Fatigue and muscle activation

Exp Brain Res (2002) 142:1–12 DOI 10.1007/s00221-001-0904-9

R E S E A R C H A RT I C L E

Daniel M. Corcos · Hai-Ying Jiang · Janey Wilding Gerald L. Gottlieb

Fatigue induced changes in phasic muscle activation patterns for fast elbow flexion movements Received: 3 January 2001 / Accepted: 7 September 2001 / Published online: 20 November 2001 © Springer-Verlag 2001

Abstract The present study investigated how muscle fatigue influences single degree-of-freedom elbow flexion movements and their associated patterns of phasic muscle activation. Maximal unfatigued voluntary isometric elbow flexor and extensor joint torque was measured at the beginning of the experiment. Subjects then performed elbow flexion movements over two distances as fast as possible, and movements over the longer distance at an intentionally slower speed. The slower speed was close to what would become the maximal speed in the fatigued state. Subjects then performed a fatiguing protocol of 20 sustained isometric flexion contractions of 25 s duration with 5 s rest at 50% maximal unfatigued voluntary force. After a recovery period they repeated the movements. The fatigue protocol was successful in inducing muscle fatigue, the evidence being decreased isometric maximal joint torque of over 20%. Fatigued movements had lower peak muscle torque and speed. Our principal finding was of changes in the timing of the D.M. Corcos (✉) · J. Wilding School of Kinesiology (M/C 194), University of Illinois at Chicago, 901 West Roosevelt Road, Chicago, IL 60680, USA e-mail: [email protected] Tel.: +1-312-3551708, Fax: +1-312-3552305 D.M. Corcos Department of Psychology, University of Illinois at Chicago, Chicago, IL 60680, USA D.M. Corcos Department of Neurological Sciences, Rush Medical College, Chicago, IL 60612, USA H.-Y. Jiang Department of Speech-Language Pathology, University of Toronto, 6 Queen's Park Crescent West, Toronto, Ontario M5S 3H2, USA J. Wilding Department of Physical Therapy and Human Movement Sciences, Northwestern University Medical School, Chicago, IL 60611, USA G.L. Gottlieb NeuroMuscular Research Center, Boston University, 19 Deerfield Street, Boston, MA 02215, USA

phasic patterns of fatigued muscle activation. There was an increase in the duration of the agonist burst and a delay in the timing of the antagonist muscle as measured by the centroid of the EMG signals. We conclude that these changes serve as partial but incomplete, centrally driven compensation for fatigue induced changes in muscle function. An additional, unexpected finding was how small an effect fatigue had on movement performance when using a recovery time of 10 min that is long enough to allow muscle membrane conduction velocity to return to normal. This raises questions concerning the behavioral significance of classical laboratory studies of human fatigue mechanisms. Keywords Motor control · Fatigue · Electromyography · Movement · Neural control

Introduction Motor control models help us relate changes in movement task to predictable changes in EMG pattern. For example, movements of longer distances or with heavier loads are associated with longer and larger agonist EMG bursts and delayed antagonist muscle activation (Berardelli et al. 1984; Gottlieb et al. 1989; Pfann et al. 1998). Movements performed over the same distance that are made more quickly are associated with larger, more steeply rising EMG bursts and earlier antagonist activation (Mustard and Lee 1987; Corcos et al. 1989). These studies changed movement by instruction or external conditions such as load, target position or target size. Movement also changes when muscles fatigue, a condition deliberately avoided in the studies cited above. Here we raise the question of whether, to reduce the kinematic consequences of muscle fatigue, there are compensatory neural adaptations that modify muscle activation patterns. If so, are those changes predictable from studies of unfatigued movement? There is much research on the neural mechanisms that underlie muscle fatigue (Gandevia et al. 1995b). Most

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studies examine changes in the electromyogram during steady state isometric contractions (Bigland-Ritchie et al. 1983b; Marsden et al. 1983; Garland et al. 1994; cf. Enoka and Stuart 1992), whereas relatively few studies have addressed changes that occur during movement. Berardelli and colleagues (1984), and Tschoepe et al. (1994) found fatigue induced slowing and increased the duration of the first agonist EMG burst. They suggested that the increase in the duration of the first agonist burst partially compensates for the decrease in maximal motoneuron firing frequency that had been observed in isometric contractions (Bigland-Ritchie et al. 1983a). Some recent studies, however, suggest that motor unit firing rates can increase during fatigue (Miller et al. 1996), and fire at very short interspike intervals (Griffin et al. 1998). Lucidi and Lehman (1992) found that although the kinematics of the movement after an hour of recovery were not distinguishable from those made before the fatiguing task, there remained an increase in the width of the first agonist burst. All three studies that investigated the time course of the agonist EMG suggest that fatigue causes changes in the temporal profile of the agonist electromyogram and, if the fatigue is great enough and the recovery interval is not too long, a slowing of the movements. The present study was intended to test three hypotheses related to the effects of muscle fatigue on patterns of muscle activation and movement performance. The first is that the way the CNS compensates for fatigue-induced muscle weakness is similar to its compensation for a heavier load. In both cases, we postulate that there are similar changes in the patterns of muscle activation to increase or maintain force output. These changes are prolongation of agonist activation, delay of antagonist activation and an increase in the peak amplitude of the agonist EMG with no change in the rate of rise of agonist muscle activation. This strategy, which we have termed a speed insensitive strategy (Gottlieb et al. 1989) for controlling movement distance as well as controlling load changes in unfatigued muscle, does not preserve movement time and therefore is an incomplete compensation for changing task conditions. The rationale for this hypothesis is based in part on previous studies showing fatigue induced temporal changes in agonist and antagonist EMG waveforms. We tested a second hypothesis that the EMG compensation under fatigued conditions would be greater for short movements than for long movements but that the reduction in peak velocity would be greater for long movements than for short ones. The rationale is that because short movements need lower forces and use less muscle activation, additional motor units might be available for compensatory recruitment. This is based on previous studies that have shown EMG increases for submaximal isometric contractions (Kirsch and Rymer 1987), and additional motor units being recruited in submaximal isotonic tasks (Miller et al. 1996). We tested a third hypothesis that the increase in agonist duration observed during fatigue would not be observed for unfatigued movements that were intentionally slowed to a fatigued speed. The rationale for this hypothesis is that the

neural control signals associated with weakness induced by neuromuscular fatigue are different from those associated with intentional reductions in movement speed.

Materials and methods Subjects Eight male subjects were used in this study. Males were selected because in laboratory protocols, they fatigue more rapidly than females (Scalzitti 1994). Our subjects were between the ages of 21 and 33 years, in good health, and without any history of joint or neuromuscular disease. They performed elbow flexion isometric and isotonic contractions and elbow extension isometric contractions with their right arms in the horizontal plane. All subjects gave informed consent according to University IRB protocols before participation in the experiment. Equipment A manipulandum was used to support the subject's forearm and restrict movement to one degree of freedom. A capacitative transducer on the axis of rotation of the manipulandum measured angular displacement. Joint acceleration was measured by a piezoresistive accelerometer mounted 47.6 cm from the center of rotation. A torque transducer was attached to the manipulandum. A torque motor was used to move the manipulandum so that the moment of inertia of each subject's forearm could be measured. Joint velocity was computed from the measured angle. Pairs of pediatric EKG electrodes were placed 2 cm apart over the bellies of the biceps brachii, and the lateral and long heads of triceps to measure the EMG signals that were amplified (×1600) and band pass filtered (60–300 Hz). Joint angle, acceleration and the EMG signals were digitized with 12-bit resolution by a data acquisition computer at a rate of 1000/s. Procedure The subject sat in a chair with his right arm abducted 90° away from his body on the manipulandum on which he grasped a vertical handle. The elbow joint was aligned with the rotational axis of the manipulandum. The manipulandum was locked in place for isometric contractions and rotated freely when movements were performed. A weight of 20 lb was added to the end of the manipulandum to increase the moment of inertia of the manipulandum to 2.28 kg.m2 in order to increase the force requirements during the movement and thus accentuate the effects of neuromuscular fatigue. Pilot experiments had shown that if the force requirements of the task are low, fatigue had little effect on either mechanical or EMG parameters. In addition, our previous work has shown that the EMG patterns of movements performed against both small and large inertias are qualitatively the same. The quantitative difference is that the EMG bursts are longer and larger for larger inertias, and the antagonist is delayed (Gottlieb et al. 1989). A computer monitor was located in front of the subject. There was a cursor on the monitor to display the angular position of the manipulandum and give the subject feedback about the movement. A narrow green marker on the screen represented the starting position. A broad red marker was located as a target at the desired angular distance. The width of the broad marker corresponded to 9° of angular elbow rotation in all the experiments reported here. Subjects were instructed that when a computer-generated tone sounded, they should accurately move to the target zone as quickly as possible. They were asked to perform the following tasks. Maximal and 50% of maximal isometric contractions The manipulandum was locked in place at 90°. The subject performed four isometric flexions and four isometric extensions at

3 100% of his maximal voluntary contraction (MVC), and then four isometric flexions and four isometric extensions at 50% of the just measured maximal torque. The purpose of measuring 100% MVC torque was to determine the extent to which fatigue reduces maximal voluntary torque. The purpose of measuring 50% MVC was to be able to determine whether contractile fatigue has occurred. Contractile fatigue would result in an increase in EMG at a given level of torque (Kirsch and Rymer 1987).

Isometric fatigue protocol repetition 2 The subject repeated the fatigue protocol but did only 11 repetitions since the protocol was quite painful. These 11 repetitions were intended to restore the muscle's fatigued state. Rest period 2 The subject rested for the same interval as in Rest period 1 above.

Fast unfatigued flexion The subject performed 11 voluntary elbow flexions over 20° (55–75°, 0° being full elbow extension) and over 60° (55–115°) as fast as possible. The purpose of this was to determine the unfatigued mechanical and EMG parameters of fast voluntary movements over two fixed distances.

Fast fatigued flexions at distance 2

Intentionally slowed unfatigued flexion

Fatigued maximal isometric and 50% isometric

The subject performed 20 flexions of 60° at a speed that was 10% less than the unfatigued maximum velocity for the 60° distance. The purpose of this was to collect data in which speed was intentionally reduced in order to compare these data with movements in which speed was reduced by fatigue. Pilot studies had shown that our fatigue protocol for the longer movement distance reduced peak movement velocity by approximately 10%. The effect of fatigue on peak velocity was less than 10% for the shorter movements, and so we chose not to conduct this experiment at the shorter distances. To assist the subject, we monitored peak velocity and reported its value to the subject after each movement, along with encouragement, if necessary, to move faster or slower.

The subject again performed four isometric flexions and four isometric extensions at 100% of his maximal voluntary contraction (MVC), and then at 50% of his unfatigued MVC. The protocol developed by Kirsch and Rymer (1987) produces significant muscle fatigue. Fatigue causes a fall in the mean frequency of the EMG spectrum as a consequence of changes in conduction velocity in the muscle fibers. However, Kirsch and Rymer (1987) showed that 10 min of rest following the fatigue protocol returns the mean power frequency of the EMG signal to the prefatigue levels in both the biceps and the brachialis muscles. Thus, after 10 min, any changes in the electromyogram induced by fatigue can be attributed to factors other than changes in conduction velocity. Subjects practiced the whole experimental protocol once before they took part in the experiment. The time interval between practice and experiment was at least 48 h. Subjects did not do any intensive exercise before they participated in the experiment.

Isometric fatigue protocol repetition 1 The fatigue protocol consisted of 20 repetitions of a 50% MVC isometric flexion at the elbow joint for 25 s, followed by 5 s of rest between the repetitions.

The subject performed 11 voluntary elbow flexion movements as fast as possible over either 20° or 60°, whichever distance was not performed under Fast fatigue flexions above.

Data analysis Rest period 1 After the fatigue protocol, the subject rested for ten minutes to allow muscle membrane conduction velocity to return to normal values (Kirsch and Rymer 1987). In another group of four subjects, we used only a 2-min recovery period. We used two recovery time periods so that we could both minimize the effects of recovery time on motor performance (2-min recovery protocol), and collect data in which the EMG signal is not affected by changes in conduction velocity (10-min recovery protocol). Since the shorter recovery period causes ambiguities in interpreting EMG changes, the EMG signal is not analyzed for this recovery time period. However, the magnitude of the kinematic changes was larger for the shorter recovery interval and allows us to demonstrate the effectiveness of this fatigue protocol. Fast fatigued flexions at distance 1 The subject performed 11 voluntary elbow flexion movements as fast as possible either over 20° or over 60°. The order in which the distances were performed was counterbalanced such that half of the subjects performed the 20° movement before the 60° movement. These movements were analyzed to determine the mechanical and EMG parameters of fatigued muscle when completing voluntary movements.

The digitized EMG signals were full wave rectified and filtered with a 10-ms moving average window for plotting the EMG time series data (Fig. 1, Fig. 2, Fig. 5). The data in these figures were all aligned with respect to the onset of the agonist EMG. The following parameters were calculated. Isometric parameters 1. Maximal elbow torque (Nm): the maximal elbow torque in the isometric contraction. 2. Integrated EMG (arbitrary unit): the EMG was integrated over 200 ms centered about the time of peak isometric elbow torque. We chose this time interval since it was the longest time interval that all subjects maintained a steady-state maximum contraction in the fatigued condition. 3. Torque/EMG ratio: the peak of the torque in the 50% isometric condition divided by the EMG integrated over 200 ms centered about the time of peak isometric elbow torque. One data set was lost to equipment malfunction, and so these data were only collected on seven subjects. Movement parameters 1. Movement time (ms): the time interval from 1% of peak acceleration to the time when the velocity falls to 5% of peak velocity. 2. Peak velocity (Vmax–deg/s): The largest value of movement velocity.

4 3. Peak elbow torque (Nm): for voluntary movement, elbow torque was the maximum muscle torque during the acceleration phase of the movement. Elbow torque was calculated by multiplying acceleration by the effective moment of inertia (forearm plus manipulandum). 4. Q30 (arbitrary unit): the integral of the agonist EMG signal from the visually marked onset to 30 ms thereafter. This parameter is used to characterize the initial slope of the agonist EMG burst. 5. Qag (arbitrary unit): the integral of the agonist EMG from the marked onset to the time of peak velocity. This parameter is used to characterize the area of the first agonist EMG burst which is responsible for the limb accelerating towards the target. 6. Qant (arbitrary unit): the integral of the antagonist EMG from the marked onset of the agonist burst to the end of the movement (the distance at which velocity drops below 5% of Vmax). This parameter is used to characterize the area of the antagonist burst. 7. Agonist EMG peak amplitude (arbitrary unit): the EMG peak amplitude was measured as the maximal value in the filtered and averaged agonist burst. 8. Cant ms: the centroid of the antagonist burst. This value is calculated by the following equation: (1) u (t)=1 if emg(t)≥K emgmax u (t)=0 if emg(t)
Results The results are divided into four parts. Part 1 describes the effects of fatigue on isometric muscle torque and EMG. Part 2 describes the effects of fatigue on movement kinematics and EMG patterns. Part 3 compares the EMG patterns of intentionally slowed unfatigued movements with those of fatigue-slowed movements. Part 4 compares the kinematic effects of a 2-min recovery interval with that of a 10-min recovery interval.

Changes in muscle torque and EMG in maximal voluntary contractions On average there was a statistically significant decline of 21.2% in flexion torque [mean±SE pre-fatigue= 69.1±4.2 Nm, fatigued=54.5±4.3 Nm, t(7)=5.98, P=0.001]. From this fact we conclude that the protocol developed by Kirsch and Rymer (1987) was effective in producing fatigue in the agonist biceps muscle. This reduction in maximum flexion torque is shown for a representative subject in Fig. 1A. Even though the fatigue protocol did not call for strong contraction of the extensor muscles, maximum extension torque was reduced 4.1% following the fatigue protocol as shown in Fig. 1B, but the decline was not statistically significant [mean± SE pre-fatigue=43±2.66 Nm, fatigued=41.2±3 Nm, t(7)=1.18, P=0.278]. The integrated EMG during MVC activity was not statistically significantly different between the fatigued and unfatigued conditions for either the biceps muscle in flexion [t(7)=1.99, P=0.087] or the triceps muscle in extension [t(7)=1.82, P=0.111]. In the agonist muscle, the ratio of torque to EMG, the measure usually considered the defining characteristic of physiological fatigue, was significantly smaller in the fatigued than the unfatigued state in the 50% MVC condition [mean ratio±SE pre-fatigue=85.96±13.32; mean ratio fatigued=55.12±10.3, t(6)=2.73, P=0.03]. Comparison between fatigued movements and unfatigued movements Fatigue decreased movement velocity and increased movement time. The data from one representative subject are shown in Fig. 2. The peak elbow torque in the acceleration phase of the movement decreased. The initial rising phase of the EMG (Q30) in the agonist is similar. However, the rate of rise was not sustained with fatigue and, as a consequence, the EMG peak amplitude of the biceps muscle decreased. These observations apply to both 20° and 60° movements. The late component of the antagonist burst (beginning approximately 160 ms after the agonist onset) is delayed in both the lateral head of triceps and the long head of triceps as a consequence of fatigue. These findings are summarized in Fig. 3 and Fig. 4 and in Table 1 for all eight subjects. There was no change in movement amplitude with respect to fatigue or distance. Movement time significantly increased by 7.38% (averaged over 20° and 60°), and was longer for longer movements. Movement time can be partitioned into both acceleration time and deceleration time. Acceleration time increased significantly while deceleration time was unchanged. There was a statistically significant interaction between fatigue and distance for peak movement velocity. As such, paired t-tests were performed on both the 20° movements and the 60° movements. This analysis showed that fatigue significantly decreased peak velocity in the 60° movements by 7.2% [t(7)=–4.33,

5 Fig. 1 Averaged maximum voluntary isometric contractions in flexion (A) and extension (B) for a representative subject. The data depict elbow torque, biceps EMG, and lateral head of triceps EMG. The data are from subject 7

P=0.003] while the decrease in peak velocity in the 20° movements (4.89%) did not quite reach statistical significance [t(7)=–2.16, P=0.067]. Peak elbow torque dropped significantly (by 15.22% averaged over 20° and 60°). Q30 dropped by 24.95% (averaged over 20° and 60°) as a result of fatigue but this result was not statistically significant. Inspection of the data of individual subjects showed that Q30 dropped by as much as 50% in one subject, and not at all in other subjects. The agonist peak amplitude dropped significantly (by 30.53% averaged over 20° and 60°). The integrals of the agonist burst (6.83% decrease) and antagonist EMG burst (2.06% decrease), averaged over 20° and 60°, did not change significantly. However, the timing of the centroid of the agonist burst (14% change) and the antagonist burst (12% change), averaged over 20° and 60°, occurred significantly later in the fatigued condition.

Comparison between the intentionally slowed unfatigued movements and fatigued movements Before performing the fatigue protocol, subjects performed 20 movements over 60° at a peak velocity that was 10% less than their unfatigued maximal speed. From this set of 20 movements, we later selected those that were closest to the maximal speed of the fatigued movements. The average number of trials that were selected as the “intentionally slowed pre-fatigued movements” was 10 (range 6–17). Intentionally slowed pre-fatigued movements were kinematically indistinguishable from fatigued movements but the patterns of muscle activation differed as shown in the time series plot for one subject in Fig. 5. A paired t-test was used to determine if there were significant differences in selected movement and EMG parameters between fatigued and intentionally slowed pre-fatigued movements. There were no significant differences in movement amplitude, movement time, peak velocity, Q30, the peak of the agonist burst or the integral

6 Fig. 2 Averaged position, velocity, elbow torque, biceps (agonist) EMG, lateral head of triceps (antagonist), and long head of triceps EMG for movements over 20° (A) and 60° (B). The data are averaged over 11 trials. Movements were performed prior to the fatiguing protocol (pre-fatigue) and following the fatigue protocol (fatigued). The data are from subject 4

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of the antagonist burst as shown in Table 2. However, the integral of the agonist burst was significantly larger in the fatigued movements. The centroid of the fatigued agonist burst (Cag) was significantly later which indicates an increase in EMG burst duration, and is consistent with the fact that burst area increased although burst peak amplitude did not. The centroid of the antagonist burst (Cant) was significantly later in the fatigued movements than the intentionally slowed pre-fatigued movements. This is consistent with the fact that it was an increase in acceleration time that produced an increase in movement time in the fatigued movements. The data in Fig. 6 depict Cag (part A) and Cant (part B) in the prefatigue condition, the fatigued condition and in the intentionally slowed pre-fatigued condition. Effect of fatigue recovery interval All the fatigue measures above were made after the subjects had a 10 minute recovery period so that muscle conduction velocities would return to normal (Kirsch and Rymer 1987). To confirm the return of membrane conduction velocity to pre-fatigue levels, a power spectrum analysis was performed on agonist EMG data from the isotonic movements. There is a methodological issue in performing a power spectrum analysis on EMG data from isotonic movements. Normally, median frequency is calculated on steady state data (e.g. Kirsch and Rymer 1987). The EMG bursts of isotonic movements are not stationary and rarely exceed 300 ms in duration. We calculated median frequency using 300 ms of data starting from the marked agonist onset and padded with 700 ms of zeros. This method examines frequency changes in the agonist burst with a resolution of 1 Hz (DeLuca 1985). Consistent with the findings of Kirsch and Rymer (1987), with 10 min of recovery, we found no statistical difference in median frequency when comparing pre-fatigued to fatigued movements [mean 20°: pre=72.4 and post=73.1; mean 60°: pre=71.0 and post=73.1; F(1,7)= 0.22, P=0.65]. We also performed a study on four subjects with only two minutes of recovery (Jiang 1996). All of the kinematic effects described above were larger in this group of four subjects. Peak velocity of 60° movements dropped by 25% after 2 min of recovery but only by 7.2% after 10 min as shown in Fig. 3D. For 20° movements, the drop was 11.9% after 2 min of recovery and 4.89% after 10 min. These results show that 10 min of recovery allows not only recovery in muscle fiber conduction velocity but also substantial recovery in kinematic performance. Reduction of muscle fiber conduction velocity increases the magnitude of the recorded EMG waveform. Fig. 3 Movement time (A), acceleration time (B), deceleration time (C), peak movement velocity (D) and peak elbow torque (E) for 20° (dashed line) and 60° (solid line) movements are shown in pre-fatigue and fatigued states. The data are averaged over eight subjects. The data are mean±SE

8 Fig 4 The integral of the first 30 ms of the agonist EMG (A), the agonist peak amplitude (B), the integral of the agonist burst (C), the integral of the antagonist burst (D), the centroid of the agonist (E), and the antagonist (F) for 20° (dashed line) and 60° (solid line) movements pre-fatigue and fatigued. The data are averaged over eight subjects. The data are mean±SE

Table 1 Effects of fatigue and distance. The results of two-way factorial repeated measures ANOVA on eight subjects comparing pre-fatigue movements and fatigued movements and movements Fatigue Pre vs Post

Movement amplitude Movement time Peak velocity Acceleration time Deceleration time Peak elbow torque Q30 Agonist peak Qag Qant Centroid agonist Centroid antagonist

over two different distances. All degrees of freedom for the statistical analysis are 1, 7 Distance 20° vs 60°

Interaction Fatigue by Distance

F

P

F

P

F

P

0.38 35.14 12.79 11.85 0.02 74.63 3.33 13.66 1.30 0.32 14.94 46.84

0.555 0.001 0.009 0.011 0.882 0.000 0.111 0.008 0.291 0.591 0.006 0.000

7942 187.1 2002 81.81 90.99 14.55 0.46 8.22 39.35 10.61 111.9 183.1

0.000 0.000 0.000 0.000 0.000 0.007 0.519 0.024 0.000 0.014 0.000 0.000

0.029 0.46 26.68 0.46 0.26 0.91 2.95 0.01 0.28 0.26 0.05 0.35

0.869 0.520 0.001 0.52 0.63 0.371 0.130 0.925 0.614 0.624 0.833 0.572

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Fig. 6 The centroid of the agonist (A) and the centroid of the antagonist (B) in the pre-fatigue condition, the fatigued condition and in the intentionally slowed pre-fatigue movement condition. The data are mean±SE

This increase could be confused with an increase in recruitment or firing frequency. Therefore, even though the changes in EMG reported after 10 min of recovery were also seen after 2 min, we have not presented those results, since their interpretation is open to question.

Discussion

Fig. 5 Averaged position, velocity, elbow torque, biceps EMG (agonist) and lateral head of triceps EMG (antagonist) for intentionally slowed pre-fatigue movements and fatigued movements. The data are from the same subject as in Fig. 2

Our first hypothesis was that the rules that the CNS uses for compensating for a fatigue-weakened muscle are the same as those for compensating for a larger inertial load. Our reasoning is that it is the change in the ratio of required to available force that drives the compensatory strategy. This implies that it does not matter whether the ratio changes because the muscle gets weaker or the load gets heavier. This strategy has three principal rules: prolonged agonist activation, delayed activation of the late component of the antagonist burst, and no change in the rate at which the agonist EMG burst rises. This hypothesis was confirmed by the data. One additional finding is that the peak agonist EMG is reduced which was not predicted. This change would tend to reduce muscle force and therefore speed, which would be kinematically noncompensatory. On the other hand, by reducing muscle activation, this would tend to slow the progression of fatigue, an effect that might be desirable but is incompatible with kinematic compensation. Our second hypothesis was that the EMG changes would be greater for short movements than for long movements but that the kinematic effects of fatigue would be greater for long movements than for short ones. We found that the degree of slowing was indeed

10 Table 2 A comparison of fatigued movements and intentionally slowed pre-fatigue movements. The results of paired sample t-tests on the data of eight subjects when comparing the intentionally slowed pre-fatigue movements with the fatigued movements. The data are averaged over eight subjects (mean±SE)

Movement amplitude Movement time Peak velocity Q30 Peak of agonist burst Integral of agonist burst Integral of antagonist burst Centroid of agonist burst Centroid of antagonist burst

greater for longer distance movements than for shorter distance movements. However, the EMG did not show greater changes for shorter movements than for longer movements, which is in contrast to the findings of Berardelli and colleagues (1984). This hypothesis, therefore, was not confirmed by the data. We tested a third hypothesis that the EMG patterns associated with fatigue-induced slowing would differ from those of intentional slowing. This hypothesis was confirmed by the data. These findings question whether the reduction in torque during movement is exclusively a consequence of “peripheral, contractile fatigue”, i.e. a decrease in the capacity of the biceps to generate force. It might also represent a change in the way the CNS activates the muscle that would serve to slow the progression of fatigue. An additional interesting finding is the fact that movement velocity was reduced by less than 10% after ten minutes of recovery. This finding is consistent with that of Raastad and Hallén (2000), who showed a 12–14% reduction in isokinetic performance following a high-intensity exercise protocol, and a 6–7% reduction after a moderate intensity protocol with a recovery time of 5–20 min. The finding is also supported by the work of Miller et al. (1987), who showed that a 4-min fatiguing protocol can reduce MVC to less than 10% but that it returns to almost 90% after 10 min of recovery. We also used a large load to increase the effects of fatigue as much as possible during the movement. Thus we believe that we achieved a level of fatigue that was typical of what has been done by many others. These results all demonstrate that despite the fact we know how to fatigue a muscle in order to produce an arbitrary decrement in isometric force, it is exceedingly difficult to produce substantial decrements in movement speed, while also allowing sufficient time for conduction velocity to return to normal. Peripheral fatigue We can draw conclusions similar to those of Kirsch and Rymer (1987), and Griffin et al. (1998) about decreases in dynamic torque/EMG ratios from our isometric and movement data. When fatigued, our subjects showed an

Intentionally slowed

Fatigued

Significance

Mean±SE

Mean±SE

t

P

62.18±0.41 711±15 183±4 4.00±0.623 0.999±0.198 156.1±22.8 245.1±39.3 163±8 436±10

62.8±0.61 725±19 185±4 4.72±0.934 0.995±0.171 190.1±27.9 253.6±33.8 178±9 461±10

–1.15 1.68 0.93 1.41 0.04 2.44 0.71 3.56 2.78

0.287 0.137 0.386 0.201 0.968 0.045 0.499 0.009 0.027

increase in EMG during a 50% MVC isometric contraction. Fatigue also produced a decrease in peak elbow torque during isotonic movements without a significant change in the area of the agonist burst. Both findings reveal a decrease in the torque/EMG relationship. Such observations are also consistent with a number of other studies (Edwards and Lippold 1956; Hagberg 1981; Maton and Gamet 1989; Garland et al. 1994; Miller et al. 1996; Potvin 1997). These findings define the presence of a peripheral fatigue component, a diminished ability of muscle to produce force. Central fatigue and rules for muscle activation The presence of peripheral fatigue does not rule out central fatigue as an additional factor. Central fatigue during exercise has been defined by Gandevia et al. (1995a) as: “The decrease in muscle force attributable to a decline in motoneuronal output” (p. 281). Three of our measures of the strength of activation, Q30, Qag and Qant were slightly reduced by fatigue, but none of the changes reached statistical significance. The largest and most variable reduction was in Q30, which suggests that some subjects reduce the initial excitation of the muscle when fatigued but others do not. The peak of the agonist burst was significantly reduced by fatigue and this could have reduced peak muscle force. Hence, using Gandevia's definition, there is evidence for central fatigue in only one of our four measures of motoneuronal output. However, the timing of the EMG bursts in both agonist and antagonist muscles was changed by fatigue to a degree that could not be predicted by the way subjects intentionally slow their movements. Fatigue prolonged the agonist burst. If the level of muscle activation is unchanged, this increases the force output of the muscle. Were the CNS not to do this, the movement would be even slower. Hence, this prolongation is compensatory for the effects of peripheral fatigue and is consistent with the changes seen when moving a heavier inertial load in the unfatigued state. However, the compensation is not complete and the fatigued movement is, never the less, slower than the unfatigued movement. Since the fatigued movement time is greater than that of an unfatigued movement, delay of the antagonist is

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biomechanically appropriate. However, fatigue delayed the antagonist burst to a degree that exceeded the amount we would expect from the antagonist timing of unfatigued movements of a similar speed. Furthermore, since the fatigued movement's prolongation is due almost entirely to prolongation of the acceleration time, and this is not true of unfatigued movements with equal movement times, it is also appropriate that the antagonist burst that leads to decelerating torque be slightly more delayed. This additional delay of the antagonist burst, like the prolongation of the agonist burst, tends to increase movement speed and may prevent stopping the movement too soon. The limb's final resting position depends on coactivation of the flexor and extensor muscles to create a position of equilibrium. To perform an accurate movement, the point at which movement speed reaches zero during the deceleration phase should coincide with this equilibrium position. This requires a delay in braking and hence a delay in antagonist onset. How should we describe these changes? They do not fit Gandevia's definition of central fatigue since there is no overall decline in motoneuronal output. In fact, they do not represent central fatigue if by that term, we wish to imply something that diminishes motor performance. We suggest that these changes represent a “central fatigue strategy.” By this we mean that the CNS changes the patterns of muscle excitation in order to reduce the effects of peripheral fatigue (as in agonist prolongation) and prevent moving incorrect distances due to peripheral fatigue (as in antagonist delay). The reduction seen in peak agonist EMG might also be considered part of a central fatigue strategy. This reduction in peak agonist EMG could be attributable to lower motoneuron firing rates, so-called muscle wisdom (Marsden et al. 1983), that are sufficient to fully activate a muscle in the fatigued state secondary to the concurrent reduction seen in muscle fiber relaxation rate when fatigued. This might serve to prevent neuromuscular transmission failure. It is also worth noting something that we did not find to be part of a central fatigue strategy. We know that submaximal isometric torque can be preserved in a fatigued muscle by stronger activation of the muscle. Our second hypothesis raises the question of whether subjects have a reserve of performance that they can use, despite instructions to move as fast as possible. This reserve of performance can usually be exploited only by extensive practice (Corcos et al. 1993). If true, then in the presence of peripheral fatigue, subjects could, in theory, compensate more fully by harnessing that reserve. To do this they would increase the initial firing rates and number of recruited motor units and this would be observed as an increase in Q30. We had predicted that if this were the case, compensation would be greater for shorter movements than longer ones. This was based on the rationale that shorter movements require lower forces and therefore less muscle activation, leaving a reserve of motor units that could be recruited. We did not find this. Hence, either our subjects had a reserve that they were not sufficiently motivated to use, or contrary to our supposition,

the reserve does not exist. These experiments do not allow us to decide this issue. That the reserve does not exist is supported by the fact that Q30 was the same for both short and long movements in the unfatigued state. Additionally, it has been shown that subjects can produce maximum or near maximum voluntary activation of their muscles under laboratory conditions (see Gandevia et al. 1998), thus suggesting that under these conditions, a reserve does not exist. Finally, what is the relationship between the fatigue we have studied and the fatigue that is experienced as the consequence of sustained hard work or exercise? One possibility is that exercise fatigue (as we might call it) is simply greater and less well compensated. If so, were we to repeat our fatigue protocol enough times, we would get larger and more significant effects. The protocol we used was difficult and unpleasant so such an experiment would not be easy to perform. Another possibility is that using a less intense and noxious protocol over a longer period of time would produce more profound and less compensated fatigue. This should be explored. A third possibility is that the behavioral consequences of exercise fatigue are different from the slowing of elbow flexions that we are measuring here. This would suggest that exercise fatigue is not simply a loss of muscle strength due to muscular and neural factors, but a loss of coordination among muscles, a very different effect, and one that is not expressed by the study of single-joint movement. This too should be explored. Acknowledgements This study was supported in part by the National Institute of Arthritis and Musculoskeletal and Skin Diseases Grant R01-AR 33189 and by the National Institute of Neurological and Communicative Disorders and Stroke Grants K04-NS 01508, R01-NS 28127 and RO1-NS40902. We would also like to acknowledge the valuable comments of Dr. Ziaul Hasan, and the advice of Dr. Paolo Bonato and Dr. David Vaillancourt.

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