, to resolve two signals of comparable amplitude the RB must be less than the frequency separation of the two signals intended to be

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In Situ Measured Exposure Assessment and Compliance Testing

E (dB/μV)

resolved. For GSM bands the carrier separation is of 200 kHz (maximum). The smaller the RB, the longer the measuring time, and wideband contribution due to modulations, for instance, may not be accounted for. In addition, for signals with nonequal levels—that is, of different orders of magnitude—the criterion for the bandwidth filter resolution is more restrictive. In this case the filter shape factor must be considered, typically with a rate 15:1 for a signal level difference of 60 dB. The engineer must then be careful with the SA setting, particularly with RB and with the relationship between RB and sweep time, which is inversely proportional to the RB square. A reduction on RB of 10 is equal to an increase of 100 over the sweep time. It is very important to mention here that we are detecting a modulated signal (GSM type) with a quasirandom behavior. Thus, its detection is highly influenced by the RB used for the measurements. This effect is really a trade-off between measured amplitude accuracy and frequency separation precision, as it is observed from Figure 5.16, where a typical BCCH is clearly depicted with RBs of 100 kHz and 3 MHz. A 3-MHz RB provides slightly higher values than those detected with a 100-kHz RB, but it is not capable of identifying a carrier close to the BCCH, which correspond to a different BS, but it can have an effect on signal detection. Hence, we recommend, whenever possible, to use a 200-kHz RB (this is now an option of several manufacturers). If this is not possible a 100-kHz RB can be used, but should employ a RB amplitude correction factor (CFRB) of 2.2 dB for compliance testing. All throughout the measuring campaign in Spain, a maximum difference of 2.2 dB was encountered for narrowband measurements performed with a 100-kHz resolution bandwidth compared to measurements with a 3-MHz resolution bandwidth. Likewise, a polarization correction factor is also required for accurate assessment. 2G base station antennas are usually colinear arrays of crossdipoles, which are linearly polarized. Yet, measured polarization cannot be assumed linear, not only because not all antennas are crossdipoles, but also due to reflection and diffraction effects. In order to illustrate this effect, Figure 5.17 depicts horizontally and vertically polarized measured GSM900 field levels for the worst-case scenario of the BS in Figure 5.19, while Figure 5.18 depicts horizontally and vertically polarized measured GSM1800 field levels for the same dual-band BS. Negligible differences are encountered in Figure 5.18 between the two polarizations for GSM1800, while up to a 30-dB difference can be observed in Figure 5.17 for the GSM900 system. Thus, both vertical and horizontal polarizations of the measured field have to be evaluated for proper assessment. This can be accounted 108 107 106 105 104 103

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Figure 5.16

The resolution bandwidth correction factor.

5.5 Accurate Far-Field Compliance Testing for 2G Measurements

149

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941.5 Frequency (MHz)

944.7

947.8

Measurements at GSM900 frequencies with different polarizations.

100 Horizontal polarization Vertical polarization

90

E (dB/μV)

80 70 60 50 40 30 20 1.834 Figure 5.18

1.838

1.842 Frequency (GHz)

1.849

1.846

Measurements at GSM1800 frequencies with different polarizations.

for as a polarization correction factor (CFPOL). Only when it can be demonstrated that measured values are the same whatever the polarization, total field values can be obtained by multiplying vertically polarized measured field values by 2 ½, by E MeasTot = 2 E MeasVPol

(5.14)

For exposure assessment, final linearly measured field values at each frequency have to be postprocessed and calculated by

( 2) + V( dBμV ) + CL( dB) + AF(dBm )

E MeasTot ( dBμV ) = 10 log

−1

(5.15)

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In Situ Measured Exposure Assessment and Compliance Testing

Figure 5.19

Dual-band GSM900/GSM1800 base station under test.

where V is the voltage measured by the SA; CL is the reduction in signal strength that is caused by losses in the interconnecting cable between the antenna and the SA; and AF is the antenna factor, calibrated in free-space. Should compliance testing be required, the superposition level, polarization, and RB correction factors have to be added to the previous equation, field values averaging in time and space need to be performed, and with the acquired data it is necessary to extrapolate the results for the worst-case scenario regarding traffic conditions. Once we know the maximum signal level, which is determined by the BCCH sector carrier, and all the frequency carriers available in the BS, extracted with independence or by means of the supplied parameters, we only have to increase the amplitude level of all carriers to those which provided the maximum field level. Then, with all carriers fixed to this maximum level the worst-case situation is simulated and the total exposure in this new case is computed for compliance testing. The calculation for the total field represents the scenario where all channels are emitting the peak-radiated power observed at any time during the surveying period. This is similar to excluding second order statistics such as level crossing rates (LCR) or averaged duration fading (ADF). The measurement of a single signal can be given a dimensionless quantity known as the exposure quotient (EQ), ⎛ Ei ⎞ = ∑ ⎜⎜ MeasTot ⎟⎟ i =1 ⎝ E guideGSM ⎠ N

EQGSMi

2

(5.16)

where N is the total number of GSM channels under evaluation; and EguideGSM is the HPL for GSM in the guidelines under evaluation. Yet, surveys are concerned with simultaneous exposure to many different radio signals spread throughout the radio spectrum from one or several BS. All signals impinging on the measurement site will contribute to the total exposure at the point

5.5 Accurate Far-Field Compliance Testing for 2G Measurements

151

of measurement, and EQs offer a convenient form of expressing the exposure due to multiple radio signals at the point of measurement. Hence, the total exposure quotient (TEQ) for the BS under test will be equal to the sum of the n quotients for all signals in the measured bands by TEQ =

⎛ E imeas ⎞ ⎜⎜ guid ⎟⎟ ∑ i =1 ⎝ E i ⎠ n

2

⎛ E meas ⎞ = ⎜⎜ 1guid ⎟⎟ ⎝ E1 ⎠

2

⎛ E meas ⎞ + K + ⎜ nguid ⎟ ⎝ En ⎠

2

=

n

∑ EQ

n

(5.17)

i =1

By taking into account all emitting sources, a TEQ less than unity indicates compliance with the guidelines. As an example, compliance testing of the GSM900/GSM1800 BS of Figure 5.19 is illustrated below. Figures 5.20 to 5.22 show the study of superposition levels for the BS of Figure 5.19. After some postprocessing, computing final results provides a SL = 2.3% (0.023). Figures 5.17 and 5.18 show levels detected by the SA without correction factors applied in the postprocessing stage. Measurements were performed on a sunny Tuesday morning between 12:00 am and 13:00 pm with a HP8954 spectrum analyzer connected to an EMCO 3147 log-periodic antenna through a calibrated RG-213 cable. For GSM900 three carriers are clearly observed in Figure 5.17, which correspond to the values detected by the DMCMI for this sector of the BS (TC = 003, 032, 049; BCCH 935.6, 941.4, 944.8 MHz). At the same sector two carriers were also detected for the GSM1800 system, as shown in Figure 5.18 (TC = 660, 677; BCCH 1834.8, 1838.2 MHz). At the GSM900 band a maximum level of 110.4 dBμV/m was observed at 939.295 MHz, which corresponds to 0.33 V/m in linear units, with no postprocessing. At the GSM1800 band a maximum level of 127.9 dBμV/m is observed at 1834.9 MHz, which corresponds to 2.48 V/m in linear units, also with no postprocessing. The AF at the frequency where maximum GSM field levels were encountered was 23.0 dBm–1, and cable loss following the calibration figures was 2.3 dB. This procedure has to be repeated for all carriers in the sector, and after accounting for the superposition level, RB, and polarization

Figure 5.20

Superposition level study (1 to 30 MHz).

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In Situ Measured Exposure Assessment and Compliance Testing

Figure 5.21

Superposition level study (30 to 200 MHz).

Figure 5.22

Superposition level study (200 to 860 MHz).

correction factors, EQGSM900 has to be determined to assess compliance for the GSM900 system. The procedure has to be computed also for the GSM1800 system, and all results have to be combined to evaluate site compliance to safety guidelines. After some post-processing of the obtained data, EQGSM900 = 0.114 and EQGSM1800 = 0.136, and with CFRB, CFPOL, and SL, the TEQ of the site, for the worst-case scenario, was TEQ = 0.273 (27.3%). Hence, one can conclude that the base station of Figure 5.19 fulfils the evaluated safety limits, providing that no access is granted to distances up to λ/2 close to the base station. To finalize the assessment, a final report has to be undertaken. The results of each test, calculation, or measurement carried out shall be reported accurately, clearly, unambiguously, and objectively, and in accordance with any specific instructions in the followed procedure. The results shall be recorded in the test report and shall include all the information required for the interpretation of the survey or calibration results and all information required by the procedures. All the

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information needed for performing repeatable tests, calculations, or measurements giving results within the required calibration and uncertainty limits, including relevant information on the settings of controls and the intended usage of the equipment, shall also be recorded. For transmitters intended to be used with external antennas, at least one typical combination of transmitter and antenna shall be assessed. The technical specification of this antenna shall be documented in such detail that the boundary where the basic restrictions are met can be identified (e.g., by documented radiation patterns). Finally, the report shall clearly state the declaration of conformity of nonconformity of the BS to the tested guidelines. In case of dual-band or shared-sites, each individual report (system) must clearly state that the site has a global evaluation taking into account all systems in the site, and a separate global report has to be included.

5.6

Accurate Far-Field Compliance Testing for 3G Measurements 5.6.1

The Need for Measurements

If there are just a few procedures published for proper evaluation of exposure assessment of 2G systems, the number of papers published for 3G systems is scarce [12, 65–67]. Published procedures use either a spectrum analyzer for in situ measurements or simulated UMTS scenarios which require analog down-conversion of the input RF signal. For UMTS, the radio interface is characterized by great flexibility and a wide variety of different physical and logical channel types with circuit and packet switching, using several user rates and a choice of parameter settings like spreading factors, code rates, or automatic repeat request schemes, making the study of UMTS exposure evaluation and compliance testing somewhat difficult. Although UMTS’ contribution to electromagnetic exposure is well known to be lower than that of the second generation TDMA systems—since downlink power transmission is kept to a minimum to avoid undesirable interference between data traffic channels—this small contribution could be in jeopardy should measurements be undertaken with incorrect settings and procedures. In [66], some pioneer spectrum analyzer filtering settings are employed for UMTS base station electromagnetic field measurements, but these are not the core analysis of the manuscript and are not deeply analyzed, concluding that the influence of the video bandwidth filter is negligible compared to the influence of the resolution filter. Moreover, smart antenna use [68, 69], multibeam [70], or beamforming [71] in UMTS further reduces electromagnetic emissions while improving system capacity. In fact, when UMTS exposure is accounted for on top of previously existing systems in the same site, safety distances to conform to guidelines are only enlarged in theory by half a meter in the broadside direction [72]. Since the signal and radiating characteristics of third generation technologies have an ever-increasing complexity, both simulation engines and in situ measurement systems and techniques for electromagnetic exposure assessment are still the subject of current research efforts. The UMTS emission values and currently existing second generation field values are added up to account for the final total exposure ratio. Second generation signals to be evaluated have a dominant deterministic nature, but UMTS signals behave in a quasinoise way [73]. Since UMTS modulation schemes are wideband code division

154

In Situ Measured Exposure Assessment and Compliance Testing

multiple access (WCDMA) over 5-MHz FDMA channels employing spread spectrum techniques, signal power density values may follow around or below Gaussian-noise values. Yet, UMTS signals cannot be treated as noise, and in fact UMTS quality performance can seriously be diminished by repetitive impulsive noise in particular [74]. Background noise floor can also negatively affect both capacity and coverage range of UMTS systems at downlink and uplink services [75] and the maximum UMTS uplink capacity regarding noise effects is defined as an equivalent to 75% of the pole capacity (maximal theoretical capacity) of a CDMA system like GSM. When the duration of noise pulses approach that of UMTS chip rates, jamming can be expected, and its impact depends upon variable UMTS channelization code lengths; this problem still needs considerable research. If we add to this the fact that in urban environments man-made noise emissions are dominated by impulsive components rather than by Gaussian ones [76], it is clear that precise measurements have to be performed with extreme care to ensure compliance to safety standards and even to determine UMTS signal quality. Measurements still remain necessary for validation of the exposure assessment method. 5.6.2

The UMTS Downlink Signal

The CDMA scheme in UMTS is a direct-sequence CDMA (DS-CDMA); that is, the user information bits are spread over a certain bandwidth by multiplying the user data with quasirandom bits (chips) derived from CDMA variable spreading codes. Spreading takes place by the channelization used to separate the channels of one source, with a different channelization code for each data channel, and by scrambling Node Bs in downlink using pseudonoise codes, as illustrated in Figure 5.23, wherein loop power control is represented by power weights. Channelization in the downlink changes the data rate of the incoming signal to the UMTS chip rate of 3.84 Mcps for the in-phase and quadrature channels of the QPSK modulation scheme, with the spreading factor (SF) defining the number of chips used to spread one data symbol between 4 to 512. While modulation is done in the downlink direction after spreading, in the uplink direction the in-phase and quadrature channels are used to transmit two BPSK flows with different spreading codes [77]. This provides a bandwidth of 5 MHz. Since this bandwidth is much higher than other CDMA systems (CDMA for IS-95 has a bandwidth of about 1 MHz), UMTS DS-CDMA is often referred to as WCDMA. Scrambling does not change the signal data rate since it has the same chip rate as those of the channelization codes and uses long (38,400 chips) Gold-based codes in the downlink direction. WCDMA supports two basic modes of operation: the frequency division duplex (FDD) and the time division duplex (TDD). A typical measurement of FDD UMTS WCDMA using a Rhode & Schwarz FSH3 handheld spectrum analyzer is depicted in Figure 5.24. For electromagnetic exposure evaluation or compliance testing to electromagnetic safety standards, an extrapolation to account for the situation with maximum traffic has to be performed. This was easily done for GSM systems by measuring the BCCH carrier per sector, always set at the maximum power, and extrapolating this value for the number of available transmitters. For WCDMA UMTS signals this is more complicated, and an architecture analysis or simulating tools employing digital signal processing techniques is required to avoid a priori drawbacks of spectrum

5.6 Accurate Far-Field Compliance Testing for 3G Measurements

I/Q Splitter

Sdl,n I

155

G1

ChannelCode1 90° Q

G2

I ChannelCode2 90° Q

Gn

I

To modulation

ChannelCoden 90° Q GP

Primary synchronization channel

GS

Secondary synchronization channel Figure 5.23

I

Scrambling (Sdl,n) and channelization (ChCoden) of the downlink UMTS signal.

analyzers for power measurements of quasi-noise signals like UMTS [79]. The UMTS Terrestrial Radio Access Network (UTRAN) radio interface provides data transport services through three different channels: logical, transport, and physical. UTRAN is highly flexible to accommodate different bearer services with different bit rates and different transfer modes. Physical channels, which can be common or dedicated, are used to finally transmit the data or system operation parameters over the air interface and centered our interest. Transport channels are mapped onto physical channels and the dedicated physical data channel (DPDCH) is the dedicated channel carrying data from the dedicated transport channel (DCH), and it operates both uplink and downlink. The information useful for exposure evaluation is contained in the downlink dedicated physical control channel (DPCCH), which is transmitted simultaneously with the DPDCH by time multiplexing and carries physical layer information needed for system operation and to improve radio performance if required (as depicted in Figure 5.25). In the uplink, the DPCCH contains the common pilot channel (CPICH), which broadcasts a predefined bit pattern, which is used by the Node Bs to estimate the channel conditions and to cal-

156

In Situ Measured Exposure Assessment and Compliance Testing

Figure 5.24

Typical measured FDD UMTS WCDMA spectrum using a spectrum analyzer.

DPDCH Data 1

DPCCH TPC

TFCI

DPDCH

DPDCH

Data 2

Pilot

Tslot = 2,560 chips

Slot #0

Slot #1

Slot #i

Slot #14

Tframe = 10 ms

Figure 5.25

Time multiplexing of DPDCH and DPCCH in the UMTS downlink frame.

culate the signal-to-interference ratio (SIR) for the power commands. The SF for the uplink DPCCH is always 256; that is, there is always 10 bits per uplink DPCCH slot (data rate 15 Kbps). For the downlink, which is the link of interest for exposure assessment, since DPDCH and DPCCH are time multiplexed, the SF of DPDCH depends on DPCCH data rate and varies from 4 to 512. Pilot power decoding is then more difficult to obtain for the downlink. In addition, there are two types of common pilot channels, primary (P-CPICH) and secondary (S-CPICH). Since only the primary pilot channel always has a fixed channelization code allocation, and there is only one channel like that in a FDD UMTS cell or sector, it is the one that should be decoded and measured, if necessary. Modern spectrum analyzers include WCDMA code-domain power analyses with typical ±0.3-dB accuracies. In the uplink, reducing emitted CPICH power (PCPICH) causes terminals to hand over to other cells, while increasing it invites more terminals to hand over to the cell. The downlink PCPICH is set by the operators and is usually between 4% to 10% of the total BS power [2, 75]. This pilot power factor is defined by PCPICH. For downlink, perfect power control is assumed; that is, each channel perfectly achieves the target Eb/No (average energy per information bit to effective noise power spectral density),

5.6 Accurate Far-Field Compliance Testing for 3G Measurements

157

assuming that maximum transmitted power is not exceeded. The maximum downlink traffic channel power in the EU (Region 1) is 36 dBm. Since there may be more than one channel per Node B, maximum Node B output power is 43 dBm (20W). At each iteration of the downlink power control loop, the service petitioners request more or less power, depending on their carrier to interference (C/I) values. In the downlink, macrodiversity is modeled so that the signal received from active base stations is summed together; maximal ratio combining of n diversity paths is realized by summing measured SIR values together: SIR =

i=n

∑I i =1

Ci i + N

(5.18)

SIR in CDMA systems is expressed as the bit energy-to-interference density ratio (Eb/Io). Using a code domain analyzer, the important measure for determining UMTS WCDMA signal quality would be the (Ec /Io)2 (squared ratio of average energy per pseudonoise chip to total received power spectral density at the user equipment (UE) antenna connector, including signal and interference) [78] of the CPICH, Ec Io

= CPICH

RSCPCPICH RSSI

(5.19)

where RSCPCPICH (received signal code power) is the received power on one code measured, with the code specified as the pilot bits of primary CPICH, and RSSI (received signal strength indicator) is the wideband received power within the adequate channel bandwidth. The total Node B instantaneous radiated power for a user could be extracted with a code-domain analyzer with [78] PCCPCH _ E c + CPICH _ E c + TPC _ E c + TFCI _ E c + DPDCH _ E c + SCCPCH _ E c + OCNS _ E c = I or

(5.20)

where _Ec indicates the averaged energy per pseudo-noise chip of a specific channel; Ior is the total base station transmit power; PCCPCH is the primary common control physical channel; TPC is the transport format combination; TFCI is the transport format combination indicator; SCCPCH is the secondary common control physical channel; and OCNS is the orthogonal channel noise simulator, a mechanism used to simulate the users or control signals on the other orthogonal channels of a forward link. This calculation is useful for downlink dimensioning to avoid the possible downlink bottleneck of FDD UMTS. This dimensioning is based on averaged transmission power and not the maximum power for the cell edge, which is the link budget, since users at the edge may need more power for the connection than users close to the base station, and both requirements can be satisfied simultaneously by WCDMA. For electromagnetic exposure evaluation, however, it would be sufficient to decode and obtain the RSCPCPICH of the UMTS signal to be able to extrapolate measured values once the power factor PCPICH to maximum traffic base station power used to transmit the pilot code is known. PCPICH, like ntrx in GSM, is set by the

158

In Situ Measured Exposure Assessment and Compliance Testing

operators and can be somewhat confidential, but it can be acquired through the use of an UMTS testing mobile system by decoding system information or supplied by the network operator. Extrapolation using PCPICH would have a similar effect as making measurements with the Node B UMTS downlink signal set to its maximum traffic power. Alternatively, since in UMTS transmission blocks have a fixed length and only blocks belonging to the same user can be transmitted during a transmission time interval (TTI or frame), (5.20) could be evaluated only for one TTI by locating a high-speed user at the cell border, forcing maximum output power for the dedicated channel PCCPCH of that user. Yet, a frame is composed of multiples of 16 slots (1 slot = 625 μs), and repetitive measurements with worst-case scenarios would be difficult to be performed accurately, with cell dropping an important degrading factor of measurement validity. Extrapolation of measured field values to worst-case scenarios (WCS) for compliance testing is easily performed in a similar way to previously described extrapolation formulas in the literature [80] by PMeas UMTS WCS = PMeas UMTS E Meas UMTS WCS = E Meas UMTS

RSCPCPICH PCPICH η P CPICH

(5.21)

RSCPCPICH PCPICH η PCPICH

providing a UMTS exposure quotient (EQUMTS) of EQUMTS =

S Meas UMTS WCS S Guideline

(5.22)

where SMeas UMTS WCS is the extrapolated measured UMTS power density for the worst-case scenario, and SGuideline is the limit specified by the guideline for the spectral power density at 2,140 MHz. The worst-case scenario for EQUMTS will be represented by PMeas UMTS WCS in (5.21), which has been calculated with the maximum E-field measured within the 5-MHz UMTS band. Taking into account the extrapolation, EQUMTS has to be accounted for in the determination of the TEQ. A TEQ less than unity will indicate compliance with the guidelines under evaluation.

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[39] Schaefer, D.J., “Bioeffects of MRI and patient safety,” in The Physics of MRI, P. Sprawls and M.J. Bronskill, Eds., College Park, MD: American Association of Physicists in Medicine, 1992, pp. 387–421. [40] IRA/INIRP, “Protection of the patient undergoing a magnetic resonance examination,” Health Physics, Vol. 61, pp. 923–928, 1991. [41] Stuchly, S.S., Kraszewski, A., Stuchly, M., Hartsgrove, G., and Spiegel, R.J., “RF energy deposition in a heterogeneous model of man: Far-field exposures,” IEEE Transactions on Biomedical Engineering, Vol. 34, pp. 951–957, Dec. 1987. [42] ETSIT, Universidad Politécnica de Cataluña, “Plan de Comunicación sobre la Telefonía Móvil,” June 2000 (in Spanish). [43] Angelo, G.C., Neto, I., Correia, L.N., “Health and penetration issues in buildings with GSM base station antennas on top,” Proceedings of the 48th IEEE International Conference on Vehicular Technology, pp. 450–454, 1998. [44] Rapport au Directeur Général de la Santé, “Les téléphones mobiles, leurs stations de base et la santé,” Ministere Santé, France, January 2001. [45] Mann, S.M., Cooper, T.G., Allen, S.G., Blackwell, R.P., and Lowe, A.J., “Exposure to radio waves near mobile telephone base stations,” Chilton, National Radiological Protection Board Report. R 321, June 2000. [46] Aniolczyk, H., “Electromagnetic field pattern in the environment of GSM base stations,” International Journal of Occupational Medicine and Environmental Health, Vol. 12, pp. 47–58, 1999. [47] Neubauer, P.G., “Exposure next to base stations in Austria,” Austrian Research Center Seibersdorf, A-2444, Seibersdorf, Austria, 2000. [48] Hamnerius, Y., and Uddmar, T., “Microwave exposure from Mobile phones and base stations in Sweden,” Proceedings of the International Conference on Cell Tower Sitting, pp. 52–63, 2000. [49] “Radiocommunications (Electromagnetic Radiation — Human Exposure) Standard 1999,” Australian Communications Authority, 1999. [50] “Human Exposure to Radiofrequency Electromagnetic Energy,” Information for licensees or operators of radiocommunications transmitters: Evaluation of compliance with the ACA standard, Australia, September 2000. [51] Environmental Health Directorate, Health Protection Branch, Canada, Safety Code 6. “Limits of human exposure to radiofrequency electromagnetic fields in the frequency range from 3 KHz to GHz,” 99-EHD-237, 1991. [52] Bundesamt für Metrologie und Akkreditierung (METAS), “Nichtionisierende Strahlung Vergleichsmessungen an Mobilfunk-Basisstationen,” METAS Bericht 2002-256-472, 2002. [53] Netzer, M.Z., Hartal, O., “Cellular sectorial radio relay stations – radiation safety to personnel,” Proceedings of the IEEE International Symposium on Electromagnetic Compatibility, pp. 336–339, 1997. [54] Fabbri, S., Frigo, F., Violanti, S., Andreucetti, D., and Bini M., “Electromagnetic Field Monitoring and Control System: state-of-the-art and work-in-progress,” Radiation Protection Dosimetry, Vol. 97, No. 4, pp. 395–400. 2001. [55] Martínez-González, A.M., and Sánchez-Hernández, D., “New Advances in the Verification of Compliance of Digital Mobile Radio Base Stations to Limitations of Exposure of the General Public to Electromagnetic Fields,” Proceedings of the Progress in Electromagnetics Research Symposium (PIERS), 2003. [56] Martínez-González, A.M., and Sánchez-Hernández, D., “Electromagnetic Field Measurement Campaign in an Urban Environment. Exposure Levels in the City of Carthagene,” COST 281 Workshop on Mobile Pone Base Stations and Health, Dublin, Ireland, 2003. [57] Mann, S.M., Cooper, T.G., Allen, S.G., Blackwell, R.P., and Lowe, A.J., “Exposure to radio waves near mobile phone base stations,” National Radiological Protection Board Report R321, 2000.

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In Situ Measured Exposure Assessment and Compliance Testing [58] Olivier, C., and Martens, L., “A practical method for compliance testing of base stations for mobile communications with exposure limits,” Proceedings of the IEEE Antennas and Propagation International Symposium, Vol. 2, pp. 64–67, July 2001. [59] The European Conference of Postal and Telecommunications Administrations (CEPT) protocol ECC/REC/(02)04 2002, September 30, 2002. [60] Agence Nationale des Fréquences (ANFR), “Protocole de mesure in situ visant à vérifier pour les stations émettrices fixes, le respect des limitations, en terme de niveaux de référence, de l’exposition du public aux champs électromagnétiques prévues par le décret n° 2002-775 du 3 mai 2002,” ANFR/DR-15 v2.1, 2004. [61] Olivier, C., and Martens, L., “Optimal settings for narrow-band measurements used for exposure assessment around GSM base stations,” IEEE Transactions on Instrumentation and Measurement, Vol. 54, No. 1, pp. 311–317, 2005. [62] COST 244bis Final Report, “Biomedical effects of electromagnetic fields,” November 2000. [63] Wiart, J., Dale, C., Bosisio, A.V., Le Cornec, A., “Analysis of the influence of the power control and discontinuous transmission on RF exposure with GSM mobile phones,” IEEE Transactions on Electromagnetic Compatibility, Vol. 42, No. 4, pp. 376–385, 2000. [64] Hanna, S.A., “On human exposure to radio-frequency fields around transmit radio sites,” Proceedings of the IEEE International Conference on Vehicular Technology, Vol. 2, pp. 1589–1593, 1999. [65] Bernasconi, V., Bollea, L., Breda, A., Daponte, P., Maroncelli, G., Rapuano, S., “A TFR-based method for the quality assessment of UMTS signals: an application on the First Italian Experimental Network,” IEEE Transactions on Instrumentation and Measurement, Vol. 53, No. 2, pp. 485–492, 2004. [66] Joseph, W., Olivier, C., Martens, L., “A robust, fast, and accurate deconvolution algorithm for EM-field measurements around GSM and UMTS base stations with a spectrum analyzer,” IEEE Transactions on Instrumentation and Measurements, Vol. 51, No. 6, pp. 1163–1169, 2002. [67] Olivier C., and Martens L., “Optimal Settings for Frequency-Selective Measurements Used for the Exposure Assessment Around UMTS Base Stations,” IEEE Transactions on Instrumentation and Measurements, Vol. 35, No. 5, pp. 1901–1909, October 2007. [68] Dekorsy, A., Schacht, M., Jung, P., “On capacity and emission improvements by smart antennas in mixed traffic UMTS networks,” Proceedings of the IEEE International Symposium on .Signal Processing and Information Technology, pp. 572–575, 2003. [69] de Sousa, V.A., Jr., Cavalcanti, F.R.P., Lima, C.H.M., Rodrigues, E.B., “Performance study for a microcell hot spot embedded in WCDMA macrocell system with smart antennas,” Proceedings of the IEEE Vehicular Technology Conference, pp. 360–364, 2002. [70] Ericson, M., Osseiran, A., Barta, J., Gransson, B., Hagerman, B., “Capacity study for fixed multi beam antenna systems in a mixed service WCDMA system,” Proceedings of the 12th IEEE International Symposium on Personal, Indoor and Mobile Radio Communications PIMRC 2001, San Diego, CA, Vol. 1, pp. 31–35, 2001. [71] Valle, S., “Doppler spread measurements for tuning pilot-assisted channel estimation,” Proceedings of the IEEE International Symposium on Signal Processing and Information Technology, pp. 572–575, 2003. [72] Netzer, M., and Shahori, Z., “Radiation safety and environmental effects around cellular base stations of third generation DAMPS, DCS-1800, UMTS,” Proceedings of IEEE International Symposium on Electromagnetic Compatibility, pp. 95–99, 2002. [73] Apollonio, F., Liberti, M., D’Inzeo, G., “Theoretical evaluation of GSM/UMTS electromagnetic fields on neuronal network response,” IEEE Transactions on Microwave Theory and Techniques, Vol. 50, No. 12, pp. 3029–3035, 2002. [74] Sanchez, M.G., Alejos, A.V., Cuinas, I., “Urban wide-band measurement of the UMTS electromagnetic environment,” IEEE Trans. on Vehicular Technology, Vol. 53, No. 4, pp. 1014–1022, 2004.

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[75] Neubauer, T., and Bonek, E., “Impact of the variation in the background noise floor on UMTS system capacity,” Proceedings of IEEE Vehicular Technology Conf., pp. 2435–2439, 2001. [76] Constantinou, P., et al., “Man made noise measurements,” Proceedings of IEEE Vehicular Technology Conf., pp. 475–476, 1991. [77] 3rd Generation Partnership Project, “Spreading and modulation (FDD),” 3GPP TR 25.213 V6.2.0 03/2005. [78] 3rd Generation Partnership Project, “Radio Frequency (RF) system scenarios,” TR 25.942. V6.4.0 04/2005. [79] Angrisani, L., D’Apuzzo, M., D’Arco, M., “A new method for power measurements in digital wireless communications systems,” IEEE Transactions on Instrumentation and Measurement, Vol. 52, No. 4, pp. 1097–1106, 2003. [80] Wiart, J., “UMTS and exposure measurement,” COST-281 Workshop on Base Station Monitoring, Vienna, August 2003.

CHAPTER 6

Near-Field SAR Measurements with Automated Scanning Systems David A. Sánchez-Hernández and Juan F. Valenzuela-Valdés

6.1

Introduction Near-field tests are normally conducted for exposure assessments of new base station (BS) antennas or handset compliance testing, while far-field tests typically represent street level scenarios and are normally conducting for compliance testing. As it has been explained, compliance with safety guidelines can be accomplished by computational methods, which have to be efficient, reliable, and reasonably simple in order to predict the typical electromagnetic environment around base stations and provide worst-case scenarios. For that purpose, full-wave rigorous solutions do not necessarily provide more accurate results in the far-field for worst-case scenarios than simplified, less computationally demanding simulation models like the spherical wave or the cylindrical wave ones [1]. For measurements in the near-field, scanners were developed early in the 1970s using temperature-sensing or electric field probes [2] and in the 1980s using computer-controlled acquisition systems with external or implantable electric field probes [3]. The instrumentation for measuring near-field exposure with whole-body models is the same as that employed for partial-body models, which is well defined under the diverse standards. Despite the existence of several automated systems—such as the University of Utah system [4, 11] (depicted in Figure 6.1), which uses a 3D stepper motor to move a Narda model 8021 E-field probe inside a phantom, or the system developed at La Sapienza University of Rome [5]—there are mainly two commercial systems that dominate the market. One is the dosimetric assessment system (DASY) by Schmid & Partner Engineering AG (SPEAG) [6–8], and the other is the SAR assessment system (SARA) by IndexSAR [9, 10]. These two systems are depicted in Figure 6.2. These systems consist of a computer-controlled scanning robot which positions a triaxial miniaturized electric or magnetic field probe within the reduced space available between the boundaries of a phantom. The systems include the electronic circuitry for interfacing the probe with the computer, the instrumentation and sources for calibration and generation of the desired exposure scenario, data acquisition software, phantom models, tissue simulating liquids and both simulating and postprocessing software platforms.

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Figure 6.1 The 3D stepper-motor-driven automated SAR measurement system at the University of Utah. (Reproduced from [4] with permission from John Wiley & Sons.)

(a)

(b)

Figure 6.2 DASY5 (a) and SARA2 (b) SAR measurement systems. (DASY5 picture courtesy of SPEAG. SARA2 picture is courtesy of IndexSAR.)

An alternative to homogeneous liquids for measurements, which require a horizontal container and a robot for performing measurements, are the dry ceramic or jelly-based phantom models [12–14], although their application is somewhat limited and their use has not been popularized due to their inherent fabrication difficulties. Other computer-assisted systems and extensions of the above include the IXS-070 spherical scanning system, MultiSAR and SAR-WLAN by IndexSAR, and

6.2 Dosimetric Assessment System

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the hearing aid compatibility (HAC) (illustrated in Figure 6.3) and EASY4 four-channel exposure acquisition extensions of DASY4/5 by SPEAG.

6.2

Dosimetric Assessment System DASY5, an advanced version of DASY2, DASY3, and DASY4, is the latest version of the system described in [6, 8], which has enhanced accuracy and flexibility. The system comprises a mechanical arm to position an isotropic electric field probe inside a standardized phantom, typically the specific anthropomorphic mannequin (SAM), which has an ear thickness of 6 mm. When measuring, averaging procedures for DASY5 use a SEMCADX postprocessor. In DASY, the center of the measured volume is aligned to the interpolated peak SAR value of a previously performed area scan wherein the maxima is searched for. If the 10g is not entirely inside the measured volumes, it is shifted to higher values. Thus, a relatively large grid spacing for the area scan might give an incorrectly interpolated peak location. Since probes cannot directly measure at the phantom surface, the separating distance is included in an extrapolation algorithm to determine the values between the deepest measured point and the surface. Likewise, an interpolation algorithm is employed to provide a finer mesh for the measured results. The interpolation, extrapolation, and maximum search routines are all based on the modified quadratic Shepard’s method [15], with the rest being identical to the SEMCADX postprocessing averaging methods. Although DASY systems are intended for measurements in the near-field, some attempts which make use of DASY to characterize transition regions, or even the radiating near-field region for panel array antennas, have been reported [16–18], as depicted in Figures 6.4 to 6.6. All measurements confirmed that special attention has to be paid to the antenna model in simulations. Yet, there is no standard available for these measurements, and the validity of current standards for radiating fields evaluation of panel antennas is not yet clear [19].

6.3

SAR Assessment System The SAR assessment system (SARA) for compliance measurements to IEC/EN/FCC standards (by IndexSAR) employs a six-axis compact industrial robot with probe

Figure 6.3

Hearing Aid Compatibility extension by SPEAG. (Courtesy of SPEAG.)

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Field probe

Robot

Phantom

Antenna Figure 6.4

Measurements of SAR using DASY3 in [16].

Figure 6.5 Measurements of SAR using DASY3 in [17]. (Reproduced from [17] with permission from John Wiley & Sons.)

positioning and a SAM/flat phantom head situated upright, which has the advantage of using less liquid and having lower evaporation than other phantoms’ positions. The latest version of the system is called SARA2 and has an extension able to test 2 to 6-GHz WLAN packages. The major advantage of the SARA2 system is that it uses an upright phantom. The phantom volume is digitized and the location and

6.4 Portable SAR Systems

169

Figure 6.6 Measurements of SAR using DASY3 in [18]. (Reproduced from [18] with permission from John Wiley & Sons.)

orientation of the probe tip is known at all times, without having to return to the phantom surface to establish a position at each measurement point. This means it can make faster and more precise measurements. Extensions of SARA include a flat phantom, handset dipole mount, laptop-EUT support, and a side bench, depicted in Figure 6.7, among others.

6.4

Portable SAR Systems The recent development of algorithms that accurately and quickly estimate the peak 1g or 10g averaged SAR in a human part phantom when exposed to a wireless device using 2D area scans and 3D calculations [20] has prompted the appearance of portable SAR testing equipment. The most popular ones are i-SAR by SPEAG and MapSAR by IndexSAR, depicted in Figure 6.8. The i-SAR systems (the latest one at time of print was the i-SAR2) employs a head phantom for testing devices operated at the ear as required by IEC62209-1, IEEE 1528, and OET65, and a flat phantom for testing body mounted devices according to IEC 62209-2. The testers are filled with solid absorbing material simulating head or body tissue specifications

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Figure 6.7

Some extensions of SARA2. (Courtesy of IndexSAR.)

(a)

(b)

2

Figure 6.8 i-SAR by SPEAG (a) and MapSAR by IndexSAR (b). (Courtesy of SPEAG and IndexSAR.)

6.5 Sources of Inaccuracies

171

in the frequency range of 300 MHz to 6 GHz. In the basic configuration, a sensor array of 256 dipoles covers an active measurement area of 240 mm × 120 mm into a 3D SAR result, which includes the complete absorption pattern 4 mm below the surface. This allows for the visualization of differences in the absorption pattern between prototypes, the evaluation of the effect of small design modifications on RF performance and spatial peak SAR. The MapSAR systems (the latest one at time of print was the MapSAR2) also use a 2D mapping technique supplemented by 3D calculations, which give complete, volume-averaged SAR results directly. MapSAR uses a fully calibrated, isotropic SAR probe as its measuring device together with a 200-mm diameter glass sphere phantom simulating phantom head and several liquids as required by standards. Rather than moving the probe within the sphere, the sphere is moved instead. For a sphere, the translations are equivalent but mechanically simpler. A novel mechanism allows the sphere to be manually moved in two axes with a position encoder tracking the sphere/probe movement to a resolution ±0.2 mm. The SAR probe is removable but is normally fixed in position with the sensors 5 mm from the internal surface of the sphere. This depth is chosen to be centered on the 1g averaging volume giving maximum relevance to the instantaneous (spot) SAR reading. Once the required area has been scanned, the data are then automatically processed to display the 2D map in a regularly gridded format and spline-interpolated. Finally, the data are expanded into a 3D dataset using an understanding of the rate of decay of the SAR with depth in a sphere. Computations are then performed to show, simultaneously, the peak SAR averaged values over volumes of 1g or 10g.

6.5

Sources of Inaccuracies Measurements with different models provide different results. Full-body heterogeneous models have indicated that maximum SAR can be expected in the neck [21] and that energy deposition concentrates on the body region closest to the source of radiation. Likewise, maximum SAR positions were found equivalent for both heterogeneous and homogeneous models in early studies, but different in more detailed models. Some interesting discussion about SAR variation due to these and other variables is yet still to be fully addressed in the literature. In [22] it was made clear that the differences in computed SAR results for very similar methods could become very small when precise details of the simulation were harmonized, particularly in the regions close to the source point. Nikita [22] continued that even when the same cell size is used, the details for building the source in the Yee grid can produce discrepancies in the simulated parameters of interest. For example, the exact number of cells used for modeling a simple dipole, if the associated electrical size does not correspond to an integer number of cells, has a significant effect on the obtained results. Consequently, special care should also be taken to accurately evaluate the antenna output power since its setting can constitute a large uncertainty component. Something similar can be said for the dielectric material employed in measurements, for example, the head simulating liquid (HSL) in SAM phantoms. Most studies use data reported in [23] for the dielectric parameters, and due to the extremely

Near-Field SAR Measurements with Automated Scanning Systems

Relative permittivity

70 60

Relative permittivity Conductivity

3 Glycerol-based phantom 2.5

50

2

40

1.5 Muscle-equivalent phantom

30 20 10 0 0

1 0.5

5

10

15

20

25

Conductivity [S/m]

172

0 30

Day

Figure 6.9

Durability of the electrical properties of some recipes in [24].

long measuring times and the ageing effect of the head simulating liquids, near-field scanner measurements are usually performed with a 5-mm cell size. Despite this rather coarse measurement, different degradation rates can be found in the literature for the different recipes [24], illustrated as an example in Figure 6.9. Electromagnetic matching is better achieved for a solo 2/3-muscle tissue phantom [25], and this can be translated into different input impedances for the source and higher power absorbed in the tissue than for other tissues. The 2/3-muscle as the solo tissue also withstands better the enlargement of cell size [25], should this have to be performed, since there is more power deposited in the tissue, and therefore the percentage result for this tissue varies less than others depending upon cell size. Some authors have also observed increased absorbed power for larger cell sizes [26], but tissue differences were not accounted for. As a conclusion, it has long been abandoned the idea of [27], that for a source position at or above the ear provides the highest absorption values since SAR depends strongly on source matching, among other parameters. In fact, CENELEC standards do not use brain but rather HSL which has a dielectric constant slightly above that of 2/3-muscle tissue. A clear indication of this source of uncertainty is the different HSL recommended by the IEC [28], yet this may produce a 5% difference in peak SAR averaged over 10g, which is well below the 30% of uncertainty required for compliance testing. The limited use of the HSL or body tissue simulating liquid (BTSL) for far-fieldlike exposure evaluation using the scanning systems has recently been highlighted in [19], wherein it is concluded that the evaluation of the absorption in anatomical tissue sequences shows that the dielectric parameters of the tissue simulating liquids defined by current standards for compliance testing do not always yield a conservative exposure estimate for the averaged SAR in the body for far-fieldlike exposure conditions.

References [1] Karwowski, A., “Evaluating exposure to radio-frequency emissions from base station antennas,” Proceedings of the IEEE Microwaves, Radar and Wireless Communications, International Conference, pp. 1877–1881, 2002. [2] Balzano, Q., et al., “Energy deposition in biological tissue near portable radio transmitters at VHF and UHF,” Proceedings of the 27th IEEE Vehicular Conference, pp. 25–39, 1977.

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[3] Stuchly, S.S., et al., “A computer-based scanning system for electromagnetic dosimetry,” Rev. Sci. Instrum., Vol. 54, pp. 1547–1550, 1983. [4] Gandhi, O.P., Lazzi, G., Tinniswood, A., and Yu, Q-S., “Comparison of numerical and experimental methods for determination of SAR and radiation patterns of handheld wireless telephones,” Bioelectromagnetics, Vol. 20, pp. 93–101, 1999. [5] Pisa, S., et al., “Numerical–experimental validation of a GM-FDTD code for the study of cellular phones,” Microwave and Optical Technology Letters, Vol. 47, No. 4, pp. 396–400, Nov. 2005. [6] Schmid, T. et al., “Automated E-field scanning system for dosimetric assessments,” IEEE Transactions on Microwave Theory and Techniques, Vol. 44, pp. 105–113, Jan. 1996. [7] DASY4, “V4.5 System handbook,” SPEAG, Zurich, Switzerland, 2005. [8] Pokovic, K., “Advanced electromagnetic probes for near-field evaluations,” Doc. Tech. Sci. Diss. ETH Nr. 13334, Swiss Federal Institute of Technology (ETH), Zurich, Switzerland, 1999. [9] Gabriel, C., and Manning, M., “Assessment of exposure of people to electromagnetic near-fields from telecommunications equipment,” IEE Seminar on Electromagnetic Assessment and Antenna Design Relating to Health Implications of Mobile Phones, (Ref. No. 1999/043), pp. 2/1, June 1999. [10] http://www.indexsar.com. [11] Christ, A., Chavannes, N., Nikoloski, N., Gerber, H.U., Pokovic, K., and Kuster, N., “A numerical and experimental comparison of human head phantoms for compliance testing of mobile telephone equipment,” Bioelectromagnetics, Vol. 26, pp. 125–137, 2005. [12] Nojima, T., Kobayashi, T., Yamada, K., and Uebayashi, S., “Ceramic dry phantoms and its application to SAR estimation,” Proceedings of the IEEE International Conf. on Microwave Theory and Techniques, pp. 189–192, 1991. [13] Kobayashi, T., Nojima, T., Kamada, K., and Uebayashi, S., “Dry phantom composed of ceramics and its application to SAR estimation,” IEEE Transactions on Microwave Theory and Techniques, Vol. 41, pp. 136–140, Jan. 1993. [14] Nojima, T., Nishiki, S., and Kobayashi, T., “An experimental SAR estimation of human head exposure to UHF near fields using dry-phantom models and a thermograph,” IEICE Transactions on Communications, Vol. E77-B, No. 6, pp. 708–713, June 1994. [15] Renka, R.J., “Multivariate interpolation of large sets of scattered data,” ACM Transactions on Mathematical Software, Vol. 14, No. 2, pp. 139–148, 1988. [16] Bahr, A., et al., “Occupational safety in the near field of GSM base stations,” 2000 International Millennium Conference on Antennas & Propagation (AP-2000), Davos, Switzerland, 2000. [17] Cooper, J., et al., “Determination of safety distance limits for a human near a cellular base station antenna, adopting the IEEE standard or ICNIRP guidelines,” Bioelectromagnetics, Vol. 23, pp. 429–443, 2002. [18] van Wyk, M., Bingle, M., and Meyer, F.J.C., “Antenna modeling considerations for accurate SAR calculations in human phantoms in close proximity to GSM cellular base station antennas,” Bioelectromagnetics, Vol. 26, pp. 502–509, 2005. [19] Christ, A., Klingenböck, A., Samaras, T., Goiceanu, C., and Kuster, N., “The dependence of electromagnetic far-field absorption on body tissue composition in the frequency range from 300 MHz to 6 GHz,” IEEE Transactions on Microwave Theory and Techniques, Vol. 54, No. 5, pp. 2188–2195, 2006. [20] Kanda, M.Y., et al., “Faster determination of mass-averaged SAR from 2-D area scans,” IEEE Trans. on Microwave Theory and Techniques, Vol. 52, No. 8, pp. 2013–2020, Aug. 2004. [21] Stuchly, S.S., Kraszewski, A., Stuchly, M., Hartsgrove, G., and Spiegel, R.J., “RF energy deposition in a heterogeneous model of man: Far-field exposures,” IEEE Transactions on Biomedical Engineering, Vol. 34, pp. 951–957, Dec. 1987.

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Near-Field SAR Measurements with Automated Scanning Systems [22] Nikita, K.S., Cavagnaro, M., Bernardi, P., Uzunoglu, N.K., Pisa, S., Piuzzi, E., Sahalos, J.N., Krikelas, G.I., Vaul, J.A., Excell, P.S., Cerri, G., Chiarandini, S., De Leo R., and Russo P., “A study of uncertainties in modeling antenna performance and power absorption in the head of a cellular phone user,” IEEE Transactions on Microwave Theory and Techniques, Vol. 48, pp. 2676–2685, 2000. [23] Gabriel, C., “Compilation of the dielectric properties of body tissues at RF and microwave frequencies,” Brooks Air Force, Brooks AFB, TX, Tech. Rep. AL/OE-TR-1996–0037, 1996. [24] Ito, K., Hamada, L., Asahina, T., and Yoshimura, H., “Phantoms for estimation of interaction between antennas and human body,” 2000 International Millennium Conference on Antennas & Propagation (AP-2000), Davos, Switzerland, 2000. [25] Fayos-Fernández, J., Arranz-faz, C., Martínez-González, A.M., and Sánchez-Hernández, D., “Effect of pierced metallic objects on SAR distributions at 900 MHz,” Bioelectromagnetics, Vol. 27, pp. 337–353, 2006. [26] Monebhurrun, V., Dale, C., Bolomey, J.C., and Wiart, J., “A numerical approach for the determination of the tissue equivalent liquid used during SAR assessments,” IEEE Transactions on Magnetics, Vol. 38, No. 2, pp. 745–748, 2002. [27] Burkhardt, M., and Kuster, N., “Appropriate modeling of the ear for compliance testing of handheld MTE with SAR safety limits at 900/1800 MHz,” IEEE Transactions on Microwave Theory and Techniques, Vol. 48, No. 11, pp. 1927–1934, 2000. [28] IEC 62209-1, “Human exposure to radio frequency fields from hand-held and body-mounted wireless communication devices, Part 1: Procedures to determine the specific absorption rate (SAR) for hand-held devices used in close proximity to the ear (frequency range of 300 MHz to 3 GHz),” February 2005.

CHAPTER 7

The Effect of Metallic Objects on SAR Distributions David A. Sánchez-Hernández

7.1

Introduction One important aspect of EMF safety is related to the interaction of RF energy with passive or active implants in the human body. Many different types of metallic implants using stainless steel, titanium alloys, and cobalt chromium alloys have gained importance in the orthopedic prostheses industry due to their mechanical features that match those of the human bone [1]. Biocompatibility tests are typically performed to obtain the degree of chemical stability, corrosion resistance, and hardness. The electromagnetic compatibility of implants has been deeply studied, particularly for cardiac pacemakers or defibrillators. This is due to the need to avoid potential risks for patients. A good review can be found in [2]. Likewise, many studies are available in the literature regarding the effect of metallic implants on SAR distribution or temperature increments for magnetic resonance imaging (MRI) or computer tomography (CT) scans [3–9], hyperthermia or diathermia applications [10–12], and industrial applications [13, 14]. Similarly, the risk of implanted medical devices in workers exposed to EMF can also be studied in several publications [15]. However, very few study the high frequency range employed in wireless communications. Quite unexpectedly, just a handful of studies describe measured results [16–19]. This surprisingly low number of studies is in contrast with the increasing number of medical procedures that implant passive metallic objects within the human body, both at the surface and deep inside it, and the importance of a possible specific potential for EMF-related hazard in these individuals. Moreover, results at lower frequencies (60 Hz to ∼100 MHz) have already demonstrated that high intensity fields such as those in occupational exposure limits or under some fault conditions for MRI systems [20] are capable of significantly heating these metallic implants. It has to be specified, however, that this heat is very unlikely to be a significant hazard under realistic exposure conditions [13] or simply for common auditory or cochlear implants [12]. Similarly, excessive heating of metal implants has been proven with RF heat sealers [15], plastic welding machines, or induction furnaces [13], wherein pacemaker leads can act as antennas and lead to burns by coupling excessive RF currents into the tissue. In the RF industry, how-

175

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The Effect of Metallic Objects on SAR Distributions

ever, emissions are unwanted and occupational exposure levels can be avoided and treated. MRI or CT scans and hyperthermia or diathermia treatments are designed to specifically heat or explore the tissue with the patient’s authorization, and thus exposure, typically exceeding safety guidelines, is voluntary, with well-known heating effects on wire-leads and stimulators [11]. In fact, the application of short wave diathermy over metallic implants is usually contraindicated [21]. The effect on SAR distribution and temperature increments for wireless applications, however, is not voluntary and public exposure values must apply. Superficial (noninvasive) attached objects such as glasses (spectacles), earphones, earpieces, neck braces, hands-free wires, or superficially implanted objects such as earrings or piercings, and others, situated very close to the source of electromagnetic radiation may also influence the SAR distribution and the radiation characteristics of the handset antenna. Likewise, metallic elements included with invasive procedures include wire-leads for pacemakers, defibrillators, spinal cord stimulators, neurostimulators or cochlear implants, artificial metal joints, disks, pins, rods, screws, clips, and plates for orthopedics and dentistry, rings and stents in heart valves, electrodes, wires in sutures, bionic eras, hip prosthesis, auditory implants, transdermal delivery patches, drug delivery systems, or even complete electronic devices such as pacemakers or defibrillators. Some of these elements for orthopedics, dentistry, or surgery are depicted in Figures 7.1 and 7.2. The presence of metallic objects or walls in the near-field of antennas has long been known to alter the radiation properties, and some arrays like the Yagi antenna are specifically designed to make use of these alterations. Yet, it is less known that the presence of these metallic walls could increase the power absorbed in the head [24]. Even if the object is not metallic, its influence on SAR distribution can be significant, as discovered by [25] and [26]. An excellent summary of findings published until 2005 regarding passive metallic implants was reported in [27]. Just a few studies have been published after that, and most confirmed the general finding of aug-

Figure 7.1 Typical metallic implants used in orthopedics and dentistry. (Reproduced from [22] and [9] with permission from the Institute of Physics Publishing Ltd.)

7.2 Perfectly Conducting Spectacles and Eye Implants

177

Sternum 25 mm

7 mm

12 mm

19 mm

Figure 7.2 Schematic of sternum from the side showing wire implants in [23]. (Available at http://www2000.irpa.net/irpa7/cdrom/VOL.1/S1_150.pdf.)

mented SAR, but with resulting temperature increase below recommended thermal guidelines. The effect of a glass lens located in front of the cornea on SAR distribution was analyzed in [25], and an increase of approximately 31% of peak SAR averaged over the whole eye was found at 18 GHz, the frequency at which the simulated lens almost perfectly matches the cornea to the air. Previously, Bernardi had found that reduced peak SAR, averaged SAR, and total power absorbed were found when a dipole antenna was placed 0.5 cm away from a fat-layer-loaded human abdomen [24], and thus dielectric materials can influence SAR distribution either matching or mismatching the incoming wave. In [26], SAR averaged over 10g was found to increase in approximately 16.5% when a perfectly conducting square obstacle was providing scattering contributions from diffractions in edges and vertices to a human body placed away from the base station source. One important reason for these studies is the fact that, according to ICNIRP, SAR should be averaged over 10g for the exposure of the head and body but excluding limbs (abdomen). Consequently, this chapter summarizes recent advances on the influence of metallic implants on SAR distribution for the wireless communications frequency range, based upon the type of implant. A good rule of thumb regarding RF exposure assessment of metallic implants can be found in [28]. A review of the interaction of radio frequency electromagnetic fields and passive metallic implants was also published in 2006 [27].

7.2

Perfectly Conducting Spectacles and Eye Implants When the eyelids are closed and the skin does not protect the eye, this organ becomes one of the most hazardously exposed organs, and thus is the origin of safety thresholds [25]. Nonmetallic implants like glass lenses [25] or retina stimula-

178

The Effect of Metallic Objects on SAR Distributions

tors [29, 30] can make the multilayer structure match the air and hence increase SAR. This increment may lead to thermal increase above that specified in safety guidelines [25], which call for limits being specified directly using temperature increase. Metallic objects have a different interaction with electromagnetic waves. As with superficially attached objects, like metallic spectacles, SAR distribution is modified. In 1983 Griffin [31] demonstrated that metal-frame spectacles near the human eye in the presence of a monopole as the electromagnetic source provided a significant enhancement to shielding electric field values and depolarization at both 2 and 3.6 GHz. Anderson [16] revealed that a phantom wearing spectacles has a maximum measured 29% increment in nonaveraged peak SAR in the eye closest to the phone and a 295% increase in the brain, both at 835 MHz. The digital AMPS phone was held near the ear and configured to transmit at maximum nominal power (600 mW nominal). This important SAR increment yielded only a total of 0.83 W/kg and a temperature increase of 0.034ºC in the brain, which is well below safety guidelines worldwide. The use of metallic spectacles was studied through simulations in [32] with FDTD, using a monopole on a metallic box positioned at the side of the head of an heterogeneous phantom with a resolution of 5 mm. Considerable SAR increments (77% for peak SAR averaged over 1g and 73% for peak SAR averaged over 10g) were found in a whole body simulated model at 1,800 MHz, with a radiation efficiency drop of 19% and an increment of 42% in absorbed power when spectacles were present. Increments due to spectacles obtained in [32] are reproduced in Table 7.1. Similar increments were later obtained for SAR at 450 MHz and the monopole antenna placed in front of the right eye at a 30-mm distance [33]. These increments were associated with small tissue masses close to the auxiliary conductor. Peak SAR averaged over the eye was found to decrease, while peak SAR averaged over the head was found to increase. Surprisingly, a small efficiency increase and a reduced power deposition were also observed. Increments due to spectacles obtained in [32] are reproduced in Table 7.2. Similarly, several metal-frame spectacles were found to provide changes in SAR when antennas were mounted in a PDA at 1.5 to 3 GHz [34]. Results in [34] clearly called for in-depth studies in the matter so as to identify critical assessment factors and the role of frequency, eyelids, and size and shape of the metal frame. These studies were published in 2004 and 2005 [35, 36]. A detailed study for perfectly con-

Table 7.1

Effects of Metal-Frame Spectacles on SAR Head-Operated

Waist-Operated

Hands-Free

Spectacles

SAR max 1g (W/Kg)

0.321

0.399

0.901

0.567

SAR max 10g (W/Kg)

0.201

0.232

0.340

0.347

SAR max voxel (W/Kg) 0.501

0.523

3.580

0.789

SAR mean 1g (W/Kg)

4.16e-4

5.95e-4

6.55e-4

5.94e-4

SAR mean 10g (W/Kg)

4.11e-4

6.17e-4

6.66e-4

5.90e-4

SAR mean (W/Kg)

4.85e-4

7.02e-4

7.91e-4

6.88e-4

Power absorbed (W)

0.0420

0.0600

0.0704

0.0598

Efficiency (%)

57

35

23

38

Reproduced from [32] with permission.

7.2 Perfectly Conducting Spectacles and Eye Implants Table 7.2

179

Effects of Metal-Frame Spectacles on SAR

Domain efficiency, η (%)

Without Spectacles

With Spectacles

32.0

36.6 Location

Peak head SAR (W/kg)

Location

1g

4.17

Oribicularis oris

6.70

Nasalis

10g

2.52

Oribicularis oris

2.45

Oribicularis oris

1g peak eye SAR (W/kg) Right

1.61

1.00

Left

0.45

0.33

Extracted from [33].

ducting spectacles attached to a realistic Brooks Air Force MRI-scanned 1-mm resolution head model was published in [35]. The effects of spectacles on SAR from 1.5 to 3 GHz due to a plane wave irradiation of 50 W/m2, the maximum permissible exposure density limit for controlled environments under [37], or a dipole placed 15 mm away from the head, were studied. Since contact points were identified as possible hot spots, the frame did not touch the skin, and the eyelids were kept closed. Like in previous studies, a frequency-dependence behavior was observed; with average increments of 59% and 76% for the peak SAR averaged over 1g in the eye and in the head, respectively. The dipole and the plane wave were compared as sources, showing interestingly that source effects were ruled out as scaled results were encountered, illustrated in Figure 7.3. Likewise, the position of maximum SAR was always close to the metal edges of the spectacles, either on the side of the nose or on the side of the head next to the metallic arms. Results shown in [35] demonstrated that the specific spectacle frame, size, and polarization of the incoming wave were essential for defining the SAR variation. By altering the frame and the size of the spectacles the authors concluded that an average pair of spectacles could increase SAR in the eye by 50% at 1.8 and 2.4 GHz, while it could marginally decrease at 3 GHz. Results of SAR variation with simple spectacle frames are reproduced in Figure 7.4.

Average SAR in eye (W/kg)

0.25 0.20

Zdp with specs Zdp no specs Ez plane with specs/15 Ez plane no specs/15

0.15 0.10 0.05 0.00 1.5

2.5 2.0 Frequency (GHz)

3.0

Figure 7.3 A comparison of SAR in the eye at 1.8 GHz wearing spectacles with two different excitations: a 50 W/m2 Ez plane wave and a 0.6W Z-directed dipole. Plane wave results are scaled by a factor of 1/15. (Reproduced from [35] with permission from IEEE.)

180

The Effect of Metallic Objects on SAR Distributions

Average SAR in eye (W/kg)

3

2

1

0 1.5

No specs Square specs Circular specs Rectangular specs Elliptical specs

2.0

2.5

3.0

Frequency (GHz)

Figure 7.4 SAR averaged over the eye with and without spectacles. (Reproduced from [35] with permission from IEEE.)

It is also interesting to point out that lower averaged SAR values were found in this study when the eyelids were kept closed, which is in concordance to previous studies. Opening the eyelids at 5 GHz, on the other hand, was found to increase averaged SAR by 15%. Thus, the study concluded that specific configuration of spectacles could be designed to either reduce or increase average SAR in the eye at a specific frequency. This was concluded since most designs tend to increase average SAR by an average of 56%. Later in 2005 the same authors developed a genetic algorithm for a deep analysis of the role of size and shape of spectacles on SAR distribution [36] and concluded that these two were the most significant factors for SAR in the eye, along with the frequency and the polarization of the source. The use of spectacles was always found to decrease SAR in the eye for horizontal polarization of the source (parallel to the spectacles arms), and a complex shape-dependence was suggested for further work. The authors also conclude that current safety standards are unlikely to be breached by a real source with the use of perfectly conducting spectacles, which is not even common nowadays. All these simulations on spectacles and their interesting results are yet to be confirmed by measurements, but as it will be described further on, many problems are envisaged for measuring this influence since it is mainly concentrated on the volume taken by the phantom shell itself.

7.3

Electrodes and Wire-Leads Although hands-free operation (illustrated in Figure 7.5) enables the handset to be removed from the head region, health concerns are not avoided due to the presence of an RF-carrying conductor connecting the handset to the audio ear-piece. Likewise, simply transferring the handset to the waist (without the hands-free lead) produces peak SAR increments over 20% and a degradation of system efficiency [32, 38]. Consequently, hands-free devices have been the subject of many simulation studies. The interaction between the antenna and the conducting wire remains as the coupling mechanism, with large dependence on relative orientation, frequency of

7.3 Electrodes and Wire-Leads

181

Figure 7.5 Layout of cellular handset with nontypical use. (Reproduced from [38] with permission from the Institute of Physics Publishing Ltd.)

operation, and proximity of biological tissues. Early simulation studies on the effect of placing metallic electrodes showed that the fields surrounding the implants were implant size and shape, and frequency dependent [39]. Large SAR amplification factors (72% for peak SAR averaged over g and 30% for peak SAR averaged over 10g) were also numerically found for 20-cm-long implanted metallic pins and filaments at the implantation site within a human head modeled as a single-layer sphere, excited by a 0.45λ dipole at 900 MHz in [40]. Some polarization and resonance-related effects were also described in [40], with maximum SAR increments identified for filament lengths approaching ∼λm/2, where m represents the tissue, somehow agreeing to the earlier results by Guy [39]. The lower absorbed power observed when the implants were present was attributed to a blocking effect of the incident wave by the metallic implant. Likewise, the study concluded that the thinner the implant structure and the shaper the endpoints, the greater the increases in local SAR. Other studies have also concluded that, for implanted metallic pins and filaments, the worst-case scenario regarding SAR is that of the implant having been made equal to one-half of a wavelength in the tissue at the frequency of exposure [23]. A contradiction to these results was numerically found in [32, 33] for metallic flexible-filaments implanted in full-body realistic models at 1,800 MHz. Although SAR amplification factors similar to earlier studies were found (80% for peak SAR averaged over 1g and 69% for peak SAR averaged over 10g), power absorbed was found to increase for all implant scenarios while the radiation efficiency decreased. The wires were significantly longer than in previous studies (0.7m and 1m) and the frequency higher. Consequently, the effect on the radiation efficiency could be attributed to a wavelength-related factor since the filament length was far from ∼λm/2. What in principle may seem as a contradiction was an advance instead. In [35] another factor was found to dominate the coupling mechanisms for hands-free wire: that of the wire-antenna spacing. When the wire-antenna separation was

182

The Effect of Metallic Objects on SAR Distributions

enlarged to 0.18λ with respect to an original of 0.03λ, power absorbed was reduced from 70.4 mW down to 62.3 mW, normalized to a transmitting power of 125 mW. This represents an increase of 6.5% in radiation efficiency. A recent measurement study has revealed that no effect was observed in the device operation for a deep brain stimulator with 51-cm leads implanted 1 cm below the inner surface of a phantom shell. The shell was exposed to commercial GSM phones at both 900 and 1,800 MHz with maximum radiated peak power (2W at 900 MHz and 1W at 1,800 MHz) [17], as reproduced in Figure 7.6. Yet, this study measured for the first time the increased E-field by a wire-lead and its influence on the device’s operation, but not SAR. A broadband dipole was employed in an attempt to find the interference level to the device, defined as the transmitting power of the dipole when the implant showed an influence. Results found a relatively large value at 900 MHz (1.24W) compared to that at 1,800 MHz (0.14W), with extremely low levels around 1,500 MHz (0.005W). These low interference levels were only found for CW signals and when the dipole was placed directly on the skin surface next to the device and not in the lead loops or in the ear. This suggests an EMC effect on the device itself and not the wire leads. Unfortunately, no SAR values were provided. Studied for wire-leads in MRI scanning are also available. In [8], the associated heating due to the RF magnetic field of the MRI system is linked to both the length and the insulating properties of the wire. In summary, results on wire-leads have shown a length-frequency-spacing dependence and a general SAR increase, but more studies are required for proper thermal increase assessment. Results up to now have not demonstrated a threat to human health by providing thermal increments over those in safety guidelines at mobile communication frequencies, with the exception of diathermia treatments. In these patient-accepted high-power medical treatments, deep brain stimulators (DBS) have demonstrated the production of tissue heating rates up to twice as much as

7 cm

Electrode Electrode holder Hair line

3.5 cm

Figure 7.6 Test setup in [17]. (Article under verbatim copyright, available at http://www.biomedical-engineering-online.com/content/2/1/11.)

7.4 Pins

183

those reported for other leads, which in some situations have unfortunately lead to the patient’s death [11].

7.4

Pins Fayos-Fernandez [18] confirmed by measurements both the increments in peak SAR averaged over 1g and 10g and the lower power absorbed by the phantom when different metallic piercings in the ear region were present. In addition, a size and shape dependence was clearly observed in [18]. This dependence was predicted in 1992 [41] for orthopedic 9.5-cm-long metallic pins inserted in the bone tissue at the ankle and 5-cm-long pins in the bone tissue at the knee. The human body model consisted of a three-layer cylindrical tissue and the simulation technique employed a thin-wire hybrid moment-finite element method. The ankle scenario was studied at 640 MHz and the knee at 1,250 MHz. In both situations a field enhancement factor greater than 5 was found due to the metal implantations and a maximum was located near the tip of the pins. Likewise, absorbed power and different SAR values were calculated for a infinitely thin metallic wire and a circular disk implanted on an homogeneous 20-cm diameter sphere filled with a brainlike material ( r = 50, = 1.0 S/m) and fed by a 0.45λ dipole at 900 MHz [40]. With 1.05 million mesh points, the highest peak SAR values averaged over 1g were obtained for filament lengths of ∼0.5 λm, where λm is the wavelength within the homogeneous medium. Amplification factors for individual cells (1 mg) were found to be up to 38, while for 1g and 10g averaged SAR the maximum found amplification factors decreased to 1.6. If the implants were located near the sphere surface, a very marked increase in local SAR values was expected. Total absorbed power was lowered when implants were present. Unfortunately, the study was limited to infinitely thin metal, 900 MHz, and to a simple homogeneous sphere phantom. A more detailed study was published in 2005 [22] wherein implant size, orientation, location, and signal frequency were changed to find out worst-case scenarios. Results at 900 and 1,800 MHz confirmed a pin wavelength-related worst-case scenario, with averaged SAR over 1g and 10g increase due to the metallic implant by a factor of 3 or 2, respectively. It has to be mentioned that the implants moved peak SAR hot spots to near the implant itself, while with no implant these hot spots were located in the skin. A λ/4 monopole antenna on a generic phone was employed. Unfortunately, the human model was an homogeneous cylinder with a diameter of 150 mm and a 4-mm-thick skin surface layer, which makes the results difficult to be compared to those obtained in more realistic heterogeneous models. SAR distributions in different tissues with and without a pin implant and the relative enhancement of SAR when the implant was present are reproduced in Figure 7.7 and Table 7.3, respectively. In any case, no significant thermal increase was observed, and the thermal thresholds for damage were not surpassed. When the piercings or jewellery pieces are attached to the eyebrow instead of the ear, less pronounced SAR increments are found at both 900 and 1,800 MHz [19]. These increments are facilitated by a redistribution of the absorbed energy pattern inside the head, focusing this energy towards the area of the head nearest to the center of the pin [18, 19]. The measurement setup in [19] is reproduced in Figure 7.8.

184

The Effect of Metallic Objects on SAR Distributions

Muscle tissue 3

Fatty tissue

Bony tissue 3

3

z (cm)

20 dB 2

2

2

1

1

1

0

0

0

15 10 5 0

–1 0.5 1 1.5 2 2.5

–1 0.5 1 1.5 2 2.5 (a)

x (cm)

3

Muscle tissue

–1 0.5 1 1.5 2 2.5

3

Bony tissue

Fatty tissue 3

z (cm)

20 dB 2

2

2

1

1

1

0

0

0

–1 0.5 1 1.5 2 2.5

–1 0.5 1 1.5 2 2.5

–1 0.5 1 1.5 2 2.5

15 10 5 0

(b)

x (cm)

Figure 7.7 SAR distributions in different tissues with (a) and without (b) a pin implant. (Reproduced from [22] with permission.)

Table 7.3 Relative Enhancement of SAR when the Implant in Figure 7.7 Is Present Surrounding Tissue Under the Skin

7.5

SAR1max g (W kg ) max 1g

SAR

(W kg )ref

max SARpeak (W kg )

max SARpeak (W kg )ref

Muscle

2.1

47

Fat

1.6

53

Bone

2.2

50

Plates Large metallic plates are surgically implanted in the skull for such things as repairing defects in the skull resulting from an accident, for an operation like tumor removal, for a skull malformation, or simply to help ossification. In [40] a metal disk in the head was studied at 900 MHz, and although the authors highlighted the fact that such an implantation should seldom be a risk, its presence saw considerable

7.5 Plates

185

Figure 7.8 The measurement setup with the DASY4 system. The 72.5-mm dipole was positioned 98 mm away from the flat section of the twin SAM phantom. A 70-mm pin was hung 10 mm below the phantom. (Reproduced from [19] with permission from the Institute of Physics Publishing Ltd.)

enhanced local SAR values. These results were analyzed and reproduced in [42] for an evaluation of the occupational exposure conditions. This was done because the ICNIRP specifically recommended that persons carrying metallic items inside their bodies, when occupationally exposed to high electromagnetic fields, should be assessed for the potential of exceeding allowable localized SAR limits. McIntosh [42] added a simulated thermal study to the SAR simulation. A 50-mm-diameter 2-mm-thick titanium cranioplasty plate (depicted in Figure 7.9) was incorporated in the forehead of the visible human body model [43] and excited with a 10 W/m2 plane wave at frequencies from 100 to 3,000 MHz. Two effects were observed. The first one was a resonant effect around 200 to 300 MHz, whereby small SAR and temperature increments were attributed to an enhanced E-field since the plate diameter was around a third of a wavelength. The second one was a constructive or blocking effect in the frequency range 2,100 to 2,800 MHz, where the plate thickness corresponded to a distance of around a quarter-wavelength and the wave was reflected back and forth between the air-scalp interface and the scalp-plate interface. It is interesting to note from this study that, while ICNIRP SAR occupational

(a)

(b)

Figure 7.9 (a) The titanium cranioplasty plate modeled in [42]. (b) An example of a smaller titanium plate. (Available at http://www.medphys.ucl.ac.uk/mgi/brochure.htm and http://www. medphys.ucl.ac.uk/mgi/cranio.htm.)

186

The Effect of Metallic Objects on SAR Distributions

limits were never exceeded in the presence of the plate, the IEEE/ANSI 1999 limits were exceeded at 2,600 MHz in the tissue adjacent to the plate. In fact, even when the plate was not present, the IEEE/ANSI 1999 limit for peak SAR averaged over 1g was exceeded at 1,500 MHz and in the range from 2,100 to 2,300 MHz. This suggests that a large plate could indeed provoke an important trapping effect for high power density electromagnetic waves. A similar SAR enhancement due to a 2 × 45 × 95-mm skull metallic plate placed right under the ear and at 0.5 to 4-mm deep into the skin surface was found in [44], but only for peak SAR averaged over 1g. An enhancement of 162% in peak SAR1g was found in [44]. Yet, in [44] it was also made clear that more firm conclusions about the effect of implants would require predictions of maximum temperature elevations due to those SAR enhancements. In this sense it is interesting to note that in [42] the thermal model did not register any temperature increment over 1ºC, as depicted in Figure 7.10. Since SAR limits are specifically designed to avoid such temperature increments, this study suggests that even when the guideline limits are exceeded, one cannot guarantee that the recommended ICNIRP thermal threshold for biological effects (1ºC), which may not be necessarily negative, is surpassed. Moreover, in this study the temperature increments get close to 1ºC (at most 0.8ºC), and this is not sufficiently justified by the relatively large SAR increase with a maximum of 16.76 W/kg. In spite of the fact that the thermal simulation was rather conservative and the thermal capabilities of the human thermoregulatory system were not well reproduced, the high SAR combined with the influence of the metallic plate limited the maximum additional temperature increment to 0.05ºC. This suggests that there may be an inconsistency between the stated formulation of the limits and what is observed in theoretical studies, which has only become apparent when developments and hybridization of modeling techniques and computer capabilities have allowed such simulations to be performed. Or in other words, the unknown protective factors of current safety limits, stated in Chapter 1, are further enhanced by our body’s complex thermoregulatory system and are larger than initially predicted.

7.6

Rings, Piercings, and Auditory Implants Regarding auditory implants and piercings, electromagnetic interference of hearing aids with digital wireless telephones has received considerable attention [45, 46], even in the search for a solution to avoid such interference [47]. In contrast, the effect on SAR has only recently gained attraction. These implants, however, may include both an internal cochlear implant, such as the one depicted in Figure 7.11, and an external speech processor, also depicted in Figure 7.11. The high resolution numerical model of the middle and inner ear for detailed analyses of RF energy absorption has only been made available recently [48]. Consequently, most simulations and measurements are devoted to SAR effects due to metallic implants which are either attached or pierced to the external ear. Scientific references of measured SAR effects of these externally pierced metallic objects are scarce [18, 19, 44, 50]. The great importance of the implant orientation relative to the electromagnetic field source, highlighted years earlier [51], was emphasized when wearing metallic pins and rings in [22]. With appropriate reso-

7.6 Rings, Piercings, and Auditory Implants

187

10.00 Unaveraged

–1 SAR (Wkg )

1g cube average 10g cube average

1.00

0.10

0.01

0

300

600 900 1200 1500 1800 2100 2400 2700 3000 Frequency (MHz)

100.000

–1 SAR (Wkg )

10.000 1.000 1g cube average at IEEE limit 10g cube average at ICNIRP limit

0.100 0.010 0.001

10g pancake average at ICNIRP limit 0

300 600 900 1200 1500 1800 2100 2400 2700 3000 Frequency (MHz)

Temperature increase (°C)

1.000

0.100

0.010 Plate at IEEE limit Plate at ICNIRP limit 0.001 600

900

1200

1500 1800

2100

2400 2700 3000

Frequency (MHz)

Figure 7.10 Simulated SAR results and temperature increase in [42]. (Reproduced from [42] with permission from John Wiley & Sons.)

nance dimensions, orientations, and shapes, a large enhancement of the electric field and hence SAR is expected by simulations [22]. The model was performed using SEMCAD and a quarter-wave monopole antenna in a generic conductive case phone, with its feedpoint located 10 mm away from the skin surface of a cylindrical muscle, bone, or fat tissue phantom with a 4-mm skin layer, illustrated in Figure 7.12. The implants were perfectly electric conductor rings and pins with thickness in

188

The Effect of Metallic Objects on SAR Distributions

Volume control (a)

Receiver Microphone Ear hook

Telecoil Function S/W

Amplifier/ Circuit Battery

Magnet Implant case

(b)

Antenna Cochlea electrodes

Ball electrode

Figure 7.11 (a) External speech processor and (b) internal cochlear implant. (Reproduced from [49] and [47] with permission from John Wiley & Sons and IEEE, respectively.)

z y x Figure 7.12 Geometry employed in [22]. (Reproduced from [22] with permission from the Institute of Physics Publishing Ltd.)

the range of 0.5 to 8 mm and lengths or diameter in the range of 7 to 50 mm. All results were normalized to a peak input current of 100 mA, theoretically corresponding to an emitted power of 0.25W. The electric field was deformed towards the pin end in all cases, with the highest absorption values always observed in the tissues adjacent to the implant. No field enhancement was observed for perpendicularly oriented pins. Thickness was found to affect peak SAR only, but since averaging depends strongly on the method, tissue density, and heterogeneity, among other parameters, some results were not clarifying, particularly the effect of implant depth, where two effects were mixed, that of tissue dependence and field attenuation. Increment factors of 700 (35,000%), 3 (200% increment), and 2 (100% increment) were found for peak SAR, peak SAR averaged over 1g, and peak SAR

7.6 Rings, Piercings, and Auditory Implants

189

averaged over 10g, respectively, demonstrating a very localized effect, as in earlier studies. Based upon the three different pin lengths studied and the three different ring diameters, the authors also concluded that when pin lengths get close to λt /3 (14.67 mm at 900 MHz) and ring diameter to either λt /3 or λt /2 (22 mm at 900 MHz), the absorption was strongest. Yet, no simulations were provided for exactly those lengths and diameters, but rather for a pin length of 14 mm and a ring diameter of 30 mm, illustrated in Figure 7.13 and Table 7.4. Unfortunately, the manuscript does not mention whether this was also happening around 1,800 MHz. The authors also indicate that heating would not pose a risk since time averaging was not taken into account and because of the low power typically allowed in current mobile phones. Additional measurements at 1,800 and 2,140 MHz were published in 2007 and 2008 [44, 19]. Results at 1,800 MHz showed that pin size in wavelength-terms is important for determining absorbed power in the body. Consequently, the same pins may have a larger absorbed power at 1,800 than at 900 MHz. Yet, in [19] a resonant effect around 0.42λ was encountered at both 900 and 1,800 MHz, reproduced in Figure 7.14. In addition, the pin-to-head distance was another parameter to be accounted for, and the fact that the field penetrates deeper in the tissues at 900 7 mm

4

3

3

3

2

2

2

1

1

1

10

0

0

0

5

–1

–1

–1

–2

–2

–2

z (cm)

4

3 2 1 x (cm) 15 mm

z (cm)

28 mm

14 mm

4

1

2

3

2

3

50 mm

30 mm

3

3

3

2

2

2

1

1

1

0

0

0

–1

–1

–1

4

–2 3

0

(a) 4

2 1 x (cm)

15

1

4

–2

20 dB

15 dB

10

5

0

–2 1

2 (b)

3

1

2

3

Figure 7.13 The effect of size of the implant on SAR distribution in the x-z plane for a pin (a) and a ring (b). (Reproduced from [22] with permission from the Institute of Physics Publishing Ltd.)

190

The Effect of Metallic Objects on SAR Distributions Table 7.4 Relative Enhancement of SAR Values for the Pins and Rings of Figures 7.12 and 7.13

(

SAR1max W kg −1 g

(

SAR1max W kg g

−1

)

)

ref

( ) (W kg )

max SARpeak W kg max SARpeak

−1

−1

ref

Length of the Pin 7

1.2

13

14

2.1

47

28 Diameter of the Ring

1.4

27

15

1.6

14

30

2.7

6.2

30

1.5

2.4

MHz [44] could compensate the wavelength-related effect at higher frequencies for the same-size piercing. At the same time, tissue conductivity, absorption, and thus SAR increased for increasing frequency [44]. As a consequence, there is yet a clear frequency-related effect to be outlined for energy absorption enhancement due to the presence of metallic piercings. Despite the importance of the above-mentioned publication, the vast majority of published papers on the influence of metallic objects on SAR, however, were only based upon simulations. Although rudimentary, as it has been mentioned, the first measurements on the effects of metallic objects on the external field distribution were performed for spectacles and took place in 1983 [31]. Despite these results, no other measurements were reported until 1995 [16], and later in 2003 [11] for wire-leads and in 2006 [18], 2007 [50], and 2008 [19] for piercings. Several unusual but possible exposure situations using piercings at 900 MHz were considered in [18]. Measured results showed that for some scenarios local peak SAR increases in subjects wearing metallic implants in their face. Likewise, the reflection coefficient, radiated power, and radiation patterns were obtained, along with the SAR distribution, peak SAR averaged values over 1g and 10g of tissue, and the total absorbed power within the human head tissues. The codes used to solve the electromagnetic problems were CST Studio and SEMCAD. Four different aluminium-based metallic objects were employed as piercings in four different scenarios. Piercing 1 in Figure 7.15 was attached to the head models/phantoms EPI and BLAS/SAM to represent attached simulated and measured scenarios, while piercings 2 to 4 in Figure 7.16 were inserted in the outer/inner surface of EPI and BLAS/SAM to represent pierced simulated and measured scenarios. The simulated and fabricated metal implants can be observed in Figure 7.16. The implant was attached when it was not inserted in the human ear and only direct contact existed between the metallic implant and the modeled ear. When the implant was pierced to the human ear, some ear cells were replaced by the implant metallic material. Measurements were performed with the DASY4 system by SPEAG. For all scenarios, the dipole was located with its feedpoint directly above the ear reference point (ERP) at a distance of 10 mm to the surface of the head. The evaluated scenarios were: (a) dipole antenna in free space, (b) dipole antenna and EPI model, (c) dipole antenna and BLAS/SAM models, (d) dipole antenna and EPI model with attached metallic

7.6 Rings, Piercings, and Auditory Implants

191

2.0

Max 1g SAR (W/kg)

Just head Pin 6 mm from head

1.5

Pin 12 mm from head Pin 20 mm from head

1.0

0.5

0.0 0.0

0.1

0.2 0.3 Length of pin (wavelengths) (a)

0.4

0.5

3.0 Just head 2.5 Max 1g SAR (W/kg)

Pin 6 mm from head 2.0

Pin 12 mm from head

1.5 1.0 0.5 0.0

0.0

0.1

0.2

0.3 0.6 0.4 0.5 0.7 Length of pin (wavelengths) (b)

0.8

0.9

1.0

Figure 7.14 The resonant effect of an eyebrow piercing at 900 MHz (a) and 1,800 MHz (b). (Reproduced from [19] with permission from the Institute of Physics Publishing Ltd.)

object, (e) dipole antenna and EPI model with pierced metallic objects, (f) dipole antenna and BLAS/SAM models with attached metallic object, and (g) dipole antenna and BLAS/SAM models with pierced metallic objects, illustrated in Figure 7.16. Tables 7.5 and 7.6 list the calculated and measured results, respectively, for the feeding point impedance, the power factor, the power radiated by the antenna, the total power absorbed by the human model, the radiated power into free space in presence of the human head, and the total power radiated by the antenna computed as the power absorbed by the user plus the power radiated into free space. The ratio between radiated power and absorbed power is shown in the last row of Tables 7.5 and 7.6. From these tables, a good agreement between the two possibilities for extracting the radiated power of the antenna can be observed. The validity of simulated results for deducing conclusions is reinforced by the well-matched situations in all scenarios plus the usual radiation characteristics and the fact that all power is either radiated into free space or absorbed by the head as illustrated in Tables 7.5 and 7.6.

192

The Effect of Metallic Objects on SAR Distributions

l = 2.65

r = 3.33 1 w = 0.66

(a)

l = 2.5

2

3

r = [0.5√ 2, 1] 4 r = 0.5 (b)

Figure 7.15 Different metallic piercings used in the simulations and measurements (units in cm) in [18]: (a) piercing attachment setup for scenarios d and f; (b) piercing insertion setup for scenarios e and g. (Reproduced from [18] with permission from John Wiley & Sons.)

Simulated and measured peak SAR averaged over 1g and 10g of tissue and peak SAR averaged over the whole head, normalized to their respective maxima, are listed in Table 7.7 for all scenarios. Only one cell at the z-axis was found as a difference of position for diverse tissues within the same simulated scenarios. The effect of the measuring probe not being able to get close to the phantom surface and SAM 6-mm thick glass fiber composite surface at the ear was obvious for SAR measurements of scenario g, which has a piercing with three separate pieces, providing no initial SAR increase. In an effort to investigate the predicted increment described by the simulations with both CST and SEMCAD, which did not include the glass fiber composite case and thus favored coupling, and since DASY4 probes could get only within 9 mm of the EPI surface (4.0-mm-thick phantom surface plus probe security distance) and within 10.3 mm of the SAM ear outer surface (6.0-mm-thick phantom surface plus probe security distance), piercings 2 to 4 were relocated at the inner SAM surface. While measured results for scenarios e and g (outer surface) did not clearly confirm the

7.6 Rings, Piercings, and Auditory Implants

193

(a)

(b)

(c)

(d)

(e)

Figure 7.16 DASY4 Dosimetric Assessment System at Carthagene employed in [18]: (a) general picture; (b) simulated and measured metal object attached to the ear for scenario d; (c) simulated and measured metal objects pierced to the ear for scenario e; (d) simulated and measured metal object attached to the ear for scenario f; (e) simulated and measured metal objects pierced to the ear for scenario g. (Reproduced from [18] with permission from John Wiley & Sons.)

0.998

2.2

2.2

—

2.2

—

cos θ

Prad (W)

Prad frsp (W)

Pabsd (W)

Prad frsp + Pabsd (W)

Prad frsp/Pabsd (%)

69.95

0.33

0.24

0.09

0.35

0.377

34.2– j84.0

51.51

0.31

0.22

0.09

0.43

0.466

34.2– j84.0

5 mm

72.69

0.38

0.28

0.10

0.38

0.428

38.5– j81.3

60.03

0.39

0.28

0.11

0.47

0.532

41.9– j66.7

1.5 mm 5 mm

2/3 Muscle

SEMCAD

70.60

0.35

0.26

0.09

0.36

0.386

35.0– j83.6

1.5 mm

53.36

0.35

0.25

0.10

0.44

0.478

37.7– j69.3

5 mm

Volume Weighted

SEMCAD

71.58

0.35

0.26

0.09

0.37

0.403

36.5– j82.9

1.5 mm

HSL

SEMCAD

56.10

0.35

0.25

0.10

0.45

0.499

39.5– j68.5

5 mm

Scenario c

81.6

1.47

1.2

0.27

1.48

0.951

47.5– j15.4

5 mm

57.29

0.68

0.39

0.29

0.68

0.931

36.3– j14.3

5 mm

54.94

0.69

0.38

0.31

0.69

0.951

38.0– j12.4

5 mm

HSL

SEMCAD

Scenario d Scenario e SEMCAD

Heterogeneous HSL

CST

CST

Scenario g

83.5

1.33

1.11

0.22

1.34

0.983

42.9– j7.9

5 mm

81.4

1.29

1.05

0.24

1.31

0.894

57.8– j12.5

5 mm

Heterogeneous Heterogeneous

CST

Scenario f

Notes: Zin is the input impedance, cosè is the power factor, Prad is the power radiated by the antenna, Prad_frsp is the radiated power into free space in the presence of the human head computed by the near- to far-field transformation, Pabsd is the total power absorbed by the human model, Prad_frsp Pabsd is the total power radiated by the antenna computed as the power absorbed by the user plus the power radiated into free space.

70.4–j4.0

Zin (Ω)

Simulation results

5 mm

Voxel size

1.5 mm

Heterogeneous Muscle

Tissue

Scenario b

SEMCAD

CTS

Scenario a

Simulated Feed Point Impedance, Power Factor, and Radiated Power in [18]

Simulator

Table 7.5

194 The Effect of Metallic Objects on SAR Distributions

7.6 Rings, Piercings, and Auditory Implants Table 7.6

195

Measured Feed Point Impedance, Power Factor, and Delivered Power in [18]

Tissue

Scenario b

Scenario c

Scenario d

Scenario e

Scenario f

Scenario g

HSL

HSL

HSL

HSL

HSL

HSL

Measured results Zin (Ω)

43.3–j31.9

41.1–j34.3

43.7–j31.8

50.13–j17.7

43.0–j35.0

47.8–j19.9

cos θ

0.806

0768

0.808

0.943

0.775

0.923

Prad (W)

0.28

0.26

0.27

0.30

0.26

0.31

Prad frsp (W)

0.15

0.14

0.15

0.17

0.14

0.17

Pabsd (W)

0.12

0.11

0.12

0.14

0.12

0.13

Prad frsp + Pabsd (W)

0.27

0.25

0.27

0.31

0.26

0.30

Prad frsp/Pabsd (%)

44.26

44.12

45.01

45.61

44.61

43.23

Notes: Zin is the input impedance, cosè is the power factor, Pdel is the power delivered to the antenna measured with the directional coupler, Pdel_frsp is the radiated power into free space in the presence of the human head, Pabsd is the total measured power absorbed by the human model, Pdel_frsp Pabsd is the total power radiated by the antenna computed as the power absorbed by the user plus the power radiated into free space.

Table 7.7 Simulated and Measured Peak SAR Averaged over 1g, 10g, and Whole Head in W/Kg in [18] Simulated Scenario b Scenario c Scenario d Scenario e Scenario f Scenario g Simulator

CST

SEMCAD

CST

SEMCAD

SEMCAD

CST

CST

Model

EPI

EPI

BLAS

EPI

EPI

BLAS

BLAS

Peak SAR

19.3

17.3

16.4

18.9

20.9

24.4

30.4

Peak SARave 1-g

15.7

10.6

14.8

10.8

10.4

18.8

19.7

6.6

10.3

6.8

6.7

12.3

10.6

—

0.20

—

—

0.21

0.20

Peak SARave 10-g 9.9 SARave whole head

0.22

Measured

Scenario b

Scenario c

Scenario d

Scenario e

Scenario f

Scenario g

Measuring System

DASY4

DASY4

DASY4

DASY4

DASY4

DASY4

Model

EPI

SAM

EPI

EPI

SAM

SAM Outer

SAM Inner

Peak SAR

15.0

15.5

15.3

15.1

17.8

14.2

28.8

Peak SARave 1-g

13.9

14.4

14.3

14.1

16.2

13.2

16.5

Peak SARave 10-g 8.5 SARave whole head

—

8.5

8.6

8.7

8.4

8.1

9.3

—

—

—

—

—

—

changes in SAR values observed at the outer ear surface in close contact with the metallic pieces, the insertion of metal implants at the phantom inner surface provided final increased measured SAR exposure values closer to simulated ones. Figure 7.17 shows the computed normalized peak SAR distribution for a vertical cut containing the antenna plane for EPI and BLAS head models at 900 MHz (scenarios b and c). The increase in both simulated and measured peak SAR values and deformed distribution of scenarios d and e can be observed in Figures 7.18 and 7.19. Figure 7.20 illustrates calculated peak SAR at the BLAS ear with (a) and without (b) metallic objects (scenarios c and g), as well as a comparison (c) through (a) and (b) at 900 MHz. The with-object situation chosen for this comparison is that corresponding to the worst-case (largest SAR) exposure—that is, the pierced metallic

196

The Effect of Metallic Objects on SAR Distributions EPI

BLAS

SAR (W/kg) 0

20

Figure 7.17 Simulated SAR distribution within EPI and BLAS models at antenna plane in [18]. (Reproduced from [18] with permission from John Wiley & Sons.)

z

y 0 dB x –4 dB

(a)

–8 dB

–12 dB

–16 dB

–20 dB

z y 0 dB x –4 dB

–8 dB (b) –12 dB

–16 dB

–20 dB

Figure 7.18 SAR distribution for scenario d in XY plane at z = 0.00359 in [18]: (a) simulated (EPI and SEMCAD); (b) measured (EPI and DASY4). (Reproduced from [18] with permission from John Wiley & Sons.)

7.6 Rings, Piercings, and Auditory Implants

197

z y 0 dB

x

–4 dB

–8 dB (a) –12 dB

–16 dB

–20 dB

z y 0 dB

x

–4 dB

–8 dB (b) –12 dB

–16 dB

–20 dB

Figure 7.19 SAR distribution for scenario e in XY plane at z = 0.00813 in [18]: (a) simulated (EPI and SEMCAD); (b) measured (EPI and DASY4). (Reproduced from [18] with permission from John Wiley & Sons.)

25

25

25

20

20

20

15

15

15

10

10

10

5 (a)

5 (b)

5 (c)

Figure 7.20 Simulated SAR distribution (W/kg) at the ear for scenario g in [18]: (a) without metallic objects (scenario c); (b) with metallic objects (scenario g); (c) difference between (a) and (b). (Reproduced from [18] with permission from John Wiley & Sons.)

198

The Effect of Metallic Objects on SAR Distributions

objects or scenario g. Figure 7.21 illustrates measured peak SAR values for scenarios f and g. Confirming previous publications with these measurements, changes in SAR values as a result of attaching or piercing metallic objects were only observed in the proximity of these objects. A maximum SAR increase of 25% when piercings were pierced was simulated, confirmed by DASY4 measurements. Measured peak SAR values averaged over 1g of tissue increased up to 16.5 W/kg, representing a maximum increase of 18.7%. In the BLAS model only one layer was employed for the ear, and it is only in that layer where noninsignificant changes were observed. Measured results show that an increase in peak SAR values was observed in all pierced scenarios, while peak SAR averaged over 1g shows less important increments, but also in all scenarios. SAR increase was also nearly diluted for peak SAR averaged over 10g, although small increments are observed for some scenarios. These results are in agreement with other studies. Wherever made, whole-head averaged values showed no SAR increments, demonstrating the localized character of the increments. Likewise, measured absorbed power was very similar for the without-object

z y 0 dB

x

–4 dB

–8 dB

–12 dB (a)

–16 dB

–20 dB

z y x

0 dB –4 dB

(b) –8 dB

–12 dB

–16 dB

–20 dB

Figure 7.21 Measured peak SAR distribution with DASY4 for scenarios f and g in [20]: (a) scenario f; (b) scenario g. (Reproduced from [18] with permission from John Wiley & Sons.)

7.6 Rings, Piercings, and Auditory Implants

199

situations and objects attached or pierced to the ear of the EPI/SAM phantoms, with scenario g (pierced metallic objects in SAM) showing slightly less absorbed power than scenario c (BLAS with no piercings). These other results are also in agreement with other previous publications. Recently, these measurements were replicated for circular rings in [50] using the flat part of the SAM phantom. Results in [50] confirmed that a localized increased SAR could be expected with piercing metallic objects. In [50], the authors also concluded that the earrings caused the largest SAR when the ring was approximately 1 wavelength in circumference. The geometry of the ear and surrounding tissues was also found to be of great importance for final SAR influence of the piercing. The test setup and simulated and measured results in [50] are reproduced in Figures 7.22 and 7.23, and Table 7.8, respectively.

Figure 7.22

Test setup in [50]. (Reproduced from [50] with permission.)

12 0 mm 4 mm 8 mm

10

12 mm SAR (W/kg)

8

16 mm No loop

6

4

2 0 0.6

0.6 0.7

0.8

0.9

1.0

1.1

1.2

Circumference of loop (wavelengths)

Figure 7.23 Diverse simulated results of ring piercings in [50]. (Reproduced from [50] with permission.)

200

The Effect of Metallic Objects on SAR Distributions Table 7.8 The SAR1g and SAR10g Measured Results in a Flat/Cubic Phantom with a 52-mm-Diameter Loop Piercing Placed 14 mm away from the Surface FDTD No Loop

DASY4 No Loop

Microstripes No Loop

FDTD 52 mm Loop

DASY4 52 mm Loop

Microstripes 52 mm Loop

1g SAR (W/kg)

1.74

1.70

1.60

11.03

10.23

10.09

10g SAR (W/kg)

1.05

1.06

1.09

5.73

5.71

5.97

Extracted from [50].

Thus, an increase in peak SAR values is expected when piercing metallic objects to the human face or head. This global effect can be minimized for some commercial systems when accounting for the specific characteristics of such systems—like discontinuous transmission in GSM systems, or power control, lower handset power, modulation, and spread spectrum schemes in UMTS—although research is envisaged and recommended for medium- to high-power radio transmitters which are used directly in front of the user’s face, like in TETRA. Neither simulated nor measured values for peak SAR averaged over 10g and over the whole head changes significantly, and thus the findings do not contravene diverse standard safety limits. Nevertheless, research is envisaged to obtain knowledge of the diverse parameters’ influence on SAR increments, such as frequency, shape, size, and orientation of the metallic implant. Since nowadays CT scans are avoided when metallic implants are present [52], it is not unlikely that special care could be advised for frequent wireless users wearing large metallic implants near the radiating source. The use of auditory implants has also been studied during MRI [53]. MRI is preferred to CT scans due to the absence of ionizing radiation and better resolution in soft tissues, yet it uses a strong static magnetic field, and a pulse RF field, which may lead to tissue heating. The auditory implants are usually implanted near the cochlear nucleus, and hence are known as cochlear implants (CI). The CI usually consists of a stimulator/receiver, wire-leads, and some electrode contacts attached to a mesh carrier. The studies in 1995 [53] showed no associated tissue heating for 4×1.5 Tesla MRI using five different full-size homogeneous human phantoms. Similarly, MRI scanning was found to provide no associated heating for middle-ear implants [9]. These results have also been recently confirmed in 2008 by simulations for mobile-phone type exposures [49] in order to investigate conformance to the European safety requirements for implantable medical devices set up in 1998 and partially modified in 2003 [54]. This standard requires that no outer surface of an implantable part of the active implantable medical device shall be greater than 2ºC above the normal surrounding body temperature of 37ºC when implanted. The internal and external components of the cochlear implants in [49] are reproduced in Figures 7.24 and 7.25. Results in [49] showed minimal differences when the implant was present at both 900 and 1,800 MHz. Results are summarized in Table 7.9. It is interesting to observe from Table 7.9 that despite higher SAR10g with the implant, the resulting thermal increments were lower than without the implant. Since peak 10g averaged SAR was located at different spots, results in [49] may include some matching effects due to the implant presence. In spite of this, it seems clear that patients with cochlear implants comply with the EMF safety requirements of ICNIRP.

7.6 Rings, Piercings, and Auditory Implants

201 Magnet

Implant case

Antenna Cochlear electrodes

Ball electrode Figure 7.24 The internal cochlear implant in [49]. (Reproduced from [49] with permission from John Wiley and Sons.)

Figure 7.25 The external cochlear implant in [49]. (Reproduced from [49] with permission from John Wiley and Sons.)

Table 7.9

Effect of Piercings at 900 and 1,800 MHz 900 MHz 250 mW CW

1800 MHz 125 mW CW

With Implant Peak 10g SAR(W/kg)

1.31

0.93

ΔTmax(°C)

0.33

0.16

Peak 10g SAR (W/kg)

1.02

0.63

ΔTmax(°C)

0.08

0.07

Without Implant

From: [49].

202

7.7

The Effect of Metallic Objects on SAR Distributions

Stents Using stents made of alloy wire is one method for treating stenosis of lumens organ from various causes. With cardiovascular disease being a leading cause of death in Western countries, the use of metallic stents is ever-increasing. Concerns about the possibility of a patient’s stent being heated up by a strong field, particularly magnetic, from either MRI scans or simply RF industrial furnaces has been studied [13]. In [13] it was concluded through measurements at an industrial induction heating facility that significant heating of cardiovascular stents will not occur under realistic exposure conditions near induction heating equipment, and that existing safety standards provide adequate protection for the patient with stents. Not only are stents not sufficiently heated by external magnetic fields, but some authors have proposed to change this so that some sort of thermotherapy using induced eddy current losses could be used to avoid restenosis due to a bile duct tumor or abcess [55]. Thermal increase in the stent could be enhanced by a thermosensitive magnetic material attached to it [55], which can also provide for superior elasticity. Current medical procedures employ microwave-assisted balloons for placing and attaching and partially merging the stents to the duct.

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7.7 Stents

203

[11] Ruggera, P.S., et al., “In vitro assessment of tissue heating near metallic medical implants by exposure to pulsed radio frequency diathermy,” Physics in Medicine and Biology, Vol. 48, pp. 2919–2928, 2003. [12] Chou, C.K., et al., “Absence of radiofrequency heating from auditory implants during magnetic resonance imaging,” Bioelectromagnetics, Vol. 16, pp. 307–316, 1995. [13] Foster, K.R., et al., “Heating of cardiovascular stents in intense radiofrequency magnetic fields,” Bioelectromagnetics, Vol. 20, pp. 112–116, 1999. [14] Stuchly, M.A., and Lecuyer, D.W., “Induction heating and operator exposure to electromagnetic fields,” Health Physics, Vol. 49, pp. 693–700, 1985. [15] Hocking, B., Joyner, K.H., and Fleming, A.H.J., “Implanted medical devices in workers exposed to radio-frequency radiation,” Scandinavian Journal on Work Environment and Health, Vol. 17, pp. 1–6, 1991. [16] Anderson, V., “Specific absorption rate levels measured in a phantom head exposed to radio frequency transmissions from analog hand-held mobile phones,” Bioelectromagnetics, Vol. 16, pp. 60–69, 1995. [17] Kainz, W., et al., “Electromagnetic interference of GSM mobile phones with the implantable deep brain stimulator, ITREL-III,” BioMedical Engineering OnLine, pp. 2–11, 2003. [18] Fayos-Fernández, J., et al., “Effect of pierced metallic objects on SAR distributions at 900 MHz,” Bioelectromagnetics, Vol. 27, pp. 337–353, 2006. [19] Whittow, W.G., et al., “On the effects of straight metallic jewellery on the specific absorption rates resulting from face-illuminating radio communication devices at popular cellular frequencies,” Phys. Med. Biol., Vol. 53, pp. 1167–1182, 2008. [20] Chou, C.K., et al., “RF heating of implanted spinal fusion stimulator during magnetic resonance imaging,” IEEE Transactions on Biomedical Engineering, Vol. 44, pp. 367–373, 1997. [21] Gedes, L.A., and Baker, L.E., Principles of Applied Biomedical Instrumentation, Third Edition, New York: Wiley, 1989. [22] Virtanen, H., et al., “Interaction of mobile phones with superficial passive metallic implants,” Physics in Medicine and Biology, Vol. 50, pp. 2689–2700, 2005. [23] Joyner, K.H., et al., “Metallic implants and exposure to radiofrequency radiation,” Proceedings of the 7th IRPA International Conference, pp. 477–480, 1998. [24] Bernardi, P., et al., “Human exposure to radio base-station antennas in urban environment,” IEEE Transactions on Microwave Theory and Techniques, Vol. 48, No. 11, pp. 1996–2002, 2000. [25] Bernardi, P., et al., “SAR distribution and temperature increase in an anatomical model of the human eye exposed to the field radiated by the user antenna in a wireless LAN,” IEEE Transactions on Microwave Theory and Techniques, Vol. 46, No. 12, pp. 2074–2082, 1998. [26] Martínez-Búrdalo, M., et al., “An efficient FDTD–time-domain equivalent currents method for safety assessment in human exposure to base-station antennas in presence of obstacles,” Microwave and Optical Technology Letters, Vol. 48, No. 10, pp.1987–1991, Oct. 2006. [27] Virtanen, H., et al., “Interaction of radio frequency electromagnetic fields and passive metallic implants-a brief review,” Bioelectromagnetics, Vol. 27, pp. 431–439, 2006. [28] Anderson, V., and McIntosh, R., “Guidelines for the RF exposure assessment of metallic implants,” in International EMF Dosimetry Handbook, available at http://www.emfdosimetry.org/. [29] DeMarco, S.C., et al., “Computed SAR and Thermal Elevation in a 0.25-mm 2-D Model of the Human Eye and Head in Response to an Implanted Retinal Stimulator—Part I: Models and Methods,” IEEE Transactions on Antennas and Propagation, Vol. 51, No. 9, pp. 2274–2285, Sept. 2003.

204

The Effect of Metallic Objects on SAR Distributions [30] DeMarco, S.C., et al., “Computed SAR and Thermal Elevation in a 0.25-mm 2-D Model of the Human Eye and Head in Response to an Implanted Retinal Stimulator—Part II: Results,” IEEE Transactions on Antennas and Propagation, Vol. 51, No. 9, pp. 2286–2295, Sept. 2003. [31] Griffin, D.W., “A microwave antenna method of measuring the effect of metal-framed spectacles on microwaves near the eyes,” Proceedings of the IEEE Antennas and Propagation International Symposium, pp. 253–256, 1983. [32] Troulis, S.E., et al., “Effect of ‘hands-free’ leads and spectacles on SAR for a 1.8 GHz cellular handset,” Proceedings of the 1st Joint IEI/IEE on Telecommunications Systems, 2001. [33] Troulis, S.E., et al., “Influence of wire-framed spectacles on specific absorption rate within human head for 450 MHz personal radio handsets,” Electronics Letters, Vol. 39, No. 23, pp. 1679–1680, 2003. [34] Whittow, W., et al., “A study of changes to specific absorption rates in the human eye close to perfectly conducting spectacles within the radio frequency range 1.5 to 3.0 GHz,” 12th International Conference on Antennas and Propagation (ICAP), pp. 300–303, 2003. [35] Whittow, W.G., and Edwards, R.B., “A study of changes to specific absorption rates in the human eye close to perfectly conducting spectacles within the radio frequency range 1.5 to 3.0 GHz,” IEEE Transactions on Antennas and Propagation, Vol. 52, No. 12, pp. 3207–3212, 2004. [36] Edwards, R.M., and Whittow, W.G., “Applications of a genetic algorithm for identification of maxima in specific absorption rates in the human eye close to perfectly conducting spectacles,” IEE Proceedings on Microwaves, Antennas and Propagation, Vol. 152, No. 3, pp. 89–95, 2005. [37] International Commission on Non-Ionizing Radiation Protection, “Guidelines for limiting exposure to time-varying electric, magnetic, and electromagnetic fields (up to 300 GHz),” Health Physics, Vol. 74, pp. 494–522, 1998. [38] Troulis, S.E., et al., “Effect of a hands-free wire on specific absorption rate for a waist-mounted 1.8 GHz cellular telephone handset,” Phys. Med. Biol., Vol. 48, pp. 1675–1684, 2003. [39] Guy, A.W., “Biophysics – energy absorption and distribution,” AGARD Lecture Series on Radiation Hazards, Report No. LS-78, 1975. [40] Cooper, J., and Hombach, V., “Increase in specific absorption rate in human heads arising from implantations,” Electronics Letters, Vol. 32, No. 24, pp. 2217–2219, 1996. [41] Fleming, A.H.J., et al., “Calculation of electric fields in tissue near metallic implants,” Proceedings of the Asia-Pacific Microwave Conference, pp. 229–232, 1992. [42] McIntosh, R.L., Anderson, V., and McKenzie, R.J., “A numerical evaluation of SAR distribution and temperature changes around a metallic plate in the head of a RF exposed worker,” Bioelectromagnetics, Vol. 26, pp. 377–388, 2005. [43] National Library of Medicine, “The Visible Human Project,” available from: http://www.nlm.nih.gov/research/visible/visible_human.html/. [44] Virtanen, H., et al., “The effect of authentic metallic implants on the SAR distribution of the head exposed to 900, 1800 and 2450 MHz dipole near field,” Phys. Med. Biol., Vol. 52, pp. 1221–1236, 2007. [45] Skopec, M., “Hearing aid electromagnetic interference from digital wireless telephones,” IEEE Transactions on Rehabilitation Engineering, Vol. 6, No. 2, pp. 235–239, June 1998. [46] Caputa, K., et al., “Evaluation of electromagnetic interference from a cellular telephone with a hearing aid,” IEEE Transactions on Microwave Theory and Techniques, Vol. 48, No. 11, pp. 2148–2154, Nov. 2000. [47] Yang, T., et al., “Cellular-phone and hearing-aid interaction: an antenna solution,” IEEE Antennas and Propagation Magazine, Vol. 50, No. 3, pp. 51–65, June 2008. [48] Schmid, G., et al., “High-resolution numerical model of the middle and inner ear for a detailed analysis of radio frequency absorption,” Phys. Med. Biol., Vol. 52, pp. 1771–1781, 2007.

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[49] McIntosh, R.L., et al., “Assessment of SAR and thermal changes near a cochlear implant system for mobile phone type exposures,” Bioelectromagnetics, Vol. 29, pp. 71–80, 2008. [50] Whittow, W., et al., “Specific absorption rates in the human head due to circular metallic earrings at 1800 MHz,” Proceedings of the IEEE Loughborough Antennas and Propagation Conference, pp. 277–280, April 2007. [51] Mason, P.A., et al., “Effects of frequency, permittivity, and voxel size on predicted specific absorption rate values in biological tissue during electromagnetic-field exposure,” IEEE Transactions on Microwave Theory and Techniques, Vol. 48, pp. 2050–2058, Nov. 2000. [52] Gedes, L.A., and Baker, L.E., Principles of Applied Biomedical Instrumentation, Third Edition, New York: Wiley, 1989. [53] Chou, C.K., et al., “Absence of radiofrequency heating from auditory implants during magnetic resonance imaging,” Bioelectromagnetics, Vol. 16, pp. 307–316, 1995. [54] Comité Européen de Normalisation (CEN), “prEN45502-5: Active implantable medical devices—Part 2-5: Particular requirements for cochlear implant systems (under development),” Prepared by CEN Technical Body: CEN/CENELEC Joint Working Group on Active Implantable Medical Devices (CEN/CLC/JWG AIMD), 2005. [55] Shoji, H., et al., “Thermotherapy with metallic stent heated by external magnetic excitation,” IEEE Transactions on Magnetics, Vol. 41, No. 10, pp. 4167–4169, Oct. 2005.

CHAPTER 8

Worldwide Standardization and Guideline Discrepancies David A. Sánchez-Hernández

8.1

Introduction Although comforting statements regarding human safety relative to electromagnetic field exposure under the guideline limits are commonplace for several national and international governmental agencies as well as for some scientific committees, health organizations, and councils worldwide, it is also true that some discrepancies do exist between the diverse established guidelines, standards, and regulations. The inherent differences in determining safety limits between the European Council recommendation and the U.S. recommendation before partial harmonization was achieved in 2006 [1] are extremely well explained in [2], and their difference in the concept of mass or time averaging as well as thermal threshold has undoubtedly lead to differences between their implementation as regulations. ANSI’s original establishment in 1966 of 10 mW/cm2 of incident power density as the guideline for human exposure to microwave fields was modified in 1974 and 1982, while joint ANSI/IEEE has also slightly changed its guidelines for evaluation of exposure in 1991 (to incorporate the “uncontrolled” exposure scenario with an additional safety factor of 5) and 1999. ANSI/IEEE guidelines of 1999 were also slightly different from the guidelines adopted by the FCC in 1996, which made use of some recommendations by the nongovernmental National Council on Radiation Protection and Measurements. ANSI/IEEE also made some partial amendments in 2002, 2003, 2004, and 2005. ICNIRP published its guidelines for limiting exposure to alternating electromagnetic fields up to 300 GHz in 1998, but this was really a revision of previous publications of 1984, 1987, 1991, and 1993. Today, the field exposure limits (W/m2) for ICNIRP and IEEE still differ, as depicted in Table 8.1, not only in the maximum level specified (100 W/m2 for IEEE and 50 W/m2 for ICNIRP in occupational or controlled environments), but also in the frequency at which these peak values are reached (2,000 MHz for ICNIRP and 3,000 MHz for IEEE in controlled environments) [3]. There are other recommendations such as those provided by the U.K. National Radiological Protection Board in 1993 [4] which also evidence some discrepancies to both ANSI/IEEE and ICNIRP. Other standards worldwide also show some discrepancies regarding the most appropriate evaluation technique,

207

61

61

2000– 3000

3000– 5000

0.20

0.20 10

10 —

—

—

27.5

—

—

—

0.0729

10

10

fM/200

2

Power density 2 (W/m )

30

30

30

30

137

137

3√fM

61

0.2

B-field ( T)

0.36

0.36

0.45

0.45

IEEE C95.1—2005

10

50

50

—

—

—

61.4

—

—

—

0.163

100

fM/40

fM/40

10

19.63/ fG1.079

6

6

6

Power E-field H-field Power Averagdensity (V/m) (A/m) density ing time 2 2 (W/m ) (W/m ) (min.)

0.008√fM 0.01√fM fM/40

0.16

Averaging E-field H-field time (min.) (V/m) (A/m)

Notes: E-field and H-field should be computed as the RMS value of the field strength (|E|2, |H|2); Power density value matches with the RMS equivalent plane wave power density; fM = frequency in MHz; fG = frequency in GHz.

0.16

0.16

1.375√fM 0.0037√fM 0.0046√fM fM/200

2

400– 2000

0.92

0.73

28

100–400

H-field (A/m)

IEEE C95.1—2005 E-field (V/m)

ICNIRP 1998

H-field (A/m)

Power density 2 (W/m )

ICNIRP 1998

B-field ( T)

Occupational Exposure (People in Controlled Environments)

General Public Exposure

Plane Wave Exposure Limits at ICNIRP and IEEE

E-field Frequency (V/m) (MHz)

Table 8.1

208 Worldwide Standardization and Guideline Discrepancies

8.1 Introduction

209

measurements settings, time-averaging, mass-averaging, partial-body exposure limits, or even which parts of the body wherein limits have to be either relaxed or restricted. Even in the specific recommendations the different guidelines differ; for instance, ICNIRP specifically recommends that people wearing metallic implants inside their body should be assessed when occupationally exposed to high electromagnetic field for the potential to exceed allowable localized SAR limits. The grade of disagreement turns into a real problem when regulations worldwide are studied. Likewise, despite numerous statements and fact sheets [5–10] reassuring the validity of ICNIRP limits to ensure human safety, diverse standards worldwide intended to evaluate compliance to these limits show some discrepancies. Governments and intergovernmental agencies are putting pressure on their standardization bodies to harmonize and produce evaluating standards in order to gain tools for risk assessment and communication to public, which in turn is forcing these bodies to have a high workload. In return, some standards are withdrawn after a few years, as in Hungary or Australia [11, 12], and governments throughout the world have established stringent limits on the exposure levels to electromagnetic fields to those recommended by ICNIRP and are also forcing operators to produce substantial evidence that their current operation produces exposure levels below these limits through simulated values and measured campaigns. WHO has issued a statement whereby it does not recommend lowering current ICNIRP limits without substantial evidence of potentially harmful effects at those levels, which has not been achieved to date according to CSTEE [6], since this could diminish the credibility of exposure standards without really any established hazard but rather on arbitrary and inappropriate statements. In the United Kingdom, France, Spain, Australia, Switzerland, Italy, and some other countries, operators are force to present exposure predictions prior to installation of new sites, and a posteriori measurements have to be performed as well for final approval. There is, however, a difference between exposure guidelines—mainly used to specify harmful limits and safety factors for maximum permissible exposure—and conformity assessment tests. Conformity assessment is typically performed via tests following basic, product or put-into-service standards. Standards are aimed to aid the performance of conformity tests, which allows for proper standardization. Conformance to guidelines is then tested for equipment or installations, and manufacturers can then add conformance signs and seals to their products. Standardization is performed by diverse bodies worldwide. On the EMF scenario there are eight important standardization committees: ICES TC95 and TC34 in the United States, CENELEC TC106x and ETSIT TC Safety in the EU, ARIB in Japan, TTAS in Korea, and IEC TC106 and ITU-T at international level. In 2007 the ITU-T committee organized a workshop [13] in order to maintain dialogue between the various organizations active within the EMF health effects domain as well as to increase understanding and alignment, and reduce potential duplication of standardization efforts. Particular emphasis was placed on the diverse methods and approaches currently employed, with examples of application in real life, and support to developing countries in establishing national regulations concerning radiation protection.

210

Worldwide Standardization and Guideline Discrepancies

There is a general consensus among standardization bodies to avoid establishing recommendations on limiting guidelines. Some low-power exclusion clauses in some IEC standards may be considered to be an exception, yet they are thought more as an exclusion-from-testing action which in practice acts as an attestation of conformity assessment. The nonexistence of these clauses in other standards, however, is a source of conflict and a clear divergence. Other divergences have to do with the frequency range. Not all standards cover the same frequency ranges. High frequency concerns have been coexisting with very low frequency ones, and there has been a tendency to provide for separate standards. There is, however, a recent trend to unify the standards and avoid this separation of high and very low frequency [14, 15]. Two clear examples of this trend are (1) the publication in 2008 of the EN 62311:2008 Standard for the assessment of electronic and electrical equipment related to human exposure restrictions for electromagnetic fields (0 Hz–300 GHz), which replaces EN 50392:2004 and conforms to IEC 62311:2007, and (2) the work of ICES TC95 on the revision of the IEEE C95.1-2005 Standard for Safety Levels with Respect to Human Exposure to Radio Frequency Electromagnetic Fields, 3 kHz to 300 GHz, which will be replaced by the IEEE 2007 C95.1-200X, Standard for Safety Levels with Respect to Human Exposure to Electric, Magnetic, and Electromagnetic Fields, 0 to 300 GHz.

8.2

Extremities and Mass- and Time-Averaging A good example of the differences in the standards is the equivalent tissue liquid parameters of the European standard EN50361 [16], where the highest sigma producing the highest SAR is employed and a third-order polynomial interpolation function is used to avoid changing the liquid 1g and 10g averaging, and that of IEC62209-1 [17], where the highest sigma from 1g and 10g averaging is selected with more individual frequencies and a simple interpolation scheme. Although only a maximum of 5% difference in peak SAR averaged over 10g is expected, the simple fact that differences exist is not easily explained. Another difference is body part-, mass-, and time-averaging. While a 1g mass-averaging was proposed in the U.S. standard until 2004 [18], a 10g mass-averaging is proposed in the European Union [19], and a 100g mass-averaging was proposed in the United Kingdom by the National Radiological Protection Board for specific parts of the body such as the legs and limbs [4]. Similarly, 15 to 30-min time-averaging was proposed in the United States until 2004, while the European Union uses 6-min averaging periods. Likewise, specific values are differentiated for the head and trunk (2 W kg 1) in the E.U. standard with respect to the limbs (4 W kg−1) as in the ICNIRP guidelines, while in the United States until 2004 the hands, wrists, feet, ankles, and pinna (4 W kg−1) [20] receive special attention for the maximum limits and its geometry, respectively. The discrepancies between the U.S. standard and ICNIRP, adopted by most countries in the European Union, Japan, Australia, and others have been partially minimized with the recent revision of the U.S. standard [1, 21], whereby a 2 W kg−1 limit applies for any 10g of body tissues (i.e., head tissues), while a higher limit of 4 W kg−1 is used now for the pinna and the extremities’ tissues including arms, legs, elbows, and knees. Some formulas are now employed in the United States for the

8.2 Extremities and Mass- and Time-Averaging

211

averaging time in the frequency range from 5 to 300 GHz (general public) or 3 to 300 GHz (controlled environments), which is different from ICNIRP (6 minutes except above 10 GHz, where a different formula than the IEEE ones applies). These small differences that remain, for instance, have already been published to represent a divergence between the two standards, rather than a harmonization, particularly the one related to the pinna treated as an extremity, which has been reported to increase 2.5 to 16 times radiated powers allowed in the United States until 2004 and up to two times that permitted under ICNIRP guidelines [22, 23]. The standard in Canada, on the other hand, includes the neck with the same limits as the trunk but specifies noncompulsory restricted limits for the eye “whenever possible.” In Australia and New Zealand, a unique laser and radiofrequency worker eye-sight test examination was proposed [24]. The differences in the treatment for the eye, however, are due to the fact that some papers have identified the eyes to be particularly sensitive organs due to their proximity to the surface of the head and the relatively low levels of blood flow when compared to other regions of the body [25], which stresses their vulnerability as they have a tendency to accumulate damage and cellular debris [26]. Additionally and until the Australian standard was replaced by the ICNIRP guidelines in 2003 [27, 28], an exposure limitation to 8 hours was also employed [29]. Discrepancies between standards have also been identified and dealt with by the diverse committees. As an example, the CENELEC TC 106x noted a discrepancy between CEN TC114 standard EN 12198-1 and the ICNIRP Guidelines, the Council Recommendation 1999/519/EC and all standards elaborated in TC106x such as EN 12198-1, which allows for frequencies below 100 kHz averaging of 1 second. The advice given by the CEN experts is that EN 12198-1 is considered neither an emission standard nor an exposure assessment standard, but a classification standard giving advice to manufacturers of machines or components whether or not a deeper assessment is necessary. The 1s averaging statement in EN 12198-1, which was published before the ICNIRP guidelines in 1998, was based on INIRC/IRPA guidelines from around 1993, the predecessor of the ICNIRP guidelines from 1998. Also in these years, measurement equipment with intrinsically shorter averaging times of below 1s was not commercially available. Another good example of internal homogenization is the agreement of the British National Committee to endorse the proposal of the Greek National Committee (i.e., to submit the English version of the two Greek standards ELOT 1422-1:2005 and ELOT 1422-2:2005 “Radiocommunication antenna collocation” as reference documents for internal TC106X procedures). Currently, several international leading committees regarding EMF, including IEC/TC106, CENELEC TC106x, IEEE SCC39 (ICES) TC34 and TC95, CISPR SC A, and ETSI TC Safety are working in parallel on the development of diverse standards related to handheld and body-mounted wireless communication devices, numerical methods for evaluating exposure to electric or magnetic fields, household appliances and similar apparatus, short range and/or low power radio devices, industrial induction heating equipment, ground based air traffic management equipment, equipment in the electrolysis industry, EMF generated by HV switchgear assemblies and HV/LV prefabricated substations, EMF by broadcast transmitters, EMF of lighting equipment, electronic article surveillance (EAS), radio frequency identification (RFID) and similar applications, pacemakers, active

212

Worldwide Standardization and Guideline Discrepancies

implants, equipment in the railway environment, welding and allied processing equipment, domestic appliances, antennas for electroexplosive devices, among others. These works, however, are currently having some boomerang effects, and closer coordination is sought by the governing bodies of these committees. Even some already published standards which were thought to be harmonized are now being proposed for review. This is the case of EN50400 “Basic standard to demonstrate the compliance of fixed equipment for radio transmission (110 MHz – 40 GHz) intended for use in wireless telecommunication networks with the basic restrictions or the reference levels related to general public human exposure to radio frequency electromagnetic fields, when put into service” and EN50401 “Product standard to demonstrate the compliance of fixed equipment for radio transmission (110 MHz – 40 GHz) intended for use in wireless telecommunication networks with the basic restrictions or the reference levels related to general public human exposure to radio frequency electromagnetic fields, when put into service,” for which the German and Irish committees have expressed concerns about possible small discrepancies (A-deviations) with their national regulations and standards. While A (or small) deviations are allowed within the European Union and do not rule out EU harmonization, they are a clear source of conflict for the future. Other examples are the proposed withdrawal and replacement of EN 50357 by IEC/EN 62369, EN 50371 by IEC 62479, or EN 50392 by IEC/EN 62311, or the modification of EN50383 to conform to IEC 62209.

8.3

Volume Averaging Volume averaging is yet another source of discrepancy, with ICNIRP recommending field values to be averaged over the volume occupied by the human body, while a recent CENELEC standard for evaluation of compliance testing of mobile radio base 2 stations [30–32] considers the peak E-field value searched over a vertical 70 × 40-cm surface, which has demonstrated as an excessively conservative approach and thus valid for compliance testing [33]. There are, in fact, differences in calculated safety distances when volumetric averaging is performed when compared to planar averaging, with lower distances when averaging is performed in a volume [34]. With all these differences it is not strange to find contradicting publications that study which of the standards is more conservative, since that strongly depends on the factors associated to the specific exposure situation. In [35], it was demonstrated that for a realistic human body model (NORMAN) and a vertically aligned electric field exposure with no time averaging, NRPB restriction levels provide a conservative estimate of calculated SAR values on the body resonance region, but above 1 GHz they underestimate exposure to SAR. The ICNIRP occupational basic restrictions are more conservative in that region, suggesting an excessive mass averaging for NRPB (100g), despite time averaging being so important when comparing ICNIRP limits to others. The NRPB recommended the adoption of ICNIRP guidelines in the United Kingdom in March 2004. ICNIRP general public basic restrictions and reference levels, however, were not found to be sufficiently conservative in the region approaching 3 GHz and for localized exposure, respectively, as it has also been suggested by [36]. In [35], however, health safety is not threatened since sec-

8.4 Regulations

213

ondary reference levels for the limbs on ICNIRP recommendations (causing the not-conservative problems with just the basic restrictions), based upon currents, provide compliance with basic restrictions on localized SAR averaged over 10g. In the Korean TTA standard [37], which was established in December 2006 and adopted by ITU-T in May 2007, assumes the spatial average of three heights, 1.1m, 1.5m, and 1.7m, the number of basic measurement point, three (one dimension), and that of precise measurement, nine (two dimension). In case of precise measurement the area is within 0.4m (horizontal) by 0.6m (vertical) and the points are placed 0.2m apart at each height [38].

8.4

Regulations When these diverse guidelines and standards worldwide are used to developed regulations, the differences within them grow nearly exponentially since nonscientific issues are also employed openly to determine specific situations. It is not unusual to find exceptions to limits such us using the concept of the precautionary principle more profusely than both guidelines and standardization bodies have already used. It is neither the aim of this book nor the expertise of its authors to discuss the precautionary principle or nonscientific issues, and in this section we will simply outline a few encountered differences so as to compile them for the reader. The Canadian [39], Australian (until 2003) [40], and Israeli [41] regulations do account for BS activity by using a long-term average value for each location, which is obtained by continuously recording the number of simultaneous active time slots for a single carrier during 24 hours. As expected, a diurnal signal pattern was observed due to the human activity, but a monitoring 24-hour period was required for each location. Such a surveying time is not practical and yet does not guarantee for complete assessment. Therefore an additional protection factor based on the BS activity is proposed for both the broadband and the narrowband procedures. Instead of these long surveying periods the regulation in Luxemburg [42] relies on random inspections and measurements before granting operating licenses, yet no traffic considerations are accounted for. More severe limits to those of ICNIRP are in force in Italy [43], wherein 20 V/m is the limit for generic areas accessible to public, which is brought down to 6 V/m should average daily permanence time be expected to exceed 4 hours. The differences are even larger when reviewing the regulations of eastern European countries, which have a wide range of different V/m limits, EIRPs, conception of sensitive areas, and even safety distances [44, 45]. After the inclusion in June 2002 of vibration (2002/44/EC) and in February 2003 of noise (2003/10/EC) as physical agents over which risk assessment has to be performed to protect workers within the European Union, in 2004 electromagnetic field exposure was classified in the EC as a risk with the Common Position of the European Council 10/2004 and the EU Physical Agents (EMF) directive (2004/40/EC) [46], therefore altering previous schemes for use, application, and worker/consumer protection regulations. The new directive of the European Parliament and Council on the minimum health and safety requirements regarding the exposure of workers to the risks arising from physical agents (electromagnetic fields and waves) was then the third out of four proposed physical agents. The approval of

214

Worldwide Standardization and Guideline Discrepancies

the EMF directive is indeed a very important change and, although intended to harmonize EU EMF-related issues, has stimulated current legislative heterogeneities. A good example is the German legislation by which an employers’ liability insurance association commits network providers to specify safe distances for their base station antennas in the presence of adult (100 kg) and adolescent (49 kg) workers in order to keep the occupational exposure below the limits given by the guidelines [47, 48], and it turns out that the whole-body SAR of the 42-kg body model is the limiting factor for the compliance distance [49]. Under this German legislation, a unique labeling within the European Union is applied to base stations whose occupational safe distance R in the main direction exceeds 50 cm. In all other directions safety distances of R/2 come into force. Since most European countries already have risk management regulation for working environments, the new directive will provide the expected harmonization when fully into force by the end of April 2008. Unfortunately, a 4-year delay after April 30, 2008 was approved by the EU parliament, despite transposition having been already performed in Austria, Slovakia, Czech Republic, Slovenia, and Italy, among others. A detailed study of EMF regulation heterogeneities without the recent IEEE amendments [1] can be found in [50], which is represented by Figures 8.1 and 8.2. In Italy, for instance, in addition to the general limits, precautionary measures have to be applied in buildings for periods of use greater than 4 hours. In Spain, there are some “sensitive” areas wherein limits have to be carefully controlled with measurements each year and reported to the government. At 900 MHz, the limits of the electric field strength vary between 0.6 and 112.5 V/m, while at 1,800 MHz, the range is from 0.6 to 194 V/m. For the frequency range from about 20 MHz to some hundred megahertz, the variation of limits is approximately restricted to about one order of magnitude [50], which could reflect a 10000

Electric Field Strength (V/m)

NRPB 93 IEEE 99 ÖNORM 92

1000

NEL 97 CENELEC 95 ICNIRP 98

100 ITALY 1 98

AS 98

10 ITALY 2 98

HUN 86 NISV 99

1

SVorGW98 0.1 0.1

1

10

100

1000

10000 100000 1000000 10000000

Frequency (MHz)

Figure 8.1 E-field limits standardized and/or regulated in diverse countries. (Available at http://www.cost281.org/activities/Short_term_mission.doc.)

ICNIRP 98 ÖNORM 92 IEEE 99 NRPB 93 CENELEC 95 ITALY 1 98 ITALY 2 98 NISV 99 NEL 97 AS 98 SVorGW98 HUN 86

8.4 Regulations

215

1000

NEL 97

Electric Field Strength (V/m)

ICNIRP 98 ÖNORM 92

NRPB 93 IEEE 99

CENELEC 95 100

ITALY 1 98

10 ITALY 2 98

AS 98 HUN 86

NISV 99

1

ICNIRP 98 ÖNORM 92 IEEE 99 NRPB 93 CENELEC 95 ITALY 1 98 ITALY 2 98 NISV 99 NEL 97 AS 98 SVorGW98 HUN 86

SVorGW98 0.1 100

1000 Frequency (MHz)

10000

Figure 8.2 E-field limits standardized and/or regulated in diverse countries (100 MHz to 10 GHz detail).(Available at http://www.cost281.org/activities/Short_term_mission.doc.)

better understanding of dosimetry in this frequency range. Around 300 to 400 MHz, there are again increased differences between different regulations, motivated on the reduced coupling to the human body of the external fields. In terms of electric field levels, the variation is about 20% to 30% [50]. Among the different initiatives to harmonize these regulatory heterogeneities it is worth mentioning the European Information System on Electromagnetic Fields Exposure and Health Impacts (EIS-EMF) Project developed by the European Joint Research Centre (JRC) at Ispra (Italy) on behalf of Directorate General of Health and Consumer Protection (SANCO) of the European Union, which has recently finished and can be used as an important tool in support of EU policies and risk communication. Its basic component is a network of European Competent Authorities on EMF and Health. The members of the network have already used the EIS-EMF tools to exchange information and assess strategies on how information on EMF exposure can be used in national policy making and in risk communication. Authorities from EU member states, the expert community, and other stakeholders have provided strong support and feedback, and their ample participation in the JRC initiatives may lead to future coordinated activities. An example of an initiative which has not been coordinated is the recent decision of the German government to promote low-radiation mobile phones. A phone with a specific absorption rate (SAR) of 0.6 W/Kg (three times lower than the one recommended by ICNIRP as a limit) or less, averaged over 10g, can now be labeled as an environmentally friendly product in Germany. The introduction of a “Blue Angel” label is seen as a positive step for the phone industry and the consumer by the German government, but less than a year after that Siemens announced the reallocation of its phone manufacturing units in Asia. The German label is designed to help those who “have questions about possible health hazards from mobile phone radiation but do not want to do without such

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devices,” according to the official explanation. The German Federal Radiation Protection Office has also endorsed the new label with the goal of minimizing possible risks through precautionary policies. Without coordinated activities, the engineering work and research gets more complicated. Yet, even higher demanding specifications are put onto engineers desks for obtaining less SAR on their integrated antenna designs but at the same time in less and less space and also with more required bandwidth, yet relaxing VSWR requirements, with current commercial prototypes being approved with –6-dB input return loss as VSWR bandwidth criterion. Already existing differences, however, do not help scientists (biomedical, engineers, physicians, etc.) properly address the problem of public opinion, which clearly sees these discrepancies as a result of unclear and limited knowledge about the topic, sometimes turning into skepticism towards government agencies or even research institutes—or in other words, a lack of trust.

References [1] IEEE Standard C95.1-2005, “IEEE Standard for Safety Levels with Respect to Human Exposure to Radio Frequency Electromagnetic Fields, 3 KHz to 300 GHz,” American National Standard (ANSI), 2006. [2] Lin, J.C., “Safety standards for human exposure to radio frequency radiation and their biological rationale,” IEE Microwave Magazine, pp. 22–26, Dec. 2003. [3] McIntosh, R.L., Anderson, V., and McKenzie, R.J., “A Numerical Evaluation of SAR Distribution and Temperature Changes Around a Metallic Plate in the Head of a RF Exposed Worker,” Bioelectromagnetics, Vol. 26, pp. 377–388, 2005. [4] McKinlay, A.F., Allen, S.G., Dimbylow, P.J., Muirhead, C.R., and Saunders, R.D., “Restrictions on human exposure to static and time-varying electromagnetic fields and radiation,” Document of the National Radiological Protection Board, Vol. 4, No. 5, 1993. [5] Scientific Committee on Toxicity, Ecotoxicity and the Environment (CSTEE), “Opinion on Possible Effects of Electromagnetic Fields (EMF), Radio Frequency Fields (RF) and Microwave Radiation on Human Health,” Brussels, C2/JCD/csteeop/EMF/RFF30102001/D(01), Oct. 2001. [6] Scientific Committee on Toxicity, Ecotoxicity and the Environment (CSTEE), “Opinion of the CSTEE on Effects of Electromagnetic Fields on Health,” Brussels, C2/AST/csteeop/EMF 24092002/D(02), Sept. 2002. [7] Scientific Committee on Toxicity, Ecotoxicity and the Environment (CSTEE), “Opinion of the CSTEE on Effects of Electromagnetic Fields on health-Appendix to the Opinion Expressed on 24 September 2002,” Brussels, C2/VR/csteeop/EMF 17122002/D(02), Dec. 2002. [8] World Health Organization, “Establishing a dialogue on risks from electromagnetic fields,” World Health Organization, Geneva, Switzerland, 2005. [9] World Health Organization, “The international EMF projects: Progress report 2003–2004,” World Health Organization, Geneva, Switzerland, 2004. [10] World Health Organization Fact Sheet no. 374, “Electromagnetic fields and public health base stations and wireless technologies,” May 2006. [11] Hungarian Standard MSZ 16260-86, “Safety levels of high frequency electromagnetic fields (30 kHz – 300 MHz),” Hungary, 1986 (withdrawn in 2004). [12] AS/NZS 1998. 2772, Part 1 1998, Interim Australian / New Zealand Standard – Radiofrequency Fields Part 1: Maximum Exposure Levels – 3 kHz to 300 GHz, Standards Australia, 1 the Crescent, Homebush NSW 2140 Australia. Standard withdrawn in 2003.

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[13] ITU-T Workshop, “Human exposure to electromagnetic fields (EMFs),” Geneva, Nov. 2007, available at: http://www.itu.int/ITU-T/worksem/emc-emf/200711/index.html. [14] Kavet, R., et al., “Recent advances in research relevant to electric and magnetic field exposure guidelines,” Bioelectromagnetics, Vol. 29, pp. 499–526, 2008. [15] Wood, A.W., “Extremely low frequency (ELF) electric and magnetic field exposure limits: rationale for basic restrictions used in the development of an Australian standard,” Bioelectromagnetics, Vol. 29, pp. 414–428, 2008. [16] European Committee for Electrotechnical Standardization (CENELEC) EN50361:2001, “Basic standard for the measurement of specific absorption rate related to human exposure to electromagnetic fields from mobile phones (300 MHz – 3 GHz),” Sept. 2001. [17] IEC 62209-1, Human Exposure to Radio Frequency Fields from Hand-held and Body-Mounted Wireless Communication Devices, Part 1: Procedures to determine the Specific Absorption Rate (SAR) for Hand-held Devices Used in Close Proximity to the Ear (frequency range of 300 MHz to 3 GHz), February 2005 [18] IEEE Standard C95.1-1991 (Ed. 1999), “IEEE Standard for Safety Levels with Respect to Human Exposure to Radio Frequency Electromagnetic Fields, 3 KHz to 300 GHz,” American National Standard (ANSI), 1999. [19] European Council, “Council Recommendation of 12 July 1999 on the limitation of Exposure of the General Public to Electromagnetic Fields (0 Hz – 300 GHz),” Official Journal of the European Communities, L199, pp. 59–70, July 30, 1999. [20] IEEE Standard for safety levels with respect to human exposure to radio frequency electromagnetic fields, 3 kHz to 300 GHz, “Amendment 2: Specific absorption rate (SAR) limits for the pinna. Std. C95.1b-2004 Edition,” New York, NY: The Institute of Electrical and Electronics Engineers (IEEE), Inc. [21] IEEE Standard 1528a-2005, “IEEE Recommended Practice for Determining the Peak Spatial-Average Specific Absorption Rate (SAR) in the Human Head from Wireless Communications Devices: Measurement Techniques Amendment 1: CAD File for Human Head Model (SAM Phantom),” February 24, 2006. [22] Gandhi, O.P., and Kang, G., “Some present problems and a proposed experimental phantom for SAR compliance testing of cellular telephones at 835 and 1900 MHz,” Physics in Medicine and Biology, Vol. 47, pp. 1501–1518, 2002. [23] Gandhi, O.P., and Kang, G., “Inaccuracies of a plastic pinna SAM for SAR testing of cellular telephones against IEEE and ICNIRP safety guidelines,” IEEE Transactions on Microwave Theory and Techniques, Vol. 52, pp. 2004–2012, 2004. [24] Standard Association of Australia Standard House, “Maximum exposure levels— radiofrequency radiation—300 kHz to 300 GHz,” AS 2772-1985, 1985. [25] Bernardi, P., Cavagnaro, M., Pisa, S., and Piuzzi, E., “SAR distribution and temperature incresase in an anatomical model of the human eye exposed to the field radiated by the user antenna in a wireless LAN,” IEEE Transactions on Microwave Theory and Techniques, Vol. 46, No. 12, pp. 2074–2082. [26] Dimbylow, P.J., “FDTD calculations of the SAR for a dipole closely coupled to the head at 900 MHz and 1.9 GHz,” Physics in Medicine and Biology, Vol. 38, pp. 361–368, 1993. [27] “Radiocommunications Electromagnetic Raditaion - Human Exposure Standard 2003,” Australian Communications Authority, March 2003. [28] “ARPANSA Radiation Protection Standard No. 3: Maximum Exposure Levels to Radio-Frequency Fields—3 kHz to 300 GHz,” Australian Radiation Protection and Nuclear Safety Agency, 2003. [29] Fleming, A.H.J., Lubinas, V., and Joyner, K.H., “Calculation of electric fields in tissue near metallic implants,” Proceedings of the Asia-Pacific Microwave Conference, pp. 229–232, 1992. [30] CENELEC Standard EN 50383, “Basic standard for the calculation and measurement of electromagnetic field strength and SAR related to human exposure from radio base stations

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[31]

[32]

[33]

[34]

[35] [36]

[37] [38] [39]

[40]

[41] [42]

[43]

[44] [45] [46]

[47]

and fixed terminals stations for wireless telecommunications systems (110 MHz – 40 GHz),” Dec. 2002. CENELEC Standard EN 50384, “Product standard to demonstrate the compliance of radio base stations and fixed terminal stations for wireless telecommunication systems with the basic restrictions or the reference levels related to human exposure to radio frequency electromagnetic fields (110 MHz–40 GHz),” Dec. 2002. CENELEC Standard EN 50385, “Product standard to demonstrate the compliance of radio base stations and fixed terminal stations for wireless telecommunication systems with the basic restrictions or the reference levels related to human exposure to radio frequency electromagnetic fields (110 MHz–40 GHz),” Dec. 2002. Bernardi, P., Cavagnaro, M., Cristoforetti, L., Mazzurana, M., Pisa, S., and Piuzzi, E., Pontalti, R., and Sandrini, L., “Evaluation of human absorption in the near field of a BTS antenna,” Proceedings of the IEEE International Symposium on Microwave Theory and Techniques, pp. 1449–1452, 2004. Joseph, W., and Martens, L., “The influence of the measurement probe on the evaluation of electromagnetic fields,” IEEE Transactions on Electromagnetic Compatibility, Vol. 43, No. 2, pp. 339–349. Dimbylow, P.J., “Fine resolution calculations of SAR in the human body for frequencies up to 3 GHz,” Physics in Medicine and Biology, Vol. 47, pp. 2835–2846, 2002. Martínez-Búrdalo, M., Martín, A., Anguiano, M., and Villar, R., “On the safety assessment of human exposure in the proximity of cellular communications base-station antennas at 900, 1800 and 2170 MHz,” Physics in Medicine and Biology, Vol. 50, pp. 4125–4137, 2005. Telecommunications Technology Associations, “Recommendation on measurement method of exposure to base stations,” TTAS.KO-06.0125, Seongnam City, Korea, 2006. Kim, B.C., et al., “Methods of evaluating human exposure to electromagnetic fields radiated from operating base stations in Korea,” Bioelectromagnetics, Vol. 29, pp. 579–582, 2008. Environmental Health Directorate, Health Protection Branch, Canada, Safety Code 6, “Limits of human exposure to radiofrequency electromagnetic fields in the frequency range from 3 KHz to GHz,” 99-EHD-237, 1991. “Human Exposure to Radiofrequency Electromagnetic Energy,” Information for licensees or operators of radiocommunications transmitters: Evaluation of compliance with the ACA standard, Australia, Sept. 2000. “Israeli Non-Ionizing Radiation Law,” (5766), Reshumot, Jan. 2006. Grand-Duche de Luxembourg, Ministère de l’Environnement and Ministère du Travail et de l’Emploi, “Normes les plus strictes en Europe en matière de radiations en provenance des émetteurs de téléphonie mobile,” Luxemburg, Dec. 2000. “Decreto Ministero dell’Ambiente 10/09/1998 n. 381. Reglamento recante norme per la determinazione dei tetti di radiofrequenza compatibili con la salute umana. Gazzeta Ufficiale della Repubblica Italiana,” Serie Generale n. 257, Nov. 1998 (in Italian). Ordinance 61/284 off the Prime Minister, “Factors Harmful for Health in Work Environment,” Poland, 1996 (modified by 124/789 in 1997 and 8/108 in 2000). Ordinance 63/2004 of the Ministry of Health, Social and Family Affairs, “Limits of EMF exposure between 0 Hz- to 300 GHz,” Hungary, July 2004. “Directive 2004/40/EC of the European Parliament and of the Council of 29 April 2004 on the minimum health and safety requirements regarding the exposure of workers to the risks arising from physical agents (electromagnetic fields) (18th individual Directive within the meaning of Article 16(1) of Directive 89/391/EEC,” Official Journal of the European Union, L 159 of 30 April 2004. Corrigenda in Official Journal of the European Union, L 184 of 25 May 2004. BGR B11, BG-Regeln, “Elektromagnetische Felder,” Hauptverband der gewerblichen Berufsgenossenschafen, April 2001 (in German).

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[48] BGV B11, Unfallverhütungsvorschrift “Elektromagnetische Felder,” Hauptverband der gewerblichen Berufsgenossenschafen, March 2001 (in German). [49] Hansen, V., Bitz, A., Streckert, J., and El Ouardi, A., “A numerical approach for efficient calculation of human exposure in front of base station antennas,” URSI General Assembly New Delhi, October 2005. [50] COST 244bis Final Report, “Biomedical effects of electromagnetic fields,” November 2000.

CHAPTER 9

Medical Applications of High Frequency Electromagnetic Energy Pedro J. Silva

9.1

Electromagnetic Therapy and Hypothermia In this chapter, we present a partial summary of the latest developments on therapeutic applications of high frequency electromagnetic radiation to medicine (here high frequencies means from hundreds of megahertz to 10 gigahertz). First of all, we should note that medical applications in electromagnetic radiation at this high frequency regime are a dynamic and ever-changing area of knowledge, where new applications are almost everyday developed and tested all over the world. In fact, these types of therapies are presently a major subject of interest and research, due to their enormous potential to improve human health. The electromagnetic emissions considered here are nonionizing, unlike other higher frequency radiations used in medicine. Therapies based on electromagnetic radiation usually rely on the ability of the radiated photons to heat up the sample of interaction. The above phenomenon is due to the excess of incoming energy that simply cannot be accommodated into the sample, and therefore is transformed into heat which increases the temperature. Presently, it is not clear if there are aspects of the electromagnetic interaction that may be used to develop medical applications other than the thermal treatments. Nevertheless, there is increasing concern and interest in power absorption in human subjects, including interactions with the nervous system, and cellular and molecular alteration and/or destruction that could even affect genetic structure (see, for example, [1]). In fact, there are in vivo experiments that signal directs effect on microwave regimes, although there are ambiguities that preclude a clear distinction between thermal and possible nonthermal effects. Unambiguous results are obtained from in vitro experiments where cellular endpoints are affected; in particular we have calcium biding, proliferations, and ligand-receptor-mediated mechanism (see [2] for more information). In this chapter we will concentrate only on thermal phenomenology, due to an almost lack of development on other aspects. Given the nature of the vast majority of existing medical applications based on nonionizing electromagnetic radiation, these therapies are normally called thermal therapy. Thermal therapies naturally are divided into hyperthermia and thermal ablation, depending on the temperature increase produced locally on the sample.

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The term hyperthermia is normally applied to therapies with ranges of temperature between 41ºC to 45ºC, while thermal ablation corresponds to temperature above 45ºC. One of the main advantages of these therapies is its minimally invasive nature, when compared to more standardized therapies like surgery. Here we are thinking mostly, but not only, in areas like benign disease and cancer, as well as reshaping of tissues or repair of localized injuries. Nevertheless we should keep in mind that in general these electromagnetic therapies are to be used complementarily with other therapies, as is the usual situation in medicine. (See Figure 9.1 for an example of a thermal therapy as assisted surgery.) To understand its capabilities and domain of application we will first briefly discuss biological response to electromagnetic radiation and then have a word on potential hazards and risks. After this preliminary discussion, we will describe some of the latest and more promising applications to medicine. Interested readers who would like to learn more on this subject are referred to the existing literature, which is rich and too long to be reproduced here. Nevertheless, we point out, for example, the following handbooks on biological effects and medical applications that should work as a starting point [4–10]. 9.1.1

Biological Response and Risk

The absorption of electromagnetic waves by human subjects depends on the field at the local tissue being exposed that is measured as the specific absorption rate (SAR). The characteristic SAR of a sample depends on its permittivity and dielectric constant, which is a function of the frequency and amplitude of the field. The key phenomenon in high frequency radiation is relaxation. For example, various proteins and cellular membranes show this phenomenon around hundreds of megahertz, while water content in human tissue shows relaxation around 10 GHz at body temperature. In contrast, cancerous tissue, due to its high vascular capability, shows higher permittivity than surrounding healthy tissue, giving up to a 40% increase.

Figure 9.1 IEEE.)

Picture of a surgery with FR technology. (Reproduced from [3] with permission from

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At the molecular/biological level, it is clear that heat has its consequences since an increased temperature corresponds to an increase of molecular motion, which accelerates molecular reactions that may unbalance generic metabolic process that eventually may drive the tissue to unstable behavior or even destruction—that is, in fact, the desiderate end of thermal ablation. Another important point in human morphology is that heat causes many different reactions in live tissue, corresponding to different metabolic responses or activities, among which the increment of blood perfusion is the more efficient vehicle to dissipate heat. Tumors are in general badly donated with blood supply due to their chaotic cellular structure, making them easier to heat up than their host tissue. On the other hand, heat balance on the body is restored by this excess of blood flow that in humans is particularly well developed. This implies that a rise in the body temperature compromises the cardiovascular system and therefore creates potential risk to elderly people with a substantial probability of coronary thrombosis [11]. The interaction with the nervous system has been studied but no concluding results are published yet. It has been shown that excitation on microwave regimes produces analgesics results [12], and there is literature on the effects of intermediate and low level EM radiation that shows that a low SAR of about 2 W/Kg in particular circumstances indeed affects the nervous system [13–16]. Nevertheless, more experiments are needed with a better defined methodology of investigation to compare and validate results. Other preliminary results on general effects have been reported. For example, SAR above 15 W/Kg seems to produce malformation if there is an associated increase of temperature over 5ºC; cataracts can develop at power higher than 100 mW/cm2 around 1 GHz on the eye; and pulse fields may produce stronger effects than continuous waves (see [2, 8, 17, 18]). In any event, it is clear that high frequency electromagnetic (EM) therapy is becoming more accessible and attractive (due to new progress and research) as a minimal noninvasive thermal therapy. However, evaluation on human exposure risk is a difficult task that should be addressed to safely incorporate all this potential to medicine. In particular, heating the human body as a whole, partially or locally, may affect its cardiovascular system and in general its physiology. Again, a rationale for safe regulation that incorporates thermal/electromagnetic interactions needs to be defined to standardize the use of all these potential applications and avoid possible hazards.

9.2

Therapeutic Applications High frequency electromagnetic radiation therapy has increased dramatically in recent years. In fact, this type of therapy is widespread and well documented in cancer treatments, cardiovascular pathologies, some urologic and gastric pathologies, and on treatments related to deep brain stimulation for Parkinson and epilepsy, articulations, liposuction, sleep apnea and snoring, varicose veins, as well as canalization for better absorption of drugs in specific tissues. This list is by no means exhaustive, but represents a significant part of the main trends of investigation and applications to medicine. In what follows, we will review some of the more promis-

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ing therapies that are currently under research either to improve existing protocols or to actually implement them. 9.2.1

Cardiac Treatments

Thermal therapy in cardiac treatments has a long history of development, where the heating up of the cardiac tissue is used as a means of coagulation and/or necrosis for different therapeutic reasons. Here, we concentrate on two different techniques that are currently used in medicine but that are also under research due to its enormous potential. 9.2.1.1

Microwave Balloon Angioplasty (MBA)

Balloon angioplasty is a surgical repair of a blood vessel suffering stenosis. The procedure was originally developed as an alternative to cardiac bypass surgery. The main idea is to insert a balloon-tipped catheter to unblock the vein. Balloons can be produced with diameters from 0.5 to 50 mm or even more, in any working length, with very thin walls. The actual process employs a narrow balloon catheter that is advanced to the site of arterial stenosis by means of an incision in the neck or leg and fed through blood vessels. Then fluid is pumped into the balloon, inflating it to several times its normal diameter to unblock the vein. The enlarged tip quickly compresses the layer of plaque which is clogging the artery leaving a much wider opening for blood flow. Finally, the balloon is deflated and it is withdrawn with the catheter. The MBA version takes advantage of the volume heating property of microwave radiation. The device was first reported by Rosen [19], subsequently studied by Rappaport [20], and clinically tested by Smith, et al. [21] and Nardone, et al. [22]. In short, these balloons used a variety of narrow antennas incorporated within and surrounding a catheter (see Figure 9.2). The design of the antenna is the key to the success of the MBA. A cable-antenna assembly is threaded through the catheter, with the antenna centered in the balloon portion of the catheter. The first MBA devices employed dipoles and small helical antennas. Although the healthy tis-

Figure 9.2 Example of a balloon catheter and microwave delivery system. (Reproduced from [24] with permission from IEEE.)

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sue may still be heated less than the inner plaque surface, it is important to avoid overheating the artery wall, if possible [23]. 9.2.1.2

Microwave Ablation for Arrhythmia

Application of high frequency EM radiation to the treatment of abnormal heart rhythm or some cardiac arrhythmias, such as ventricular tachycardias, supraventricular tachycardia, atrioventricular node reentrant tachycardias, accessory pathways, atrial fibrillation, and atrial flutter, is another example of developments currently under research. In these types of techniques, the resulting ablation reaches a successful rate of about 70% to 95% depending on the heart rhythm disorders [25–29]. The utility of this procedure relies on the fact that all the studied arrhythmias are produced by abnormal focus of electric activity within the heart. The main idea of these treatments is based on the destruction of the tissue that sources the arrhythmia (see [29]). The actual procedure involves making catheters threaded through veins or arteries to the site of the abnormal electrical tissue responsible for the arrhythmia. Catheter ablation is usually performed in conjunction with an invasive diagnostic electrophysiology study, which will identify the origin of abnormal impulse formation [30]. RF ablation operating at frequencies around hundreds of kilohertz to a few megahertz has a big success rate in treating a wide range of cardiac arrhythmias. To be more precise, an electric current is applied between the catheter electrode (∼2.6 mm in diameter) in contact with the endocardium and a rectangular (∼15 cm × 9 cm) dispersive electrode attached at the back of the patient. Microwave power is also used to treat abnormal heart rhythm, especially ventricular tachycardia. Microwave power can ablate tissues at greater depth and across a larger volume heating than lower frequency ablation by using monopole and helical antennas [20]. Lately, microwave power using around 1,000 MHz has been studied to enlarge myocardial lesions in catheter ablation [31, 32], where the microwave energy is deliver via an antenna capable of reaching the ill tissue (see Figure 9.3). In the literature there are numerous articles that confirm the applicability and success of this type of ablation in medicine [33–37]. In particular there are successful studies on open chest surgery on dogs and pigs where the ablation is produced with radiation on the microwave region [38, 39]. Nevertheless some problems remain to be solved, like power loss in the coaxial cable and the lack of a unidirectional antenna to radiate directly into the desiderate tissue and not on vicinity regions. 9.2.2

Urological Pathologies

Benign prostatic hypertrophy (BPH) is one of the most common tumors in men nowadays, and is the most frequent cause of symptoms of urinary obstruction in men over 50 years of age. The prostate is basically a small gland shaped as chestnut that surrounds the urethra immediately below the bladder in males. BPH is a condition in which the prostate gland gradually enlarges and results in a narrowing of the urethra. This may cause bladder obstruction and problems associated with urination. Therapy ranges from watchful waiting to surgery.

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Metallic shaft

Position indicator

Handle Black markers Sliding ring

Flexible sheath

Guide lead

Figure 9.3 The Flex 10 microwave ablation catheter. This device measures 200 mm in total length and is 9 mm in diameter. The 2-cm-long microwave antenna can be positioned in any one of 10 positions along the ablation sheath, as indicated by the black shield line. This device has been used in the open chest and endosmotically. (Reproduced from [40] with permission.)

9.2.2.1

Transurethral Needle Ablation

The goal of therapy is to decrease the volume of prostatic tissue. This is a natural area where ablation based on EM field can be of use. Transurethral needle ablation (TUNA) is an endoscopical treatment using high frequency EM energy to produce thermal lesions inside the prostate tissue [41]. The procedure is performed by placing interstitial needles through the urethra and into the lateral lobes of the prostate, causing heat-induced coagulation necrosis (see Figure 9.4). The tissue is hence fore

Control and monitoring system Power oscillator Thermometry system Treatment applicator

Cooling system

Endorectal thermosensor support

Mobile probe support system

Figure 9.4 Illustration of a FR transurethral needle ablation (TUNA). (Reproduced from [42] with permission from IEEE.)

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heated to 70°C to 100°C at a frequency of around 456 kHz for about 5 minutes per lesion. The main result is the destruction of cells and therefore a reduction in tissue size. 9.2.2.2

Transurethral Microwave Thermotherapy

Another development is known as transurethral microwave thermotherapy (TUMT). This time we have a device that uses microwaves to heat and destroy excess prostate tissue to reduce urinary frequency and urgency. The therapy is such that, the urologist passes a thin catheter equipped with a small microwave-emitting device through the urethra to end in the prostate. Once in place, microwaves are precisely directed to heat and destroy excess prostate tissue. Temperatures between 45ºC to 70ºC are achieved. The problem of overheating the coaxial cable feeding the antenna is solved by injecting cooling fluid that circulates around the TUMT to prevent heat from damaging the wall of the urethra. At a more experimental level we also encounter microwave balloon catheters for the treatment of BHP. With these balloons it is possible to produce higher increases of temperature in the prostate with no damage to circumvent tissues. When compared to previously discussed microwave techniques, we gain proximity to the ill tissue and efficiency in emitted power, regarding its radial spreading [43]. Still, more research is needed before this type of treatment becomes fully operational. 9.2.3

Gastric Pathologies

Nerve ablation can be effective for the treatment of gastroesophageal reflux (GRER), which is a disease that consists of retrogradate flow of stomach contents into the esophagus. It usually comes with chest pain regurgitation, voice disorders, and in general swallowing dysfunctions. There is a small muscular valve at the junction of the esophagus and the stomach that normally prevents reflux that nevertheless can be damaged or altered by different causes like, for example, a hiatal hernia. In fact, in more than 80% of the cases studied, the problem is related to a wrong relaxation of this valve which can be attributed to dysfunctions of the nervous system that controls the valve. In a series of works [44], based on high frequency EM radiation, an ablation of the nerve pathway on the stomach of a particular kind of pig was performed with the goal of stopping the wrong signals that trigger relaxation on the corresponding valve. In all the cases under study, the relaxation of the valve was prevented, indicating a better behavior for obstacle reflux of stomach contents (see Figure 9.5). It is still too early to understand how far we could go with this type of procedure, but the literature shows clear potential for future human implementation. 9.2.4

Tumor Ablation

A very promising therapy based on microwaves is the possibility to treat cancer. For example, there is a particular form of microwave surgery, called hyperthermia, which has been used on thousands of patients suffering from prostate or breast can-

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(a)

(b)

Figure 9.5 (a) Gastric electrical stimulation (GES) system. (b) The GES system comprised a pair of leads sutured on the serosal surface of the stomach wall, and connected to an implantable battery-powered pulse generator positioned subcutaneously in the abdominal wall. (Extracted from [45] with permission from IEEE.)

cer [46–49]. Microwave-induced heat is used to destroy or ameliorate cancerous tumors. In fact, this type of therapy is used on liver tumors, lung tumors, renal and adrenal disease, and even on bone metastases. Although this technology has already been used, it is still in its infancy and much more research is needed to standardize the different procedures. In general, malignant tissues are typically heated up to the therapeutic temperature around 45ºC and maintained at this temperature for about 45 minutes without overheating the surrounding normal tissues. As is typical in this scenario, microwave therapy is frequently used in conjunction with other cancer therapies, such as radiation therapy. For example, the heat induced by the microwaves can increase tumor blood flow, thereby helping to oxygenate poorly oxygenated malignant cells. Interstitial treatments are used to send microwave energy through small needles (that act as small antennas) placed into the tumor (see Figure 9.6). It is important to generate a localized heating region only around the tip of the antenna. Usually a

Feeding point (2.45 GHz)

1.19 1.79 0.3

Coaxial cable 1.0

Biological z tissue

20.0

x 1.0

10.0

140

Catheter

Slots Short-circuit Unit: [mm]

Longitudinal cross section of the tip of the antenna

Figure 9.6 Typical structure of the coaxial-slot antenna used in tumor ablation. (Reproduced from [3] with permission from IEEE.)

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catheter is inserted into the tumor through the body, which allows the delivery of microwave irradiation and causing hyperthermia to the tumor. At this point we can take advantage of the catheter to inject the chemotherapy agent to the tumor. Microwaves can also be used to noninvasively heat subsurface tissues (dielectric heating) [4]. Major benefits of noninvasive microwave therapy are that it is virtually painless and makes no major cutting. Single-element applicators can safely deliver optimum thermal doses to relatively small superficial tumors. They are not well suited to treat large cutaneous or subcutaneous lesions that are common in patients with chest-wall recurrence of breast carcinoma. Multielement arrays have been used to improve clinical capabilities for localized microwave hyperthermia. 9.2.4.1

Liver Tumors

In Asia, there are nowadays liver tumor ablations based on microwave-induced devices. In this ablation the tumor is thermally destroy in situ; also, the nature of the radiation is local and therefore spares the patient’s liver, lowering morbidity. Initial results where reported in [50], where microwaves of 60W, for 2 minutes, were applied to patients by radiation. After this preliminary work, many others have appeared with increasing rates of success [51–54]. As an example, a system was recently developed to control solid tumors ablation using minimal invasive procedures [55]. The system comes with a microwave generator and a series of antennas-electrodes (see Figure 9.7). Among these electrodes there are temperature sensors to avoid overheating and to control temperature changes in the tumor tissue. The protocol consists of heating the tissue up to 100ºC for about 5 minutes. 9.2.4.2

Prostate Tumors

Another area subject to research is the ablation of prostate tumors. Here, in a similar fashion as in the liver, the idea is to introduce an array of antennas to radiate the tumor and ablate it. Again this is a promising treatment due to its minimal invasion and focal nature. Nevertheless, to date, there are few examples in the literature with

Figure 9.7 Detail of working models of needles for RF ablation of the liver. (Extracted from [56] with permission from the American Roentgen Ray Society.)

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clinical trials that show durability and efficiency for this application (see, for example, [57–59]). 9.2.5

Sleep Breathing Disorders

Obstructive sleep apnea is a dysfunction of the respiratory system in which the patient suffers occasional and transitorily obstructions of the upper airway channel which creates an interruption of normal breathing while sleeping. Normal therapy ranges from weight loss to surgical excision of excessive tissue or even maxillofacial surgery. Unfortunately all these different approaches have cure rates of only about 70%. In recent years, there has appeared in the literature a microwave radiating system called somnoplasty, that coagulates submocosal tissue using needles electrodes (see Figure 9.8). In this procedure not only is the tissue reduced, but also the airway is increased. The actual form of the needles is custom designed for each patient, and although it is still too early to tell, it seems to be a revolutionary method that should boost this area of treatment [60]. 9.2.6

Endometrial Ablation

The use of microwave ablation, including balloon endometrial ablation to cure dysfunctions on uterine blinding, is a revolutionary treatment that is believed to be safe, noninvasive, and easy to perform. In [62–64] the medical results for women

Figure 9.8 Illustration of the procedure for treating obstructive sleep disorders using a microwave heating device. (Extracted from [61] with permission.)

9.2 Therapeutic Applications

231

between 35 and 48 years old are described, showing satisfactory results, even though it is reported the presence of peritoneal irritation which has to be treated with local anesthesia and drug preparations. The technique is similar to other ablations, where the insertion of a small radiating system in conjunction with needles equipped with a thermal sensor to ensure the safety of the procedure is used to overheat the tissues to produce necrosis and therefore kill unwanted blood vessels. 9.2.7

Assistance to Arthroscopic Surgery

The treatment of different degrees of arthritis on different places of the body, such as vertebral disk, knees, and shoulders, has been modified to accommodate high frequency EM radiating systems. In this assisted form, the treatments are improving the effectiveness of healing and recovery time. Basically, in almost all junctions between bones the collagen plays an important role. The EM heating of this type of matter allows cutting, reshaping, and shrinking of its form to a custom design, such that different dysfunctions like joint instabilities and glenohumeral instabilities can be treated in a very effective manner [65, 66]. The procedure consists of a modification of the usual laparoscopic procedure where EM heat is included to softer the collagen present in the junction. This is done by means of small electrodes or minimal antennas that are introduced to the vicinity of the dysfunction junction. There are electromagnetic arthroscopic systems already in medical applications [67], with a large record of successful interventions, mainly in United States (see Figure 9.9). There is a lot of research on other applications, such as all kinds of knee disorders, chronic lower pain back, and finger arthritis, but the actual techniques are still in their infancy.

Electrical source 180 485 380

410B 462 488 490 400

412A

482 460

22

410A

22

CM 455A

455B 412B 475

Figure 9.9 Illustration of a RF-equipped scissor type instrument, used to threat damaged cartilage. (Extracted from [68] with permission.)

232

Medical Applications of High Frequency Electromagnetic Energy

9.2.8

Assistance to Lipoclasty

The reshaping of body contour by means of surgery is normally related to lipoplasty. This technique is based on the removal of excess subcutaneous adipose tissue using a cannula. The main difficulty with performing this surgery is the resistance of the external layer to the removal, due to its high content of fibers and rich visualization. These difficulties can be easily overcome by microwave EM heating of these regions, enhancing the solubility and therefore lowering its resistance. This should assist the removal from certain areas like the back, flanks, and breast [42]. The development of this technique involves the design of an EM cannula with a built-in EM antenna together with the studies of heating response of the adipose tissues to microwave radiation, like power, timing and frequency dependence to optimize the desiderate liquefaction with no harm to circumventing tissues [69]. The normal frequency used is around 2.5 MHz with temperature measurements in situ. Early histological studies show no damage to adjacent tissue, showing the viability of this procedure at a medical level. But again, it is an area of current research and more tests need to be done before it can be used as a standard treatment.

9.3

Conclusions and Future Research In this chapter, we have reviewed a few of the therapeutic applications of RF/microwaves in medicine that are currently under research. While some of them have already been implemented at different levels in current medicine, others are still under examination and experimentation. We emphasized clinical areas like cardiology, urology, and hyperthermia for cancer therapy, but we also consider other applications like dysfunctions of bone junctions, ablation of endometrial regions, and assistance with liposuction. Ongoing research on new, potentially useful therapeutic applications of RF/microwaves and on combining these therapies with other modalities is constantly under development (for an example, see Figure 9.10 which shows a recent development in intracavitary ablation). A more detailed discussion of some of the topics discussed here can be found in [4, 23, 55]. Regarding the directions and trends that research in this area should follow, it is a fact that we are faced with the necessity of improving microwave devices (that compared to other high frequency devices or RF are less developed). Microwave Endoscope Coaxial-slot antenna

Endoscope

Liver Target Common bile duct

Tip of the endoscope with coaxial-slot antenna

Coaxial-slot antenna Stomach Pancreas Papilla of Vater

Duodenum

Figure 9.10 Diagram of an intracavitary microwave hyperthermia. (Extracted from [3] with permission from IEEE.)

9.3 Conclusions and Future Research

233

techniques are particularly attractive due to their nature which has the advantage of a deeper range of influence together with the possibility to of acting on bigger volumes. We have to keep in mind that in thermal ablation, the principal goal is to increase induced coagulation volume while reducing exposure time. Research should be based on developing rational and reasonably sized lesions that do not require inordinate amounts of time to create. The use of more than one antenna or arrays of antennas supports this direction. We understand that much of the future success on developing these techniques will be based on more precise modeling of the bioelectromagnetic interaction. This will help to find more realistic determination on frequencies, power delivered, and time of exposure on each individual therapy. Also, there is a lot of room to develop more sophisticated antennas, electrodes, and generators of EM fields. It is clear that computer simulations will play an important role in our continued understanding of tumor coagulation and its interaction with healthy surrounding tissue.

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[40] Saltman, A.E., “Microwave ablation—a new use for an old technology,” US Cardiology, available at http://www.touchcardiology.com/articles/microwave-ablation-a-new-use-oldtechnology, 2004. [41] Rosen, A., et al., New Frontiers in Medical Device Technology, New York: Wiley, pp. 79–103, 1995. [42] Rosen, H.D., et al., “RF/microwaves,” IEEE Potentials, Vol. 18, pp. 33–37, Aug.–Sept. 1999. [43] Sterzer, F., et al., “Microwave treatments for prostate diseases,” IEEE Trans. Microwave Theory Tech., Vol. 48, pp. 1885–1891, Nov. 2000. [44] Triadafilopoulos, G., et al., “Hot water swallows improved symptoms and accelerate esophageal clearance in patients with esophageal motility disorders,” J. Clin. Gastroenterol., Vol. 26, pp. 239–244, 1998. [45] McCallum, R. W., et al., “Mechanisms of high-frequency electrical stimulation of the stomach in gastroparetic patients,” Proceedings of the 28th IEEE EMBS Annual International Conference, New York City, Aug. 30 to Sept. 3, 2006. [46] Rhim, H., “Review of Asian experience of thermal ablation techniques and clinical practice,” Int. J. Hyperthermia, Vol. 20, pp. 699–712, 2004. [47] Shimada, S., et al., “Complications and management of microwave coagulation therapy for primary and metastatic liver tumors,” Surg. Today, Vol. 28, pp. 1130–1137, 1998. [48] Shibata, T., et al., “Microwave coagulation therapy for multiple hepatic metastases from colorectal carcinoma,” Cancer, Vol. 89, pp. 276–284, 2000. Liang, P., et al., “Prognostic factors for percutaneous microwave coagulation therapy of hepatic metastases,” Am. J. Roentgenol., Vol. 181, pp. 1319–1325, 2003. [49] Liang, P., et al., “Sonography-guided percutaneous microwave ablation of high-grade dysplastic nodules in cirrhotic liver,” Am. J. Roentgenol., Vol. 184, pp. 1657–1660, 2005. [50] Seki, T., et al., “Ultrasonically guided percutaneous microwave coagulation therapy for small hepatocellular carcinoma,” Cancer, Vol. 74, pp. 817–825, 1994. [51] Clasen, S., et al., “Multipolar radiofrequency ablation with internally cooled electrodes: experimental study in ex vivo bovine liver with mathematic modelling,” Radiology, Vol. 238, pp. 881–890, 2006. [52] Abe, T., et al., “Value of laparoscopic microwave coagulation therapy for hepatocellular carcinoma in relation to tumor size and location,” Endoscopy, Vol. 32, pp. 598–603, 2000. [53] Lu, M.D., et al., “Hepatocellular carcinoma: U.S.-guided percutaneous microwave coagulation therapy,” Radiology, Vol. 221, pp. 167–172, 2001. [54] Shibata, T., et al., “Hepatocellular carcinoma: comparison of radio-frequency ablation and percutaneous microwave coagulation therapy,” Radiology, Vol. 223, pp. 331–337, 2002. [55] Reported in article by Rosen, A., et al., “Applications of RF/Microwaves in Medicine,” IEEE Trans. Microwave Theory Tech., Vol. 50, pp. 973–975, March, 2002. [56] John, P., et al., “Radiofrequency Ablation of the Liver: Current Status,” AJR, Vol. 176, pp. 3–16, Jan. 2001. [57] D’Ancona, F.C., et al., “High energy thermotherapy versus transurethral resection in the treatment of benign prostatic hyperplasia: results of a prospective randomized study with 1 year of follow up,” J. Urol., Vol. 158, pp. 120–125, 1997. [58] Sterzer, F., et al., “Microwave treatments for prostate disease,” IEEE Trans. Microwave Theory Tech., Vol. 48, pp. 1885–1891, 2000. [59] Ramsey, E.W., et al., “Durability of results obtained with transurethral microwave thermotherapy in the treatment of men with symptomatic benign prostatic hyperplasia,” J. Endourol., Vol. 14, pp. 671–675, 2000. [60] Schmidt-Nowara, W., et al., “Oral appliances for the treatment of snoring and obstructive sleep apnea,” Sleep, Vol. 18, No. 6, pp. 501–510, 1995. [61] Hovda, D.C., et al., “System and methods for electrosurgical treatment of obstructive sleep disorders,” U.S. Patent 7,131,969 B1, Nov. 2007.

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Medical Applications of High Frequency Electromagnetic Energy [62] Goldberg, S.N., et al., “Image-guided tumor ablation: standardization of terminology and reporting criteria,” J. Vasc. Interv. Radiol., Vol. 16, pp. 765–778, 2005. [63] Jack, A.S., et al., “Microwave endometrial ablation: an overview,” Rev. Gynaecol. Pract., Vol. 5, pp. 32–38, 2005. [64] Garside, R., et al., “Microwave and thermal balloon ablation for heavy menstrual bleeding: a systematic review,” BJOG, Vol. 112, pp. 12–23, 2005. [65] Zarins, B., et al., “Diagnosis and treatment of traumatic anterior instability of the shoulder,” Clin. Orthop. Rel. Res., Vol. 291, pp. 75–84, 1993. [66] Zipes, D.P., “Radiofrequency ablation—What is left?” Eur. Heart J., Vol. 16, No. Suppl., pp. 24–27, 1995. [67] Abrams, J.S., “Arthroscopic shoulder stabilization using suture anchors and capsular shrinkage,” ORATEC Interventions Inc., Menlo Park, CA, Case Rep., 1999. [68] C. Truckai, J. A., et al., “Electrosurgical working end with replaceable cartilages,” U.S. Patent 7,041,102 B2, May. 2006. [69] Rosen, A., et al., “RF/microwave aided tumescent liposuction,” IEEE Trans. Microwave Theory Tech., Vol. 48, pp. 1879–1884, Nov. 2000.

CHAPTER 10

Conclusions David A. Sánchez-Hernández

With the vast number of research papers and books on the issue, our knowledge of the phenomena dominating high frequency electromagnetic dosimetry has increased considerably. The recent use of computer codes and heterogeneous anatomical models combining electromagnetic and thermal equations has provided for some answers, but simultaneously other questions have been raised. Extremely complicated patterns of energy absorption have been revealed and many inherent difficulties on accurate evaluating techniques have been identified. This vast knowledge, however, has lead to an increasing number of papers identifying current limitations of standards. This calls for a revision of safety limits in force today. This has to be done in terms of updating reference levels with more recent simulations and measurements for worst-case realistic coupling scenarios, and in view of the need to directly incorporate thermal thresholds into the limits. Accurate determination of safety factors is yet another issue for improvement. This is particularly important now since it has become possible to predict EMF-induced temperature increase in any body part. In fact, it now seems clear that SAR alone may not provide an adequate description of the regional thermal environment [1], and several models will have to be revised. The validity of current standards for accurately evaluating exposure is yet another source of concern. While it seems clear that standards are adequate for compliance testing and human health protection, they are not so useful for accurate determination of exposure. In [2], ICNIRP general public exposure limits were not found sufficiently conservative for a realistic human body model exposed to a vertically aligned E-field plane wave unless secondary limb currents were called for and applied to 10g averaging in the leg. In [3], for instance, it was demonstrated that the solotissue measuring systems employed for compliance testing could make the current dielectric parameters approved by standards worldwide inadequate for providing a conservative exposure estimation when a realistic anatomical body model is used in far-fieldlike exposure scenarios. This is typically the situation for street-level exposure situations for the general public. In [4], it was demonstrated that under certain conditions safety distances predicted by the basic restrictions are larger than those predicted by reference levels when assessing human exposure in regions very close to the sources. This happens, for example, when UMTS-related frequencies and dipole-array antennas are employed. This may eliminate the a priori innate con-

237

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Conclusions

servative character of reference levels, or at least in theory since earlier on in [5] it was demonstrated through simulations and measurements that safety distances inferred from free space spatial maximum power density were substantially larger than those derived from SAR values. Yet, it is true that in [5] basic restrictions for power density were employed (50 W/m2 for occupational exposure and 10 W/m2 for general public), and that these restrictions cannot be applied to 935 MHz with the valid standard at the time, as it was stated also in [5]. It is also true, however, that the reference levels at 935 MHz are 23,375 W/m2 for the equivalent plane wave power density [6]. In addition, in [5], an inconsistency was found between the maximum local and whole-body SAR safety limit values specified in the IEEE standard and in the ICNIRP guidelines when safety distances were calculated and measured. These and other discrepancies are also the cause of concern, which will require further harmonization efforts in the future. Before these two above-mentioned studies were published, it was established that a temperature rise over the whole body of 1ºC could be tolerated by healthy people and that this temperature rise corresponded to a SAR of approximately 4 W/kg [7]. Consequently, 4 W/kg was set as the threshold for biological effects, and a factor of 10 was used for safety in occupational exposures and an additional factor of 5 for general public, providing the 0.08 W kg-1 limit for whole-body averaged SAR [8]. Recent studies with detailed anatomical models and complex mass and heat transfer equations have shown that the temperature rise within the head due to absorbed RF power emitted by mobile phones is modest, namely around 0.15ºC [9–12]. Yet, they have also demonstrated that present ∼2-mm anatomical resolutions are low and have a large impact on small-scale and temperature distributions [13]. There is a need for more detailed models to be adopted so that regions such as the eye and orbital areas can be properly evaluated [14]. In addition, and despite the originally predicted safety factors, the use of complex hybrid electromagnetic-thermal modeling techniques has provided brain temperature elevations as high as 1.35ºC for exposure to controlled (occupational) maximum allowed levels at both 835 and 1,900 MHz [15, 16], reproduced in Figure 10.1. Since new exposure situations are becoming commonplace with the use of new wireless devices close to different parts of the human body, the near- and far-field discoveries explained throughout this book and its recommendations should be considered carefully. With thermal studies readily available, and already predicting similar thermal protection levels for both the ICNIRP guidelines and IEEE standards, it may be time to consider establishing more direct limits based upon thermal increments. This could be in contradiction to indirect protection levels (reference levels), but it would help to avoid current discrepancies in the adopted standards. The heterogeneity of standards does not help to deliver the right message to people, and it is no surprise that they do not feel confident with such differences. The IEEE has recently changed its standard in an effort towards homogenization, but since the pinna issue remained unsolved, as far as it is not treated in the same way as in other standards, the efforts seem to be diluted in new differences. This lack of a unique standardization is in contrast with the fact that the problem of electromagnetic interaction with human tissue has been extensively tackled in the literature. The problem has been analyzed in so many papers that further deep analyses are finding

Conclusions

239 1.4

1.2

ΔTmax (°C)

1

0.8

0.6 0.4

0.2

0

0

Utah model with 14-mm-thick ear Visible Man model Utah model with 6-mm-thick ear

2

4 8 6 Non Pinna 10-g SAR (W/kg)

10

12

Figure 10.1 Maximum temperature increase as a function of peak 10g nonpinna SAR at 835 MHz in [15]. (Available at http://www.ursi.org.)

increasing difficulties for getting published. Some journal editors are stopping these papers from going into peer review, unless the authors insist. It has to be said, however, that the combination of basic restrictions, reference levels, and localized exposure limits has provided an adequate protection level for digital commercial systems. Current standard amendments have closely following scientific knowledge. Yet, it has also been made clear that old analog systems (and others in use, such as TETRA) did not completely fulfill current safety limits. As an example, some analog TETRA handsets have been banned from use in some countries. This is an important lesson to learn for future wireless systems employed in a wide variety of modes and relative positions to the human body. Therefore, since standards have been often reviewed, sufficient additional knowledge has been provided to start this new revision for a more accurate prediction of current safety factors with basic restrictions and new reference levels based upon more complicated coupling situations. Three main issues remained unsolved and represent the core of the problem between scientists, regulatory bodies, and stakeholders: 1. What has to be addressed: • The problem of the environmental exposure; • The gap between science and public perception of risks. 2. Who has to get fully involved: • Both national and supranational regulatory authorities; • The scientific community; • Stakeholders (manufacturers, operators, service providers, consumers). 3. A unique standard is required, and should be: • Uniform: Global EMF standard;

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Conclusions

• •

Mandatory: Global market; Flexible: Technology-independent.

In this book we have tried to update existing knowledge on high frequency electromagnetic dosimetry, but it is certainly just a small effort towards the proposed unique worldwide EMF standard.

References [1] Mason, P.A., Hurt, W.D., Walters, T.J., D’Andrea, J.A., Gajšek, P., Ryan, K.L., Nelson, D.A., Smith, K.I., and Ziriax, J.M., “Effects of frequency, permittivity, and voxel size on predicted specific absorption rate values in biological tissue during electromagnetic-field exposure,” IEEE Transactions on Microwave Theory and Techniques, Vol. 48, pp. 2050–2058, Nov. 2000. [2] Dimbylow, P.J., “Fine resolution calculations of SAR in the human body for frequencies up to 3 GHz,” Physics in Medicine and Biology, Vol. 47, pp. 2835–2846, 2002. [3] Christ, A., Klingenböck, A., Samaras, T., Goiceanu, C., and Kuster, N., “The dependence of electromagnetic far-field absorption on body tissue composition in the frequency range from 300 MHz to 6 GHz,” IEEE Transactions on Microwave Theory and Techniques, Vol. 54, No. 5, pp. 2188–2195, 2006. [4] Martínez-Búrdalo, M., Martín, A., Anguiano, M., and Villar, R., “On the safety assessment of human exposure in the proximity of cellular communications base-station antennas at 900, 1800 and 2170 MHz,” Physics in Medicine and Biology, Vol. 50, pp. 4125–4137, 2005. [5] Cooper, J., et al., “Determination of safety distance limits for a human near a cellular base station antenna, adopting the IEEE standard or ICNIRP guidelines,” Bioelectromagnetics, Vol. 23, pp. 429–443, 2002. [6] IEEE Standard C95.1-2005, “IEEE Standard for Safety Levels with Respect to Human Exposure to Radio Frequency Electromagnetic Fields, 3 KHz to 300 GHz,” American National Standard (ANSI), 2006. [7] National Radiological Protection Board (NRPB), “Electromagnetic fields and the risk of cancer, Report of an Advisory Group on Non-ionising Radiation,” Doc. NRPB, 3, No. 1, pp. 1–138, 1992. [8] International Commission on Non-Ionizing Radiation Protection, “Guidelines for limiting exposure to time-varying electric, magnetic, and electromagnetic fields (up to 300 GHz),” Health Physics, Vol. 74, pp. 494–522, 1998. [9] van Leeuwen, G.M., Lagendijk, J.J.W., van Leersum, B.J.A.M., Zwamborn, A.P.M., Hornsleth, S.N., and Kotte, A.N.T.J., “Calculation of change in brain temperatures due to exposure to a mobile phone,” Physics in Medicine and Biology, Vol. 44, pp. 2367–2379, 1999. [10] Wang, J., and Fujiwara, O., “FDTD computation of temperature rise in the human head for portable telephones,” IEEE Transactions on Microwave Theory and Techniques, Vol. 47, pp. 1528–1534, 1999. [11] Wainwright, P.R., “Thermal effects of radiation from cellular phones,” Physics in Medicine and Biology, Vol. 45, pp. 2363–2372, 2000. [12] Gandhi, O.P., Li, Q.X., and Kang, G., “Temperature rise for the human head for cellular telephones and for peak SARs prescribed in safety guidelines,” IEEE Transactions on Microwave Theory and Techniques, Vol. 49, pp. 1607–1613, 2001. [13] van der Kamer, J.B., van Vulpen, M., de Leeuw, A.A.C., Kroeze, H., and Lagendijk, J.J.W., “CT-resolution regional hyperthermia treatment planning,” Int. Journ. Hyperth., Vol. 18, pp. 104–116, 2002.

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[14] van der Kamer, J.B., and Lagendijk, J.J.W., “Computation of high-resolution SAR distributions in a head due to a radiating dipole antenna representing a hand-held mobile phone,” Phys. Med. Biol., Vol. 47, pp. 1827–1835, 2002. [15] Li, Q.X., and Gandhi, O.P., “Thermal implications of the present and proposed RF safety standards for the brain for exposure to cellular telephones at 835 and 1900 MHz,” URSI General Assembly New Delhi, October 2005. [16] McIntosh, R.L., Anderson, V., and McKenzie, R.J., “A numerical evaluation of SAR distribution and temperature changes around a metallic plate in the head of a RF exposed worker,” Bioelectromagnetics, Vol. 26, pp. 377–388, 2005.

Acronyms ADF

averaged duration fading

ADONIS

Algorithms for Dynamic Optical Networks Based on Internet Solutions

AECC

Asociación Española Contra el Cáncer (Spanish Association Against Cancer)

AF

antenna factor

AM

amplitude modulation

AMPS

advanced mobile phone system

ANFR

Agencé Nationale des Fréquences

ANSI

American National Standards Institute

ARFCN

absolute radio frequency channel number

ARIB

Association of Radio Industries and Businesses

ARPAT

Agenzia Regionale per la Protezione Ambientale della Toscana

ASTM

American Society for Testing and Materials

BCCH

broadcast control channel

BEM

boundary element method

BHE

bioheat equation

BLAS

basic layered anatomical shaped model

BPH

benign prostatic hypertrophy

BPSK

binary phase shift keying

BS

base station

BSA

base station antenna

CB

compliance boundary

CDMA

code division multiple access

CEN

European Committee for Standardization

CENELEC

European Committee for Electrotechnical Standardization

CF

correction factor

CIE

coupled integral equations

CISPR

Comité International Spécial des Perturbations

243

244

Acronyms

CL

correction factor for cable losses

COMOBIO

Communications Mobiles et Biologie

COST

European Cooperation in the Field of Scientific and Technical Research

CPICH

common pilot channel

CSTEE

European Scientific Committee on Toxicity, Ecotoxicity, and the Environment

CT

computer tomography

CW

continuous wave

C/I

carrier to interference

DAM

dielectric anatomical model

DASY4

Dosimetric Assessment System 4

DBS

deep brain stimulator

DCH

dedicated transport channel

DCS

digital cellular system

DMCMI

digital mobile communications measuring instrument

DPCCH

dedicated physical control channel

DPDCH

dedicated physical data channel

DS-CDMA

direct-sequence code division multiple access

DTX

discontinuous transmission

EAS

electronic article surveillance

EBEA

European Bioelectromagnetics Association

EEC

entrance to the ear canal

EIRP

effective isotropic radiated power

EIS

European information system

ELF

extremely low frequency

EMC

electromagnetic compatibility

EME

electromagnetic energy

EMF

electromagnetic field

EPI

entire plain interaction model

EQ

exposure quotient

ERP

ear reference point

ETH

Eidgenössische Technische Hochschule

ETSI

European Standard Telecommunications Institute

EU

European Union

EURC

European Union recommendation

EZ

exclusion zone

Acronyms

245

FCC

Federal Communications Commission

FDD

frequency division duplex

FDMA

frequency division multiple access

FDTD

finite difference time domain

FE

finite element

FEM

finite element method

FIT

finite integration technique

FM

frequency modulation

FS

full speech

FTRD

France Telecom R&D

GEM

electromagnetics and matter research

GIMRE

Microwave, Radiocommunications, and Electromagnetism Engineering Research Group

GMT

generalized multipole technique

GO

geometrical optics

GRER

gastroesophageal reflux

GSM

Global System for Mobile Communications

GTP

generic twin phantom

HCRA

Harvard Center for Risk Analysis

HF

high frequency

HPL

highest general public permissible exposure level

HPP

highest permissible percentage

HSL

head simulating liquid

HV

high voltage

IARC

International Agency for Research on Cancer

ICES

International Committee on Electromagnetic Safety

ICNIRP

International Commission for Nonionizing Radiation Protection

ICRP

International Commission on Radiological Protection

IEC

International Electrotechnical Commission

IEEE

Institute of Electrical and Electronics Engineers

IF

intermediate frequency

IMEI

International Mobile Station Equipment Identity

IRE

Institute of Radio Engineers

IRPA

International Radiation Protection Association

IS

International System of Units

JINA

Journées Internationales de Nice sur les Antennes

246

Acronyms

JRC

Joint Research Center

LCR

level crossing rates

LV

low voltage

MAFIA

Maxwell finite integration algorithm

MBA

microwave balloon angioplasty

MNC

mobile network code

MMF

Mobile Manufacturers Forum

MMS

multimedia message service

MoM

method of moments

MPE

maximum permissible exposure

MRI

magnetic resonance imaging

MRL

most restrictive limit

MS

mobile station

NEC

numerical electromagnetic code

NMT

Nordic Mobile Telephone System

NORMAN

normalized man

NRPB

National Radiological Protection Board

OCNS

orthogonal channel noise simulator

PCB

printed circuit board

PCCPCH

primary common control physical channel

P-CPICH

primary common pilot channel

PDA

personal digital assistant

PEC

perfect electrical conductor

PWC

power control

RB

resolution bandwidth

RF

radio frequency

RFID

radio frequency identification

RNRT

Réseau National de la Recherche en Télécommunications

RSCP

received signal code power

RSSI

received signal strength indicator

SA

spectrum analyzer

SACCH

slow associated control channel

SANCO

Directorate General of Health and Consumer Protection

SAM

specific anthropomorphic mannequin

SAR

specific absorption rate

SC

serving cell

Acronyms

247

SCCPCH

secondary common control physical channel

SCENIHR

Scientific Committee on Emerging and Newly Identified Health Risks

S-CPICH

secondary common pilot channel

SF

Spreading Factor

SID

silence descriptor speech frame

SIMD

single-instruction multiple-data

SIR

signal-to-interference ratio

SL

superposition level

SMS

short message service

SPEAG

Schmid & Partner Engineering AG

STM

short term mission

TAC

type approval code

TACS

total access communication system

TC

traffic channel

TDD

time division duplex

TDMA

time-division multiplex access

TE

transversal electrical

TEMS

test mobile station

TETRA

terrestrial trunked radio

TEQ

total exposure quotient

TFCI

transport format combination indicator

TPC

transport format combination

TPCI

transport format combination indicator

TTAS

telecommunications technology associations

TTI

transmission time interval

TUMT

transurethral microwave thermotherapy

TUNA

transurethral needle ablation

TV

television

UHF

ultra high frequency

UMTS

Universal Mobile Telecommunication System

U.S.A.

United States of America

UTD

uniform theory of diffraction

UTRAN

UMTS Terrestrial Radio Access Network

VHAD

visible human adult male head phantom

VHF

very high frequency

VHP

Visible Human Project

248

Acronyms

WCDMA

wideband code division multiple access

WCS

worst case scenario

WHO

World Health Organization

WLAN

wireless local area network

YHP

Yale Human Project

About the Editor David A. Sánchez-Hernández (Dipl.-Ing., Ph.D., CEng, SMIEEE, FIET) is with Universidad Politécnica de Cartagena, Spain, where he leads the microwave, radiocommunications, and electromagnetism engineering research group (GIMRE, http://www. gimre.upct.es). He holds more than 40 scientific papers, 80 conference contributions, nine patents, and eight books, acting regularly as a reviewer of many IET and IEEE publications and conferences. He has also been awarded several national and international prizes, including the R&D J. Langham Thompson Premium, awarded by the Institution of Electrical Engineers (formerly The Institution of Engineering and Technology, IET), or the i-patentes award by the Spanish Autonomous Region of Murcia to innovation and technology transfer excellence. He is the cofounder of EMITE Ing, a spin-off company. His research interests encompass all aspects of the design and application of printed multiband antennas for mobile communications, electromagnetic dosimetry issues, and MIMO techniques. Since 2004 he has been a member of the Spanish AENOR CTN215 “Equipment and Measurement Techniques Related to Electromagnetic Field and Human Beings” standardization committee and represents Spain at the European CENELEC TC106X “Electromagnetc Fields in the Human Environment” committee.

About the Contributors Alejandro Díaz Morcillo was born in Albacete, Spain, in 1971. He received his ingeniero (Ms. Eng.) and doctor ingeniero (Ph.D.) degrees in telecommunication engineering, both from Polytechnic University of Valencia (UPV), Spain, in 1995 and 2000, respectively. From 1996 to 1999 he was a research assistant at the Department of Communications of the UPV, and in 1999 he joined the Department of Information Technologies and Communications at the Polytechnic University of Cartagena (UPCT), Spain, as teaching assistant, and he has been an associate professor there since 2001. He leads the Electromagnetics and Matter Research Group at UPCT and his main research interest lays in numerical methods in electromagnetics, industrial microwave heating systems, and electromagnetic compatibility. He is a member of IEEE, and a coauthor of more that 20 papers in international journals and more than 60 national and international congresses. He holds several patents regarding microwave heating industrial processes and is a reviewer of sev-

249

250

About the Editor

eral international journals. In 2001 he was the recipient of the prize for the Best Telecommunication Doctoral Thesis in the Valencian Community (Spain). In 2006 his research group was awarded with the “Segundo Premio i-patentes 2006 al Fomento de la Transferencia de los Resultados de la Investigación” from the Regional Education and Culture Ministry of the Region of Murcia (Spain). José Fayos-Fernández was born in Valencia, Spain, in September 1976. He received his M.S. in telecommunications engineering from the Universidad Politécnica de Valencia (UPV) in 2001. He was with ITACA Institute, UPV, working on the base station compliance campaign in 2002. In 2003 he received his master’s of advanced studies in signal theory and communications from UPV. From October to early 2004 he was a research assistant with the Universidad Politécnica de Cartagena (UPCT), Cartagena, Spain, where he focused his research toward his Ph.D. degree in electromagnetic dosimetry. Since early 2004, he has been a lecturer with the School for Telecommunications Engineering, UPCT. In September 2006 he was an academic visitor for half a year with the IT’IS foundation of the Swiss Federal Institute of Technology Zurich, Switzerland, where he contributed in developing a large in vitro exposure setup for electromagnetic dosimetry. In 2006 and 2008 he was awarded the Murcia’s Regional Government i-patentes Prize, Spain, in the matter of innovation and technology transfer. Miguel Á. García-Fernández was born in Cartagena, Spain, in 1981. He received the Dipl. Ing. degree in telecommunications engineering from the Universidad Politécnica de Cartagena, Spain, in 2005. In 2005, he joined the Department of Information Technologies and Communications, Universidad Politécnica de Cartagena, Spain, where he is working towards his Ph.D. His research interests include the biological effects of electromagnetic radiation, SAR measurement, and antennas. He is the author or coauthor of three scientific papers in international journals, six in national journals, an invited presentation at an international congress (HES-07), six communications to international congresses and four to national congresses. In 2005, he was awarded a scholarship from the FPI program of the Fundación Séneca, the Regional R&D Coordinating Unit of the Region of Murcia (Spain). In 2006, he was awarded the “Segundo Premio i-patentes 2006 al Fomento de la Transferencia de los Resultados de la Investigación” from the Regional Education and Culture Ministry of the Region of Murcia (Spain), and the R&D group he belongs to has been awarded an Honorific Mention from the Official College of Pharmaceuticals of the Region of Murcia (Spain). Antonio M. Martínez-González obtained his Dipl.-Ing. in telecommunications engineering from Universidad Politécnica de Valencia, Spain, in 1998 and his Ph.D. from Universidad Politécnica de Cartagena, in 2004. From 1998 to September 1999, he was employed as technical engineer at the Electromagnetic Compatibility Laboratory of the Universidad Politécnica de Valencia, where he developed assessment activities and compliance certifications with European directives related with immunity and emissions to electromagnetic radiation from diverse electrical, electronic, and telecommunication equipment. Since September 1999 he has been an assistant lecturer at Universidad Politécnica de Cartagena. Research works developed by Antonio Martínez-González have been awarded with the Spanish National Prize from Foundation Airtel and Colegio Oficial de Ingenieros de Telecomunicación from Spain for the best final project on mobile communications

About the Contributors

251

in 1999. He has also been awarded with the i-patentes award by the Spanish Autonomous Region of Murcia for innovation and technology transfer excellence in 2006 and 2008. He has authored more than 20 scientific papers, 40 conference contributions, three educational books, and two research books, holds three patents, and also acts regularly as a reviewer of IET and IEEE publications. His research interest is focused on electromagnetic dosimetry, radioelectric emissions, and MIMO techniques for wireless communications. Juan Monzó-Cabrera was born in Elda (Alicante), Spain, in January 1973. He received the Dipl. Ing. and Ph.D. degrees in telecommunications engineering from the Universidad Politécnica de Valencia, Valencia, Spain, in 1998 and 2002, respectively. From 1999 to 2000 he was a research assistant with the Microwave Heating Group (GCM). In 1999, he joined the Departamento de Tecnologías de la Información y las Comunicaciones at Universidad Politécnica de Cartagena, where he currently works as an associate lecturer. He has coauthored more than 60 papers in referred journals and conference proceedings and he holds several patents regarding microwave heating industrial processes. Dr. Monzó-Cabrera is a reviewer of several international journals and is a director of the Association of Microwave Power in Europe for Research and Education (AMPERE), a European-based organization devoted to the promotion of RF and microwave energy. His current research areas cover microwave-assisted heating and drying processes, microwave applicator design, and optimization and numerical techniques in electromagnetism. Pedro J. Silva-Briceño was born in Turin, Italy, on May 1970. He received his B.Sc. in physics from the University Simon Bolivar (Venezuela) in 1994. He obtained a master’s (M.Sc.) degree in mathematics from King’s College London, University of London (UK) in 1995, and then received a second master’s (M.Sc.) in theoretical physics from Cambridge University (UK) in 1996. His Ph.D. was granted by the University of New Castle Upon Tyne in 2000. From 2000 to 2006 he has been a research postdoctorate at three different institutions, Syracuse University (USA), the University of Milan (Italy), and the University Autonoma of Barcelona (Spain). Since 2006 he has worked as a research associate at ICE-CSIC and the physics department of the University Autonoma of Barcelona. His current research areas cover microwave-assisted heating and drying processes, microwave applicator design and optimization, and numerical techniques in electromagnetics. Juan F. Valenzuela-Valdés was born in Marbella, Spain. He received his degree in telecommunications engineering from the University of Malaga, Spain, in 2003, and his Ph.D. from Technical University of Cartagena, in early 2008. In 2004 he worked at AT4Wireless (Malaga) and joined the Department of Information Technologies and Communications. He is member of the Microwave, Radiocommunications, and Electromagnetism Engineering Research Group that has been awarded with the second prize of innovative research group from Autonomous Region of Murcia Prize and has been awarded an honorific mention from the Official College of Pharmaceuticals of the Region of Murcia (Spain). He has published more than 10 scientific papers and more than 15 conference contributions, and he is a reviewer of international journals. He has three patents pending. In 2007 he joined EMITE Ing as head of research. His current research areas cover MIMO communications, reverberation chambers, and SAR measurements.

Index −λ/2 dipole antennas, 101

A Absorption phenomenon, 22 Adult male head phantom (VHAD), 95 ANSI/IEEE guidelines, 207 Antenna factors (AFs), 130 determination, 130 probe dimensions and, 131 Antennas, 129–32 −λ/2 dipole, 101 base station, 68, 82 cross dipole, 78 directional, 83 linear array, 77 technology, 82 types of, 130 Arrhythmia, microwave ablation for, 225 Arthroscopic surgery, 231 Auditory implants, 200–201 effect of size on SAR distribution, 189 electromagnetic interference, 186 external speech processor, 188 internal cochlear implant, 188 MRI and, 200 Averaging strategies, 109–10

B Base station identity code (BSIC), 142 Base stations (BS) activity determination, 140–43 antenna model geometry, 104 antenna proximity, 68 antennas, 82 antenna technology, 82 exposure, 67 exposure scenarios, 107 GSM, 136 power classes, 135 power values, 106 total exposure quotients, 139

Basic layered anatomical shaped model (BLAS), 93, 94 Benign prostatic hypertrophy (BPH), 225 Bioheat equation, 50–56, 108 defined, 50 modified version, 52, 53 Pennes modification, 53–54 Yang modification, 53 Biological effects, 7, 12 BLAS/SAM models, 190–91 Blood density, 51 mass flux, 51 temperature, 51 velocity, 51 “Blue Angel” label, 215 Body tissue simulating liquid (BTSL), 172 Boundary element method (BEM), 85 Broadband measurements, 143–44 Broadband probes, 126–28 compliance testing, 144 data acquisition and evaluation, 144–45 drawback, 128, 144 flat-response, 144–45 functions, 127 indications, 127 isotropic, 129 isotropic shaped-response, 145 measurement results, 145 measurements, 126 validity, 127 Broadcast control channel (BCCH), 142, 148

C Cancer, 10, 227–28 Cardiac treatments, 224–25 microwave ablation, 225 microwave balloon angioplasty (MBA), 224–25 thermal therapy in, 224 See also Medical applications Catheter ablation, 225

253

254

CENELEC, 93, 140 Chain rule, 53 Coaxial dielectric probe, 31 Cochlear implants (CI), 200 external, 201 internal, 201 Code division multiple access (CDMA), 29 direct sequence (DS-CDMA), 154 wideband (WCDMA), 124, 154 Cole-Cole model, 40, 41, 44 Cole-Davidson model, 41 Common pilot channel (CPICH), 155 primary (P-CPICH), 156 secondary (S-CPICH), 156 signal and interference, 157 Complex permittivity, 39–40 Compliance boundary (CB), 122, 123 Compliance testing, 69–71 for 2G measurements, 134–53 for 3G measurements, 153–58 antennas, 129–32 broadband probes, 126–28, 144 flow chart, 125 instrumentation, 126–32 narrowband equipment, 128–29 WCS, 158 Computer tomography (CT) scans, 175 Conduction currents, 39 Conductivity electric, 59 temperature and, 28 thermal, 51 Contacting electrode method scheme, 34 Coronary thrombosis, 223 COST281, 140 Coupled integral equations (CIE), 100 Cross dipole antennas, 78 Curl operator, 24 Current density, 39 Cylindrical-wave model, 82

D Debye equation, 39, 40 Debye model, 41 Dedicated physical control channel (DPCCH), 155, 156 Dedicated physical data channel (DPDCH), 155 Dedicated transport channel (DCH), 155 Deep brain stimulators (DBS), 182 Degradation rates, 172 Dielectric 2-mm anatomical models (DAM), 75

Index

Dielectric loss tangent, 24 Dielectric properties, 29–50 of blood, thyroid, and testis tissues, 46 bone tissue, 45 of brain and cerebellum tissues, 45 change with time and temperature, 46–47 current knowledge, 38–46 frequency dependence of, 44 of human tissues, 30, 45, 46, 49 in-vivo/in-vitro techniques, 37–38 measurement techniques, 29–38 muscle tissue, 45 nonresonant measurement methods, 30–34 rat tissues, 48 resonant measurement methods, 35–37 role on electromagnetic dosimetry, 46–50 skin, 45, 49 variation with moisture content, 47 whole-brain, skin, and skull, 49 Digital mobile communications measuring instruments (DMCMIs), 132, 142 Directional antennas, 83 Direct-sequence CDMA (DS-CDMA), 154 Discontinuous transmission (DTX), 103, 142 Dissado model, 42 Dosimetric assessment system (DASY), 165 defined, 167 illustrated, 166 measurements, 168 versions, 167 Driving risks, 11

E Ear reference point (ERP), 99, 190 Electric conductivity, 59 Electric conductors, 26 Electric fields distribution, 27, 59 orthogonal components, 121 Electric flux density, 23 Electric permittivity, 23 effective, 25 estimating, 59 relative, 24 See also Permittivity Electrodes, 180–83 Electromagnetic dosimetry defined, 22–29 far-field numerical, 67–85 high-frequency, 14 from mobile phones, 5–6 near-field numerical, 93–111

Index

research, 14 tissue dielectric properties and, 46–50 Electro Magnetic Field Project (EMF), 10 Electromagnetic heating, 231, 232 Electromagnetic interference, 11 Electromagnetic therapy, 221–23 biological response, 222–23 risk, 222–23 Electronic article surveillance (EAS), 211 Electrosmog, 11 EMF distribution in free space, 22 health effects, 209 health risks, 10–11 interaction with matter, 21–59 limiting exposure to, 7–9 matter and, 23–27 as physical agent, 15 risk perception, 5 safety limits, 9 EN12198-1, 211 EN50361, 210 EN50400, 212 EN50401, 212 Endometrial ablation, 230–31 Energy dissipation, 59 Entire plain interaction (EPI) model, 93, 190 Equivalent isotropically radiated power (EIRP), 80 Equivalent radiated power (ERP), 80 EURC levels, 136 European Bioelectromagnetics Association (EBEA), 139 European Information System on Electromagnetic Fields Exposure and Health Impacts (EIS-EMF) Project, 215 Exclusion zone (EZ), 121, 122, 123 Exposure assessment, field regions, 122 base stations, 5, 67 biological effects, 7, 12 compliance testing, 69–71 evaluating, 28–29, 69–71 far-field region, 22–23 GSM, 108 hybridized scenario, 85 limiting, 7–9 limiting with SAR, 29 maximum permissible (MPE), 108 plane wave, limits, 208 RF, 55

255

safety factors, 15 scenarios, 5–6 simulated values, 110 in situ measured assessment, 121–58 total quotients, 139, 151 Extrapolation techniques, 124 Extremities, 210–12 Eye implants, 177–80

F Far-field compliance testing, 134–58 for 2G measurements, 134–53 for 3G measurements, 153–58 See also Compliance testing Far-field numerical electromagnetic dosimetry, 93–111 compliance testing, 69–71 electromagnetic exposure evaluation, 69–71 human body model, 71–76 introduction to, 67–69 simulation techniques, 82–85 source modeling, 76–82 Feedpoint impedance, 74 Finite-difference time-domain (FDTD), 70, 83 cubical form, 100 uniform theory of diffraction with, 85 Finite element (FE) method, 70 Finite element method (FEM), 85, 100 enclosure, 104 MoM with, 100 Finite integration technique (FIT), 70, 103 Flat-response probes, 144–45 Frequency division duplex (FDD), 154

G Gain-based models, 76, 78, 80 Gastric electrical stimulation (GES) system, 228 Gastric pathologies, 227 Gastroesophageal reflux (GRER), 227 Generalized multipole technique (GMT), 70 Generic twin phantom (GTP), 98 Geometrical optics (GO), 85 German Federation Radiation Protection Office, 216 Green’s functions, 83 GSM base stations, 136 EMF levels, 147 exposure, 108 indoor measurement campaign, 134–35 modulated signal ring, 146 TDMA frame and super frame, 141

256

GSM900 systems, 69 carriers, 146 compliance assessment, 152 compliance verification, 121 far-field distances, 122 frequencies, measurements at, 149 signals, 135 GSM1800 systems, 69 carriers, 146 compliance assessment, 152 compliance verification, 121 far-field distances, 122 frequencies, measurements at, 149 polarizations, 148 signals, 135

H Harvard Center for Risk Analysis (HCRA), 12 Havriliak-Negami model, 41 Head modeling, 48 Head simulating liquid (HSL), 93, 171, 172 Health risks, 10–11 Hearing aid compatibility (HAC), 167 Heat EM, 231, 232 Joule, 72 microwave-induced, 228 See also Temperature Heat generation, 50–57 bioheat equation, 50–56 thermal properties, 56–57 Homogeneous vector wave equation, 25 Human body model, 71–76 coupling mechanism, 76 external view, 72 feedpoint impedance, 74 importance, 105 layered planar tissue, 72 standardized, 76 VHP, 75 Yale, 75 Human head exposure, 5 Human thermoregulatory model, 14 Hybridized exposure scenario, 85 Hyperthermia, 221 as cancer treatment, 227–28 intracavitary microwave, 232 Hypothermia, 221–23

I IEEE C95.1-200X Standard for Safety Levels, 210

Index

homogenization and, 238 plane wave exposure limits, 208 standards, 238 Impedance analysis, 33–34 Impedance analyzers, 29, 59 Incident power density, 207 Instrumentation, 126–32 antennas, 129–32 broadband probes, 126–28 far-field exposure, 126 narrowband equipment, 128–29 International Agency for Research on Cancer (IARC), 3 International Commission for Non-Ionizing Radiation Protection (ICNIRP), 9, 68 guidelines, 80, 106, 210, 211, 238 HPL, 137 limits, lowering, 209 limits, validity, 209 occupational basic restrictions, 212 plane wave exposure limits, 208 recommendations, 213 reference levels, 135 standards, 105 International Committee on Electromagnetic Safety (ICES), 9 International Electrotechnical Commission (IEC), 9 International mobile station equipment identity (IMEI), 142 International scientific messages, 9–11 INTERPHONE project, 3 Interstitial treatments, 228–29 Intracavitary microwave hyperthermia, 232 Inverse techniques, 34 In vitro technique, 37–38 In vivo technique, 37–38 Isotropic shaped-response probes, 145 IXS-070 spherical scanning system, 166

J Japanese anatomical head models, 97 Joule heating, 72

K Layered planar tissue model, 72 Linear array antennas, 77 Lipoclasty, 232 Liver tumors, 229 Loss peak radial frequency, 41 Loss tangent dielectric, 24 effective, 26

Index

M MAFIA software code, 103 Magnetic fields, orthogonal components, 121 Magnetic flux density, 23 Magnetic resonance imaging (MRI), 175 auditory implants and, 200 stents and, 202 Mass-averaging, 210–12 Maximum permissible exposure (MPE), 108 Maxwell equations, 23 Measurement (dielectric properties), 29–38 capacitive model, 31–32 coaxial dielectric probe, 31 impedance analysis, 33–34 inverse techniques, 34 in vitro, 35–37 in vivo, 35–37 nonresonant, 30–34 reflection methods, 30 resonant, 35–37 resonant-perturbation method, 36–37 resonator method, 35 transmission/reflection methods, 33 values, 46 waveguide measurements, 32–33 Measurements (2G), 134–53 base station activity determination, 140–43 broadband, 143–44 campaigns, 134–37 data acquisition and evaluation, 144–45, 147–53 narrowband, 146–47 procedures, 137–40 Measurements (3G), 153–58 need for, 153–54 UMTS downlink signal, 154–58 Measurements (near-field SAR), 165–72 dosimetric assessment system (DASY), 167 homogeneous liquids, 166 introduction to, 16–17 portable SAR systems, 169–71 SAR assessment system (SARA), 167–69 sources of inaccuracies, 171–72 Medical applications, 221–33 arthroscopic surgery, 231 conclusions and research, 232–33 electromagnetic therapy and hypothermia, 221–23 endometrial ablation, 230–31 gastric pathologies, 227 lipoclasty, 232 sleep breathing disorders, 230

257

therapeutic applications, 223–32 tumor ablation, 227–30 urological pathologies, 225–27 Membranous labyrinth, 48 Meshing strategies, 110–11 Metallic implants, 176 Metallic objects, 175–202 auditory implants, 200–201 electrodes, 180–83 eye implants, 177–80 piercings, 186–200 pins, 183–84 plates, 184–86 rings, 186–200 spectacles, 177–80 stents, 202 wire-leads, 180–83 See also SAR distributions Method of moments (MoM), 70, 100 with CIE, 100 with FEM, 100 Microwave ablation, for arrhythmia, 225 Microwave balloon angioplasty (MBA), 224–25 Microwave-induced heat, 228 Mobile network code (MNC), 142 MultiSAR, 166

N Narrowband equipment, 128–29 Narrowband measurements, 146–47 Narrowband probes, 128, 147–53 National Radiological Protection Board (NRPB), 13 Near-field numerical electromagnetic dosimetry, 93–111 averaging strategies, 109–10 meshing strategies, 110–11 phantom developments, 93–100 simulation techniques, 103–11 source modeling, 100–103 Near-field probes, 22 Near-field SAR measurements, 165–71 dosimetric assessment system, 167 introduction to, 165–67 portable SAR systems, 169–71 SAR measurement system (SARA), 167–69 sources of inaccuracies, 171–72 Near-field tests, 165 Nonresonant measurement, 30–34 capacitive model, 31–32 coaxial dielectric probe, 31

258

Index

Nonresonant measurement (continued) impedance analysis, 33–34 inverse techniques, 34 reflection methods, 30 transmission/reflection methods, 33 waveguide measurements, 32–33 See also Dielectric properties NORMAN, 95 adult model, 106 body model, 106 sagittal slices, 96 whole-body averaged SAR, 96, 97 NRPB restriction levels, 212

See also Metallic objects Power density for cylindrical waves, 78 decay, 73 deriving, 80 for evaporation, 53 incident, 207 NEC-calculated, 79 predictions, refining, 78 UMTS, 158 Preevaluation, 124–25 Prostate tumors, 229–30 Public perception of risks, 11

P

Q

Pennes’ bioheat equation, 53–54 Perfect electrical conductor (PEC), 102 Permittivity complex, 39–40 electric, 23, 24, 25, 59 materials worn by people, 38 in terahertz frequency range, 43 value variability, 47 Phantoms anatomical full-body, 76 defined, 71 generic twin (GTP), 98 near-field numerical electromagnetic dosimetry, 93–100 SAM, 171, 199 Physical Agents directive, 213 Piercings, 186–200 calculated and measured results, 194, 195 DASY4 Dosimetric Assessment System and, 193 diverse simulated results, 199 effects, 201 enhancement of SAR values, 190 peak SAR average, 190, 195 peak SAR distribution, 198 SAR distribution scenario, 196, 197 simulated SAR distribution, 196, 197 test setup, 199 types of, 192 See also Metallic objects Pins, 183–84 Plane wave exposure limits, 208 Plates, 184–86 modeling, 185 SAR enhancement, 186 SAR simulation, 185 types of, 184

Quadratic Shepard’s method, 167

R Radio frequency energy propagation, 22 Radio frequency identification (RFID), 211 Ray-tracing techniques, 83 description of dielectric properties, 83 full-wave methods with, 83 hybridized, 85 Regulations, 213–16 Australian, 213 Canadian, 213 E-field limits, 214, 215 EU, 213–14 German, 214 Israeli, 213 Italian, 213 Spanish, 214 Relaxation, 222 REMCOM model, 95 Resolution bandwidth correction factor, 148 Resonant methods, 35–37 resonant-perturbation method, 35, 36–37 resonator method, 35 See also Dielectric properties Resonant-perturbation method, 35, 36–37 Resonator method, 35 Retina stimulators, 177–78 RF ablation, 225 Rings, 186–200 Risks communication and perception, 11–13 driving, 11 electromagnetic therapy, 222–23 health, 10–11 public perception, 11

Index

S SAR assessment system (SARA), 165, 167–69 defined, 167–68 extensions, 169, 170 illustrated, 166 SARA2, 168–69 See also Specific absorption rate (SAR) SAR distributions, 48 dielectric materials and, 177 magnetic radiation and, 176 metallic objects and, 175–202 See also Specific absorption rate (SAR) SAR-WLAN, 166 Scientific Committee on Emerging and Newly Identified Health Risks (SCENIHR), 10 Scientific Committee on Toxicity, Ecotoxicity, and Environment (CSTEE), 9–10 SEMCAD averaging, 109–10 Short term mission (STM), 139, 140 Simulated exposure values, 110 Simulation techniques far-field numerical electromagnetic dosimetry, 82–85 near-field numerical electromagnetic dosimetry, 103–11 Single-instruction multiple-data (SIMD), 104 Sleep breathing disorders, 230 Slow associated control channel (SACCH), 142 Source modeling far-field numerical electromagnetic dosimetry, 76–82 near-field numerical electromagnetic dosimetry, 100–103 Spanish Association Against Cancer (AECC), 12–13 Specific absorption rate (SAR), 27–29 20-fold peak limit, 8 acceptance, 29 amplification factors, 181 averaged peak, 100, 179, 210 compliance, 100 defined, 27, 58 dependencies, 50 determination parameters, 59 dielectric tissue properties and, 49–50 difficulties, 28–29 evaluation, 28 increments, 8 layer average, 84 levels, 6 in limiting EMF exposure, 29

259

mass-averaged, 98 mobile handsets, 67 near-field measurements, 165–72 normalization, 21 NORMAN, 96, 97 numerical peak, 49 peak, 7 permittivity variability and, 47 thermometrically estimated, 56–57 time integral, 28 whole body, 67 worst-case scenario, 181 See also SAR distributions Specific absorption (SA), 28 Specific anthropomorphic mannequin (SAM), 98 comparison, 98 development, 98 phantoms, 171, 199 Spectacles, 177–80 effects on SAR, 178, 179 SAR averaged over eye with/without, 180 Spherical-wave far-field model, 82 Stents, 202 STROBE project, 3 Surface density, 23

T Temperature, 7–8 blood, 51 conductivity and, 28 dielectric property change with, 46–47 EMF-induced increase, 237 maximum increase, 239 RF exposure and, 55 steady state, 56 sweating rates and, 134 time to rise, 57 tissue, 51 TETRA, 239 Therapeutic applications, 223–32 arthroscopic surgery, 231 cardiac treatments, 224–25 conclusions and research, 232–33 endometrial ablation, 230–31 gastric pathologies, 227 lipoclasty, 232 sleep breathing disorders, 230 transurethral microwave thermotherapy (TUMT), 227 transurethral needle ablation (TUNA), 226–27

260

Therapeutic applications (continued) tumor ablation, 227–30 urological pathologies, 225–27 Thermal ablation, 221 Thermal conductivity, 51 Thermal properties, 56–57 Thermal therapy in cardiac treatments, 224 defined, 221 Thermoregulatory control, 54 Thermoregulatory mechanisms, 133 3D ray tracing propagation models, 83 Threshold limit, 14 Time-averaging, 210–12 Time division duplex (TDD), 154 Time-division multiplex access (TDMA), 141 extrapolation techniques based on, 124 frames, 141, 142 GSM basis, 141 Tissue bone, 45 brain, 45 dielectric, properties, 49–50 layered planar, 72 muscle, 45 skin, 45, 49 temperature, 51 testis, 46 thermal properties, 56–57 thyroid, 46 Total exposure quotient (TEQ), 139, 151 Transmission lines, 29–30 Transmission/reflection methods, 33 Transurethral microwave thermotherapy (TUMT), 227 Transurethral needle ablation (TUNA), 226–27 Tumor ablation, 227–30 coaxial-slot antenna in, 228 hyperthermia, 227–28 interstitial treatments, 228–29 liver tumors, 229 microwave-induced heat, 228 prostate tumors, 229–30 See also Medical applications Type approval code (TAC), 142

U UMTS Terrestrial Radio Access Network (UTRAN), 155

Index

Uniform theory of diffraction (UTD), 83 Universal Mobile Telecommunication System (UMTS), 29, 121 BS electromagnetic field measurements, 153 channelization, 155 chip rate, 154 downlink signal, 154–58 DS-CDMA, 154 emission values, 153 exposure evaluation, 153 power density, 158 quality performance, 154 radio interface, 153 scrambling, 155 signal quality, 154 transmission blocks, 158 uplink capacity, 154 WCDMA, 124, 154 Urban 120 base station antenna, 105 Urological pathologies, 225–27 transurethral microwave thermotherapy, 227 transurethral needle ablation, 226–27 See also Medical applications

V Visible Human Project (VHP), 75 Volume averaging, 212–13 Volumetric density, 23 Volunteer studies, 132–34 VSWR bandwidth criterion, 216

W Waveguide measurements, 32–33 Weekly statistical analyses, 124 Wideband CDMA (WCDMA), 124, 154 UMTS signal, 154 weekly statistical analyses, 124 See also Code division multiple access (CDMA) World Health Organization (WHO), 9, 10 Worst-case scenarios (WCS) compliance testing, 158

Y Yale body model, 75

Recent Titles in the Artech House Electromagnetic Analysis Series Tapan K. Sarkar, Series Editor

Advances in Computational Electrodynamics: The Finite-Difference Time-Domain Method, Allen Taflove, editor Analysis Methods for Electromagnetic Wave Problems, Volume 2, Eikichi Yamashita, editor Analytical and Computational Methods in Electromagnetics, Ramesh Garg Analytical Modeling in Applied Electromagnetics, Sergei Tretyakov Applications of Neural Networks in Electromagnetics, Christos Christodoulou and Michael Georgiopoulos CFDTD: Conformal Finite-Difference Time-Domain Maxwell’s Equations Solver, Software and User’s Guide, Wenhua Yu and Raj Mittra The CG-FFT Method: Application of Signal Processing Techniques to Electromagnetics, Manuel F. Cátedra, et al. Computational Electrodynamics: The Finite-Difference Time-Domain Method, Second Edition, Allen Taflove and Susan C. Hagness Electromagnetic Waves in Chiral and Bi-Isotropic Media, I. V. Lindell, et al. Engineering Applications of the Modulated Scatterer Technique, Jean-Charles Bolomey and Fred E. Gardiol Fast and Efficient Algorithms in Computational Electromagnetics, Weng Cho Chew, et al., editors Fresnel Zones in Wireless Links, Zone Plate Lenses and Antennas, Hristo D. Hristov Grid Computing for Electromagnetics, Luciano Tarricone and Alessandra Esposito High Frequency Electromagnetic Dosimetry, David A. Sánchez-Hernández, Editor Iterative and Self-Adaptive Finite-Elements in Electromagnetic Modeling, Magdalena Salazar-Palma, et al. Numerical Analysis for Electromagnetic Integral Equations, Karl F. Warnick Parallel Finite-Difference Time-Domain Method, Wenhua Yu, et al.

Quick Finite Elements for Electromagnetic Waves, Giuseppe Pelosi, Roberto Coccioli, and Stefano Selleri Understanding Electromagnetic Scattering Using the Moment Method: A Practical Approach, Randy Bancroft Wavelet Applications in Engineering Electromagnetics, Tapan K. Sarkar, Magdalena Salazar-Palma, and Michael C. Wicks For further information on these and other Artech House titles, including previously considered out-of-print books now available through our In-Print-Forever® (IPF®) program, contact: Artech House

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