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Fatigue effects on motor unit activity during submaximal contractions
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Fatigue Effects on Motor Unit Activity During Submaximal Contractions Robin A. Conwit, MD, Dan Stashuk, PhD, PEng, Hiromasa Suzuki, MD, Nicole Lynch, PhD, Matthew Schrager, MA, E. Jeffrey Metter, MD ABSTRACT. Conwit RA, Stashuk D, Suzuki H, Lynch N, Schrager M, Metter EJ. Fatigue effect on motor unit activity during submaximal contractions. Arch Phys Med Rehabil 2000;81:1211-6. Objective: To examine motor unit changes during the development of fatigue in healthy subjects. Design: Automated decomposition-enhanced spike-triggered averaging was used to characterize motor unit size and firing rate in the dominant vastus medialis during maintained contractions at 10% and 30% of maxima voluntary contraction (MVC). Setting: Academic outpatient neuromuscular clinic. Participants: Healthy laboratory personnel. Main Outcome Measures: Surface electromyogram, surfacedetected motor unit action potential amplitude (S-MUAP), mean firing rate, force (MVC), motor unit index. Results: Surface electromyogram values and S-MUAP amplitudes increased during both 10% and 30% MVC fatiguing contractions, while mean firing rates decreased. A motor unit index, indicating the degree of motor unit pool activation, increased similarly to S-MUAP size, implying that new and larger units were recruited to maintain the contraction. Repeated contractions led to earlier motor unit changes and fatigue. Conclusion: During submaximal fatiguing contractions, additional motor units are activated to maintain strength. These changes begin early, within the first minute, particularly after a previous fatiguing effort. Key Words: Fatigue; Electromyography; Action potentials; Isometric contraction; Rehabilitation. r 2000 by the American Congress of Rehabilitation Medicine and the American Academy of Physical Medicine and Rehabilitation
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EUROMUSCULAR FATIGUE is sometimes defined as ‘‘an inability of a muscle or group of muscles to sustain the required or expected force.’’1 With respect to motor unit physiology, fatigue may be better defined as the changes in nerve and muscle physiologic and biochemical processes used to produce muscle force that eventually result in the inability to maintain a contraction.2 Fatigue is a frequent problem encountered during rehabilitation and in exercise physiology. Under situations where muscle contraction must be maintained for
From the Department of Neurology, Johns Hopkins Bayview Medical Center (Conwit), and the National Institute on Aging, Gerontology Research Center (Metter), Baltimore; University of Maryland, College Park, MD (Lynch, Schrager); Department of Systems Design Engineering, University of Waterloo, Ontario, Canada (Stashuk); and Department of Rehabilitation Medicine, Dokkyo University School of Medicine, Dokkyo, Japan (Suzuki). Accepted February 14, 2000. No commercial party having a direct financial interest in the results of the research supporting this article has or will confer a benefit upon the authors or upon any organization with which the authors are associated. Reprint requests to Robin A. Conwit, MD, Department of Neurology, Johns Hopkins Bayview Medical Center, Baltimore, MD 21224. 0003-9993/00/8109-5850$3.00/0 doi:10.1053/apmr.2000.6975
extended periods, fatigue can limit the performance of both patients and athletes. Fatigue can limit recovery after sustained bed rest and during recuperation from illness. Fatigue contributes to disability, particularly in the elderly, for whom daily activities may require a higher percentage of potential strength than in younger individuals, leading to earlier and prolonged fatigue. Although there are several research-oriented fatigue indices that explore mechanisms contributing to fatigue, there are few objective, clinically obtainable markers for fatiguing motor units.3-5 Understanding the relation between fatigue and motor unit physiology in a clinical setting may be important because motor units are the fundamental contributors to muscle contraction and ultimately are directly involved in the development of fatigue. Sustained fatiguing contractions can be of two types based on a maximal or a submaximal contraction. It is well established for the cat gastrocnemius muscle that motor units developing the smallest tetanic tensions have relatively long twitch contraction times and are fatigue resistant. Stronger contracting units, on the other hand, have shorter contraction times and a broad range of fatigue resistance, the strongest units having the least resistance to fatigue.6,7 In an effort to avoid physiologic fatigue, the smallest, most fatigue-resistant motor units are recruited first. During maximal contraction, essentially all motor units are initially activated. To sustain the contraction as long as possible, motor units reduce firing rates, resulting in a gradual loss of force during the contraction, referred to as ‘‘muscle wisdom.’’1,8,9 Based on muscle wisdom, motor unit firing rates should decrease even though force generation decreases during a sustained maximal contraction. This mechanism has indeed been observed by most investigators during sustained maximal isometric contractions.1,8,10 At the same time, the mean absolute surface-detected electromyogram (SEMG) signal amplitude increases with maximal contraction,11 suggesting an increased synchronization of the motor unit firing. Conversely, during submaximal contractions the firing rate response varies, with greater emphasis on motor unit recruitment.12 Enoka and associates13 found an increased mean firing rate of newly recruited single motor units in first dorsal interosseous muscles in short duration submaximal contractions. In a subsequent study,14 they found a different response in biceps brachii. Others have also seen variable firing patterns.12 These differences may also be a function of the different recruitment and rate coding strategies of various small muscles, such as the first dorsal interosseous or abductor pollicis brevis, versus the larger biceps or deltoid.2,15 The impact of training on the motor unit can be seen in the work of Chan and colleagues,3 who trained motor units three times a week for 7 to 11 weeks using 40Hz stimulation. During the training period, some motor units responded with a gradual increase in strength, while other units showed a clear decline in force generation over many weeks. The decline in strength likely resulted from excessive fatigue of the motor unit resulting in an inability to completely recover across training sessions. When training ceased, units that had either increased or decreased in strength slowly returned to their baseline strength. Arch Phys Med Rehabil Vol 81, September 2000
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The implications are that motor units respond differently to training and rehabilitation. Motor unit physiology in neuromuscular disease can result in greater levels of fatigue after exercise combined with incomplete recovery of function. Most functional activities can be completed using submaximal contractions. Seldom in practical daily activities is sustained maximal voluntary strength capacity used. For this reason, we were interested in characterizing motor unit activity during submaximal contractions maintained at levels close to the range of strength used during daily activities. Although previous studies have examined motor unit firing rates and EMG signal amplitude, most have examined only short periods of contraction, only studied a few motor units, or utilized only S-EMG parameters, and few have studied repeated fatiguing contractions preceded by a period of rest.16 This study describes average motor unit firing rates and surface-detected motor unit action potential (S-MUAP) amplitude during multiple trials of submaximal contractions maintained to exhaustion with 30 minutes of rest between efforts. Subjects were studied as they produced 10% and 30% of their maximal strength on separate days. The questions of interest were: (1) Do changes occur in average motor unit firing rate and average S-MUAP amplitude during maintained submaximal muscle contractions? (2) Are there differences in the time course of these average motor unit characteristics during 10% and 30% of maximal contractions? (3) Do the time courses of these average motor unit characteristics change across repeated fatiguing contractions? (4) Could this approach be reasonably applied in a clinical setting to study fatigue? We have approached the problem by using decompositionenhanced spike-triggered averaging during sustained submaximal contractions. Decomposition-enhanced spike-triggered averaging is a clinical tool based on traditional EMG techniques.17-19 The method used allows for the measurement of surface- and needle-detected motor unit activity in 20- to 30-second epochs of time during a muscle contraction. The signal decomposition algorithms identify motor unit firings based on the shape of their MUAPs (as detected by an intramuscular electrode) and firing pattern. The contribution of each motor unit to the S-EMG is then examined over the full epoch. Sequential epochs can be examined during the course of a maintained contraction; however, each epoch may identify a different group of motor units. Thus, what is observed is a sampling of motor units during different periods of a maintained submaximal contraction. This approach is different from studies that examine the same individual motor units over the entire course of a contraction. In this study, we used this technique to examine fatigue. Variations of this technique have been used previously by Stashuk and coworkers.17-19 In previous reports, we have shown that in the quadriceps femoris the average size of S-MUAPs increases linearly with increasing levels of force,20 while the mean firing rate increases only at higher force levels.21 METHODS Seven healthy individuals volunteered for the study. All were free of neuromuscular disease, considered themselves to be in good to excellent health, and remained healthy over the subsequent 4 years. The study was approved by the Johns Hopkins Bayview Medical Center Institutional Review Board. Maximal Voluntary Contraction Subjects performed three maximal voluntary isometric contractions (MVCs) of the dominant knee extensors on a KinCom dynamometera with 30 seconds of rest between trials to Arch Phys Med Rehabil Vol 81, September 2000
determine maximal strength. The force measurement was calibrated by positioning and stabilizing the lever arm level to the floor. Details of the strength collection protocol have been published.20,21 Fatigue Protocol Subjects performed three separate contractions of the quadriceps at 30% MVC and maintained each contraction to exhaustion. Subjects rested for 30 minutes between each submaximal contraction. On a separate day, this procedure was repeated but with subjects maintaining a quadriceps contraction at 10% MVC, and the 10% MVC was repeated only once after a 30-minute rest period. All recording and ground electrodes were TECAb 3.0-cmdiameter silver-silver chloride recording surfaces. During all contractions an active surface electrode was placed over the motor point of the vastus medialis muscle, which was determined by moving the surface electrode until the maximum compound muscle action potential (CMAP) with minimal rise time was detected following supramaximal surface stimulation of the femoral nerve in the groin. An inactive surface electrode was placed on the patellar tendon, and a ground electrode was placed on the lateral thigh between the stimulation and recording sites. Before each fatiguing contraction, a concentric needle electrode was inserted into the vastus medialis and positioned to maximize the amplitude of MUAPs generated by motor units with fibers close to the electrode. During the fatiguing contraction, needle- and surface-detected signals were acquired using sampling rates of 25 and 2.5kHz, respectively, during 20- to 30-second consecutive epochs. Thus, the time course of the fatiguing contraction could be divided into a series of epochs that represented 20 to 30 seconds each. For each epoch, from 1 to 9 motor units were identified and tracked by the algorithms. The needle signal was used to estimate the size of the S-MUAP of each motor unit tracked by the decomposition algorithms. The mean S-MUAP amplitude for the epoch was then computed as the difference between the maximum and minimum values. An epoch mean firing rate was calculated as the average of the mean firing rates of all motor units tracked by the decomposition algorithms over the 20- to 30-second epoch. The mean firing rate of a motor unit was calculated as the reciprocal of the mean inter–potential interval value of the main lobe of the motor unit’s inter–potential interval histogram provided by the decomposition algorithms.17 The EMG signal decomposition and average firing rate algorithms were developed by Stashuk and colleagues.17-19 The S-EMG amplitude was also used to examine the overall muscle activity during the course of the contraction. To assess the degree of activation of the motor unit pool, a motor unit index was defined as the mean absolute amplitude of the S-EMG, calculated over a 20- to 30-second epoch, divided by the product of the S-MUAP size and firing rate for that epoch. This is conceptually analogous to a motor unit number estimate that is obtained by dividing the average S-MUAP size into the CMAP obtained following maximal stimulation.22 The S-EMG value represents the average electric activity of all active motor units underlying the detection electrode during a contraction epoch. As more motor units are active, the S-EMG amplitude increases in proportion to the size and relative location of the units. Thus, the motor unit index is a rough indication of the number of motor units active during a contraction epoch. Statistical Methods All statistical analyses were computed with SPSS version 8.c A mean value was obtained for each variable from all motor
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units collected in any epoch for each subject. Average values across all 7 subjects for S-MUAP amplitude, firing rate, S-EMG, and a motor unit index were calculated for each epoch. The mean values were used in all figures. To allow comparison across subjects, data were presented with respect to a percentage of the total contraction time of each effort. Since the last epoch represented a ‘‘fall off’’ in muscle strength, ie, strength was not maintained throughout the 20 to 30 seconds, we eliminated data from the last epoch from the analysis. Data were then grouped into time periods from 0% to 19.9%, 20% to 39.9%, 40% to 59.9%, 60% to 79.9%, and 80% to 95% of the total time for each effort for graphing purposes. Each variable was also expressed as a percentage of its value measured during the initial epoch of the first effort. Because each subject had a different number of epochs that also differed between contractions, mixed effects models23 were used to examine the change in each variable over time using MLwiN.24 Such models deal with the repeated measures and the unbalanced design in relation to the time of the contractions. The models are of the form where b0i and b1i are random effects that reflect individual variation from the mean effect (b0, b1): Motor unit variable ⫽ (b0 ⫹ b0i) ⫹ (b1 ⫹b1i) ⴱ time ⫹ b2 ⴱ time2 ⫹ b3 ⴱ run 2 ⫹ b4 ⴱ run 3 ⫹ b5 ⴱ time ⴱ run2 ⫹ b6 ⴱ time ⴱ run3 ⫹ error. Time refers to the percentage of the total time of contraction. Based on the appearance of the data, the quadratic term for time was included. Run refers to the three efforts at 30% MVC or two efforts at 10%. Run2 contrasts the second effort with the first, and run3 contrasts the third with the first. The remaining terms reflected the interaction between time and which effort (time · run). All models were tested for significance at p ⬍ .05 using a chi-square distribution.24 RESULTS 30% MVC Six subjects (2 men, 4 women; age range, 23–49yr) sustained forces at 30% MVC for from 2 to 5 minutes during the first effort. During the second effort, times were slightly shorter, ranging from 1.5 to 3 minutes, and during the third effort, 1.0 to 2.5 minutes. Figure 1 shows results averaged over the six subjects for S-MUAP amplitude, firing rate, S-EMG, and the motor unit index obtained during the first, second, and third efforts. During the course of each effort, an increase was observed in the S-EMG, with the S-MUAP amplitude paralleling the changes observed in the S-EMG. In all three trials there was a decline in the firing rates. The motor unit index showed a progressive gradual increase in the first run only, suggesting that the number of active units was progressively increasing as the contraction was maintained. During the second and third efforts, the initial motor unit properties (firing rate, S-MUAP amplitude) had higher values than values measured during the initial epoch of the first effort. Also, the changes in motor unit parameters during the contraction were greater in the second and third efforts. A mixed effects model was used to examine the differences across efforts and time for each of the four variables (table 1). Significant time effects were found for all four measures ( p ⬍ .05), implying changes from the initial levels as fatigue progressed. The only significant interaction found between effort and time was for the motor unit index when comparing
Fig 1. Fatigue during 30% MVC. Graphs of S-EMG, mean firing rate (FR), motor unit index, and mean S-MUAP amplitude as a percentage of initial values obtained at the onset of the first effort versus time expressed as a percentage of total duration of the contraction. (A) first effort; (B) second effort after 30 minutes of rest; and (C) third effort after 30 minutes of rest.
the second to the first effort, implying that the number of active motor units changed differently with time during the second effort. Significant differences between effort were found for firing rate and S-EMG amplitude, but not for S-MUAP size. A Arch Phys Med Rehabil Vol 81, September 2000
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Table 1: Significance Levels From Repeated-Measure Analysis of Variance Models at 30% MVC
Effort Full model Univariate* Time Full model Univariate* Effort · Time: Full model Subject (Effort): Full model
S-MUAP Amplitude
Mean Firing Rate
S-EMG
Motor Unit Index
.126 .000
.002 .000
.02 .000
.993 .966
.000 .000 .011 .000
.001 .001 .904 .009
.000 .000 .085 .000
.006 .006 .055 .000
* Univariate represents post hoc analysis for effort and time.
random effect was observed for time showing that individuals performed somewhat differently during the efforts. 10% MVC Four subjects (1 man, 3 women; age range, 22–49yr) sustained this level of exertion for 15 to 35 minutes during the first effort, and for shorter time periods (13–16min) for the second effort after 30 minutes of rest. S-EMG and S-MUAP amplitude showed an approximately fivefold increase as the contractions proceeded during both efforts, while firing rate was relatively stable and the motor unit index increased slowly during the second effort (fig 2). The mixed effects analysis for 10% MVC (table 2) found that all four variables had significant changes over time. In addition, the quadratic term for time was significant for firing rate and for motor unit index. A significant interaction was found between the effort number and time for S-EMG amplitude, but not for firing rate, S-MUAP, or motor unit index. This suggests that S-EMG changed differently during the course of the two fatiguing efforts, while the motor unit measures behaved similarly. A significant random effect across efforts implied that subjects behaved somewhat differently with respect to their responses to fatigue. Comparing average motor unit characteristics with S-EMG amplitude revealed that the motor unit index stayed relatively constant across each effort. This observation suggests that particularly during the first effort 10% MVC, there was not a large increase in the number of active motor units over time. Effect of Changing MVC Over Time In our previous work,20,21 as percentage of MVC increased, S-MUAP amplitude increased linearly. The large increase in S-EMG and S-MUAP amplitude across time during the sustained contractions at 10% and 30% MVC suggested that as fatigue progressed a change in the percentage of MVC occurred during the course of the sustained contraction. To test this hypothesis, four subjects sustained contractions of 30% of initial MVC to fatigue, with the current MVC measured at 1-minute intervals. The current MVCs were measured between 30-second motor unit data collection epochs, following which the subjects immediately returned to maintaining the 30% of initial MVC. S-EMG and S-MUAP amplitude both increased over time, while firing rate declined (fig 3). At the same time, MVC declined by 30% to 40% during the course of the sustained contraction, so that the percentage of MVC eventually being maintained approached 50% (ie, 150% to 160% of the initial percentage of MVC being sustained during the contraction). The change in the percentage of MVC during the course of the contraction paralleled the changes observed in both S-EMG and S-MUAP amplitude, while the percentage Arch Phys Med Rehabil Vol 81, September 2000
Fig 2. Fatigue at 10% MVC. Graphs of S-EMG, mean firing rate (FR), motor unit index, and mean S-MUAP amplitude at 10% MVC for a percentage of initial values obtained at the onset of (A) the first effort and (B) the second effort, versus time.
decline in MVC was similar to the decline in firing rate. A mixed effects model was utilized to test whether the change in S-EMG amplitude was only explained by the changes in percentage of MVC being maintained. In the analysis, no random effects were found. S-MUAP amplitude, firing rate, and the increase in percentage of MVC represented by the force generated independently contributed to S-EMG amplitude changes ( p ⬍ .05). Thus, the change in MVC, ie, the relative increase in percentage of MVC maintained, was not the only factor that accounted for the large increases in S-EMG amplitude.
Table 2: Significance Levels From Repeated-Measure Models at 10% MVC
Effort Time Time2 Effort · Time Subject (Effort)
S-MUAP Amplitude
Mean Firing Rate
S-EMG
Motor Unit Index
.136 .002 .729 .000 .000
.868 .000 .000 .570 .000
.009 .000 .433 .000 .000
.268 .001 .083 .683 .000
FATIGUE EFFECTS ON MOTOR UNIT ACTIVITY, Conwit
Fig 3. Effect of changing MVC over time for 4 subjects. Graph of mean S-EMG, mean firing rate (FR), mean S-MUAP amplitude, and % of force level relative to first effort values, expressed as a percentage of total duration of effort.
DISCUSSION Fatigue has an important impact on motor units and maintenance of muscle strength during sustained contractions, as observed by the lack of full motor unit recovery after 30 minutes of rest following both 10% and 30% MVC maintained contractions. The result was the need for greater effort with recruitment of larger motor units, and greater overall muscle activation (as assessed by S-EMG amplitude), but yet a decline in firing rate. The lack of full recovery between efforts and the more rapid development of fatigue during subsequent efforts with the required activation of larger motor units could have a negative impact on maximizing the rate of recovery in rehabilitation. A fatiguing effort leads to a decline in strength, such that any subsequent similar effort requires a larger portion of available strength. Rantanen and colleagues25 argued that this type of circular effect is an important contributor to disability in the elderly. Chan and coworkers3 observed that motor units behave differently when trained at 40Hz, resulting in some that become stronger and some that become weaker with training. One explanation for such results depends on the differential fatigability of motor units, and the cumulative impact of fatigue. The amount of increase in S-EMG appears to depend on time rather than force level and on whether the muscle had been previously fatigued. During the third 30% MVC effort, over the 1- to 2.5-minute contractions, S-EMG increased to about 325% of the S-EMG measured during the initial epoch of the first effort. For both efforts at 10% MVC, which lasted 10 to 36 minutes, S-EMG reached close to 500% of the initial, first effort, epoch value. In addition, the average size of active motor units, as indicated by S-MUAP amplitude, increased as the contractions progressed. The motor unit index increased consistently only for the first effort at 30% MVC and for the second effort at 10% MVC, indicating that the relationship between surface EMG and S-MUAP size changed during these specific trials. Two mechanisms may explain the findings. The first has to do with progressive use of larger motor units. The second possibility is by synchronous firing of motor units, ie, when two motor units are firing together in perfect synchrony, force production increases.26 While the large change in size and the constancy of the surface motor unit potential would support larger unit
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recruitment, we were unable to assess adequately synchrony using our research methodology. Epoch mean firing rates also started at higher levels during subsequent efforts and showed a decline during each contraction maintained at both 10% and 30% MVC. During 10% MVC maintained contractions, the decrease in firing rate, compared with the increase in S-EMG and S-MUAP amplitude, was less over the course of the contraction, and firing rate appeared to show better recovery between trials than during the 30% MVC efforts. Rate coding did not seem to be as important a factor during 10% MVCs as it was during 30% MVCs. The results from 30% MVC are consistent with other studies that have reported a decrease in firing rates during MVC.2,10,15,27 The results from the second and third efforts to maintain 30% MVCs show that once fatigued to exhaustion, motor units did not fully recover, and that the partially recovered system had to use larger motor units and initially higher firing rates, which subsequently declined. The changes in MVC over time imply that there is an increase in the percentage of MVC maintained during a constant force contraction (fig 3). Therefore, what is initially a 30% MVC represents at least a 50% MVC by the end of an effort. Nevertheless, S-EMG amplitude shows a larger increase than the change in the percentage MVC, suggesting that changes in S-EMG amplitude are only partially explained by this change in the percentage of MVC maintained. The mixed effects model supports this by showing that both S-MUAP amplitude and firing rate significantly increased the amount of S-EMG increase that could be accounted for compared with that which could be accounted for by considering the increased percentage of MVC maintained alone. Significant subject effects were found, implying that subjects used different strategies of motor unit activation to compensate for progressing fatigue during sustained contractions. For example, one subject increased S-EMG and S-MUAP amplitude rapidly, while a second subject had a slower more linear increase, gradually increasing muscle activity. This study is unique in that a ‘‘pool’’ or ‘‘population’’ of motor units was evaluated. In comparison, Marsden and associates9 examined fatigue using tetanic contractions at different frequencies in single or multiple motor units controlled as a single unit, while DeLuca2,27 concentrated on a frequency analysis of S-EMG signals during voluntary muscle fatigue. The various approaches for motor unit physiology assessments allow the evaluation of fatigue from different perspectives. The methods used by Marsden and others were exacting, but examined few motor units in very controlled research settings. The methods used by DeLuca and others rely on surface EMG signals. Using a number of assumptions and sophisticated models, DeLuca and his colleagues have made significant contributions to understanding muscle and motor unit physiology. Our spike-triggered averaging method is based on previous work done over the past 20 or more years.22 Using powerful new algorithms for identifying individual motor unit contributions to EMG signals (detected with intramuscular needle electrodes) and ensemble averaging techniques, one may examine the surface waveforms of individual active motor units along with the composite S-EMG signal reflecting the activity of the whole muscle. By examining both the composite surface EMG signal and the S-MUAPs detected using an intramuscular needle, more information can be obtained about the motor unit pool that is active during muscle contractions. Sustained moderate activity at 10% to 30% of MVC leads to a progressive loss of strength and changes the way the motor unit pool maintains an effort. The greater the effort, the earlier Arch Phys Med Rehabil Vol 81, September 2000
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that the larger, more fatigable units are recruited. At 30% MVC, in our healthy subjects, these changes began almost immediately. The impact of fatigue in patients requiring physical rehabilitation, or in frail elderly, is likely to be more severe, and during maintained contractions this impact will be present at lower force levels. Once fatigue has developed, motor unit recovery is slow and affects subsequent contractions. The findings argue for short bouts of exercise, interspersed with adequate rest to avoid excessive fatigue. Acknowledgments: We thank Michele Watt, Megan McHugh, and Alison Cowl for their technical support. Also, our gratitude is extended to Dr. William F. Brown, Dr. Brian Tracy, and Arvind Bakhru for their efforts including constructive comments on the manuscript. References 1. Bigland-Ritchie B, Woods JJ. Changes in muscle contractile properties and neural control. Muscle Nerve 1984;7:691-9. 2. DeLuca CJ. Myoelectrical manifestations of localized muscular fatigue in humans. Crit Rev Biomed Eng 1985;11:251-79. 3. Chan KM, Andres LP, Polykovskaya Y, Brown WF. The effects of training through high-frequency electrical stimulation on the physiological properties of single human thenar motor units. Muscle Nerve 1999;22:186-95. 4. Chan KM, Doherty TJ, Andres LP, Porter MM, Brown T, Brown WF. Longitudinal study of the contractile and electrical properties of single human thenar motor units. Muscle Nerve 1998;21: 839-49. 5. Robinson LR, Mustovic EH, Lieber PS, Haidet PM, Irgang JJ, McLane T, et al. A technique for quantifying and determining the site of isometric muscle fatigue in the clinical setting. Arch Phys Med Rehabil 1990;71:901-4. 6. Miller RG. Advances in single motor unit physiology. No. 9. Rochester (MN): American Academy of Electrodiagnostic Medicine; Jan. 1979. 7. Burke RE, Tsairis P. Anatomy and innervation ratios in motor units of cat gastrocnemius. J Physiol 1973;234:749-65. 8. Bigland-Ritchie B, Johansson RS, Lippold OCJ. Contractile speed and EMG changes during fatigue of sustained maximal voluntary contractions. J Neurophysiol 1983;50:313-24. 9. Marsden CD, Meadows JC, Merton PA. ‘‘Muscular wisdom’’ that minimizes fatigue during prolonged effort in man: peak rates of motoneuron discharge and slowing of discharge during fatigue. In: Desmedt JE, editor. Advances in neurology. New York: Raven Pr; 1983. p. 169-211. 10. Grimby L, Tollback A, Muller U, Larsson L. Fatigue of chronically overused motor units in prior polio patients. Muscle Nerve 1996;19:728-37. 11. Leisman G, Zehausern R, Ferentz A, Tefera T, Zemcov A. EMG effects of fatigue and task repetition on the validity of estimates of strong and weak muscles in applied kinesiological muscle-testing procedures. Percept Mot Skills 1995;80:963-77.
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12. Dorfman LJ, Howard JE, McGill KC. Triphasic behavioral response of motor units to submaximal fatiguing exercise. Muscle Nerve 1990;13:621-8. 13. Enoka RM, Robinson GA, Kossev AR. Task and fatigue effect on low-threshold motor units in human hand muscle. J Neurophysiol 1989;62:1344-59. 14. Garland SJ, Enoka RM, Serrano LP, Robinson A. Behavior of motor units in human biceps brachii during a submaximal fatiguing contraction. J Appl Physiol 1994;76:2411-9. 15. Kukulka CG, Clamann HP. Comparison of the recruitment and discharge properties of motor units in human brachial biceps and adductor pollicis during isometric contractions. Brain Res 1981;219: 45-55. 16. Christova P, Kossev A. Motor unit activity during long-lasting intermittent muscle contraction in humans. Eur J Appl Physiol 1998;77:379-87. 17. Stashuk DW, Qu Y. A robust method for estimating motor unit firing pattern statistics. Med Biol Eng Comput 1996;34:50-7. 18. Stashuk DW, Doherty TJ, Brown WF. EMG signal decomposition applied to motor unit estimates [abstract]. Muscle Nerve 1992;15: 1204A. 19. Stashuk DE, Qu Y. Adaptive motor unit action potential clustering using shape and temporal information. Med Biol Eng Comput 1996;34:41-9. 20. Conwit R, Tracy B, Jamison C, McHugh M, Stashuk D, Brown WF, et al. Decomposition enhanced spike triggered averaging: contraction level effects. Muscle Nerve 1997;20:976-82. 21. Conwit R, Tracy B, Cowl A, McHugh M, Stashuk D, Brown WF, et al. Firing rate analysis using decomposition-enhanced spike triggered averaging in the quadriceps femoris. Muscle Nerve 1998;21: 1338-40. 22. Doherty T, Simmons Z, O’Connell B, Felice KJ, Conwit R, Ming Chan K, et al. Methods of estimating the numbers of motor units in human muscles. J Clin Neurophysiol 1995;12:565-84. 23. Hedeker D, Gibbons RD. MIXREG: a computer program for mixed-effects regression analysis with autocorrelated errors. Comput Methods Programs Biomed 1996;49:229-52. 24. Goldstein H, Rasbash J, Plewis I, Draper D, Browne W, Yang M, et al. A user’s guide to MLwin. London: Institute of Education; 1998. 25. Rantanen T, Guralnik JM, Sakari-Rantala R, Leveille S, Simonsick EM, Ling S, et al. Disability, physical activity, and muscle strength in older women: The Women’s Health and Aging Study. Arch Phys Med Rehabil 1999;80:130-5. 26. Stalberg EV. Macro EMG. No. 20. Rochester (MN): American Academy of Electrodiagnostic Medicine; Nov. 1983. 27. DeLuca CJ, Foley PJ, Erim Z. Motor unit control properties in constant-force isometric contractions. J Neurophysiol 1996;76: 1503-16. Suppliers a. Model 125E; Chattecx, 4717 Adams Rd, PO Box 489, Chattanooga, TN 37343-0489. b. TECA/Oxford, 3 Campus Dr, Pleasantville, NY 10570. c. SPSS Inc., 233 S Wacker Dr, Chicago, IL 60606.
Fatigue Effects on Motor Unit Activity During Submaximal Contractions Robin A. Conwit, MD, Dan Stashuk, PhD, PEng, Hiromasa Suzuki, MD, Nicole Lynch, PhD, Matthew Schrager, MA, E. Jeffrey Metter, MD ABSTRACT. Conwit RA, Stashuk D, Suzuki H, Lynch N, Schrager M, Metter EJ. Fatigue effect on motor unit activity during submaximal contractions. Arch Phys Med Rehabil 2000;81:1211-6. Objective: To examine motor unit changes during the development of fatigue in healthy subjects. Design: Automated decomposition-enhanced spike-triggered averaging was used to characterize motor unit size and firing rate in the dominant vastus medialis during maintained contractions at 10% and 30% of maxima voluntary contraction (MVC). Setting: Academic outpatient neuromuscular clinic. Participants: Healthy laboratory personnel. Main Outcome Measures: Surface electromyogram, surfacedetected motor unit action potential amplitude (S-MUAP), mean firing rate, force (MVC), motor unit index. Results: Surface electromyogram values and S-MUAP amplitudes increased during both 10% and 30% MVC fatiguing contractions, while mean firing rates decreased. A motor unit index, indicating the degree of motor unit pool activation, increased similarly to S-MUAP size, implying that new and larger units were recruited to maintain the contraction. Repeated contractions led to earlier motor unit changes and fatigue. Conclusion: During submaximal fatiguing contractions, additional motor units are activated to maintain strength. These changes begin early, within the first minute, particularly after a previous fatiguing effort. Key Words: Fatigue; Electromyography; Action potentials; Isometric contraction; Rehabilitation. r 2000 by the American Congress of Rehabilitation Medicine and the American Academy of Physical Medicine and Rehabilitation
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EUROMUSCULAR FATIGUE is sometimes defined as ‘‘an inability of a muscle or group of muscles to sustain the required or expected force.’’1 With respect to motor unit physiology, fatigue may be better defined as the changes in nerve and muscle physiologic and biochemical processes used to produce muscle force that eventually result in the inability to maintain a contraction.2 Fatigue is a frequent problem encountered during rehabilitation and in exercise physiology. Under situations where muscle contraction must be maintained for
From the Department of Neurology, Johns Hopkins Bayview Medical Center (Conwit), and the National Institute on Aging, Gerontology Research Center (Metter), Baltimore; University of Maryland, College Park, MD (Lynch, Schrager); Department of Systems Design Engineering, University of Waterloo, Ontario, Canada (Stashuk); and Department of Rehabilitation Medicine, Dokkyo University School of Medicine, Dokkyo, Japan (Suzuki). Accepted February 14, 2000. No commercial party having a direct financial interest in the results of the research supporting this article has or will confer a benefit upon the authors or upon any organization with which the authors are associated. Reprint requests to Robin A. Conwit, MD, Department of Neurology, Johns Hopkins Bayview Medical Center, Baltimore, MD 21224. 0003-9993/00/8109-5850$3.00/0 doi:10.1053/apmr.2000.6975
extended periods, fatigue can limit the performance of both patients and athletes. Fatigue can limit recovery after sustained bed rest and during recuperation from illness. Fatigue contributes to disability, particularly in the elderly, for whom daily activities may require a higher percentage of potential strength than in younger individuals, leading to earlier and prolonged fatigue. Although there are several research-oriented fatigue indices that explore mechanisms contributing to fatigue, there are few objective, clinically obtainable markers for fatiguing motor units.3-5 Understanding the relation between fatigue and motor unit physiology in a clinical setting may be important because motor units are the fundamental contributors to muscle contraction and ultimately are directly involved in the development of fatigue. Sustained fatiguing contractions can be of two types based on a maximal or a submaximal contraction. It is well established for the cat gastrocnemius muscle that motor units developing the smallest tetanic tensions have relatively long twitch contraction times and are fatigue resistant. Stronger contracting units, on the other hand, have shorter contraction times and a broad range of fatigue resistance, the strongest units having the least resistance to fatigue.6,7 In an effort to avoid physiologic fatigue, the smallest, most fatigue-resistant motor units are recruited first. During maximal contraction, essentially all motor units are initially activated. To sustain the contraction as long as possible, motor units reduce firing rates, resulting in a gradual loss of force during the contraction, referred to as ‘‘muscle wisdom.’’1,8,9 Based on muscle wisdom, motor unit firing rates should decrease even though force generation decreases during a sustained maximal contraction. This mechanism has indeed been observed by most investigators during sustained maximal isometric contractions.1,8,10 At the same time, the mean absolute surface-detected electromyogram (SEMG) signal amplitude increases with maximal contraction,11 suggesting an increased synchronization of the motor unit firing. Conversely, during submaximal contractions the firing rate response varies, with greater emphasis on motor unit recruitment.12 Enoka and associates13 found an increased mean firing rate of newly recruited single motor units in first dorsal interosseous muscles in short duration submaximal contractions. In a subsequent study,14 they found a different response in biceps brachii. Others have also seen variable firing patterns.12 These differences may also be a function of the different recruitment and rate coding strategies of various small muscles, such as the first dorsal interosseous or abductor pollicis brevis, versus the larger biceps or deltoid.2,15 The impact of training on the motor unit can be seen in the work of Chan and colleagues,3 who trained motor units three times a week for 7 to 11 weeks using 40Hz stimulation. During the training period, some motor units responded with a gradual increase in strength, while other units showed a clear decline in force generation over many weeks. The decline in strength likely resulted from excessive fatigue of the motor unit resulting in an inability to completely recover across training sessions. When training ceased, units that had either increased or decreased in strength slowly returned to their baseline strength. Arch Phys Med Rehabil Vol 81, September 2000
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The implications are that motor units respond differently to training and rehabilitation. Motor unit physiology in neuromuscular disease can result in greater levels of fatigue after exercise combined with incomplete recovery of function. Most functional activities can be completed using submaximal contractions. Seldom in practical daily activities is sustained maximal voluntary strength capacity used. For this reason, we were interested in characterizing motor unit activity during submaximal contractions maintained at levels close to the range of strength used during daily activities. Although previous studies have examined motor unit firing rates and EMG signal amplitude, most have examined only short periods of contraction, only studied a few motor units, or utilized only S-EMG parameters, and few have studied repeated fatiguing contractions preceded by a period of rest.16 This study describes average motor unit firing rates and surface-detected motor unit action potential (S-MUAP) amplitude during multiple trials of submaximal contractions maintained to exhaustion with 30 minutes of rest between efforts. Subjects were studied as they produced 10% and 30% of their maximal strength on separate days. The questions of interest were: (1) Do changes occur in average motor unit firing rate and average S-MUAP amplitude during maintained submaximal muscle contractions? (2) Are there differences in the time course of these average motor unit characteristics during 10% and 30% of maximal contractions? (3) Do the time courses of these average motor unit characteristics change across repeated fatiguing contractions? (4) Could this approach be reasonably applied in a clinical setting to study fatigue? We have approached the problem by using decompositionenhanced spike-triggered averaging during sustained submaximal contractions. Decomposition-enhanced spike-triggered averaging is a clinical tool based on traditional EMG techniques.17-19 The method used allows for the measurement of surface- and needle-detected motor unit activity in 20- to 30-second epochs of time during a muscle contraction. The signal decomposition algorithms identify motor unit firings based on the shape of their MUAPs (as detected by an intramuscular electrode) and firing pattern. The contribution of each motor unit to the S-EMG is then examined over the full epoch. Sequential epochs can be examined during the course of a maintained contraction; however, each epoch may identify a different group of motor units. Thus, what is observed is a sampling of motor units during different periods of a maintained submaximal contraction. This approach is different from studies that examine the same individual motor units over the entire course of a contraction. In this study, we used this technique to examine fatigue. Variations of this technique have been used previously by Stashuk and coworkers.17-19 In previous reports, we have shown that in the quadriceps femoris the average size of S-MUAPs increases linearly with increasing levels of force,20 while the mean firing rate increases only at higher force levels.21 METHODS Seven healthy individuals volunteered for the study. All were free of neuromuscular disease, considered themselves to be in good to excellent health, and remained healthy over the subsequent 4 years. The study was approved by the Johns Hopkins Bayview Medical Center Institutional Review Board. Maximal Voluntary Contraction Subjects performed three maximal voluntary isometric contractions (MVCs) of the dominant knee extensors on a KinCom dynamometera with 30 seconds of rest between trials to Arch Phys Med Rehabil Vol 81, September 2000
determine maximal strength. The force measurement was calibrated by positioning and stabilizing the lever arm level to the floor. Details of the strength collection protocol have been published.20,21 Fatigue Protocol Subjects performed three separate contractions of the quadriceps at 30% MVC and maintained each contraction to exhaustion. Subjects rested for 30 minutes between each submaximal contraction. On a separate day, this procedure was repeated but with subjects maintaining a quadriceps contraction at 10% MVC, and the 10% MVC was repeated only once after a 30-minute rest period. All recording and ground electrodes were TECAb 3.0-cmdiameter silver-silver chloride recording surfaces. During all contractions an active surface electrode was placed over the motor point of the vastus medialis muscle, which was determined by moving the surface electrode until the maximum compound muscle action potential (CMAP) with minimal rise time was detected following supramaximal surface stimulation of the femoral nerve in the groin. An inactive surface electrode was placed on the patellar tendon, and a ground electrode was placed on the lateral thigh between the stimulation and recording sites. Before each fatiguing contraction, a concentric needle electrode was inserted into the vastus medialis and positioned to maximize the amplitude of MUAPs generated by motor units with fibers close to the electrode. During the fatiguing contraction, needle- and surface-detected signals were acquired using sampling rates of 25 and 2.5kHz, respectively, during 20- to 30-second consecutive epochs. Thus, the time course of the fatiguing contraction could be divided into a series of epochs that represented 20 to 30 seconds each. For each epoch, from 1 to 9 motor units were identified and tracked by the algorithms. The needle signal was used to estimate the size of the S-MUAP of each motor unit tracked by the decomposition algorithms. The mean S-MUAP amplitude for the epoch was then computed as the difference between the maximum and minimum values. An epoch mean firing rate was calculated as the average of the mean firing rates of all motor units tracked by the decomposition algorithms over the 20- to 30-second epoch. The mean firing rate of a motor unit was calculated as the reciprocal of the mean inter–potential interval value of the main lobe of the motor unit’s inter–potential interval histogram provided by the decomposition algorithms.17 The EMG signal decomposition and average firing rate algorithms were developed by Stashuk and colleagues.17-19 The S-EMG amplitude was also used to examine the overall muscle activity during the course of the contraction. To assess the degree of activation of the motor unit pool, a motor unit index was defined as the mean absolute amplitude of the S-EMG, calculated over a 20- to 30-second epoch, divided by the product of the S-MUAP size and firing rate for that epoch. This is conceptually analogous to a motor unit number estimate that is obtained by dividing the average S-MUAP size into the CMAP obtained following maximal stimulation.22 The S-EMG value represents the average electric activity of all active motor units underlying the detection electrode during a contraction epoch. As more motor units are active, the S-EMG amplitude increases in proportion to the size and relative location of the units. Thus, the motor unit index is a rough indication of the number of motor units active during a contraction epoch. Statistical Methods All statistical analyses were computed with SPSS version 8.c A mean value was obtained for each variable from all motor
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units collected in any epoch for each subject. Average values across all 7 subjects for S-MUAP amplitude, firing rate, S-EMG, and a motor unit index were calculated for each epoch. The mean values were used in all figures. To allow comparison across subjects, data were presented with respect to a percentage of the total contraction time of each effort. Since the last epoch represented a ‘‘fall off’’ in muscle strength, ie, strength was not maintained throughout the 20 to 30 seconds, we eliminated data from the last epoch from the analysis. Data were then grouped into time periods from 0% to 19.9%, 20% to 39.9%, 40% to 59.9%, 60% to 79.9%, and 80% to 95% of the total time for each effort for graphing purposes. Each variable was also expressed as a percentage of its value measured during the initial epoch of the first effort. Because each subject had a different number of epochs that also differed between contractions, mixed effects models23 were used to examine the change in each variable over time using MLwiN.24 Such models deal with the repeated measures and the unbalanced design in relation to the time of the contractions. The models are of the form where b0i and b1i are random effects that reflect individual variation from the mean effect (b0, b1): Motor unit variable ⫽ (b0 ⫹ b0i) ⫹ (b1 ⫹b1i) ⴱ time ⫹ b2 ⴱ time2 ⫹ b3 ⴱ run 2 ⫹ b4 ⴱ run 3 ⫹ b5 ⴱ time ⴱ run2 ⫹ b6 ⴱ time ⴱ run3 ⫹ error. Time refers to the percentage of the total time of contraction. Based on the appearance of the data, the quadratic term for time was included. Run refers to the three efforts at 30% MVC or two efforts at 10%. Run2 contrasts the second effort with the first, and run3 contrasts the third with the first. The remaining terms reflected the interaction between time and which effort (time · run). All models were tested for significance at p ⬍ .05 using a chi-square distribution.24 RESULTS 30% MVC Six subjects (2 men, 4 women; age range, 23–49yr) sustained forces at 30% MVC for from 2 to 5 minutes during the first effort. During the second effort, times were slightly shorter, ranging from 1.5 to 3 minutes, and during the third effort, 1.0 to 2.5 minutes. Figure 1 shows results averaged over the six subjects for S-MUAP amplitude, firing rate, S-EMG, and the motor unit index obtained during the first, second, and third efforts. During the course of each effort, an increase was observed in the S-EMG, with the S-MUAP amplitude paralleling the changes observed in the S-EMG. In all three trials there was a decline in the firing rates. The motor unit index showed a progressive gradual increase in the first run only, suggesting that the number of active units was progressively increasing as the contraction was maintained. During the second and third efforts, the initial motor unit properties (firing rate, S-MUAP amplitude) had higher values than values measured during the initial epoch of the first effort. Also, the changes in motor unit parameters during the contraction were greater in the second and third efforts. A mixed effects model was used to examine the differences across efforts and time for each of the four variables (table 1). Significant time effects were found for all four measures ( p ⬍ .05), implying changes from the initial levels as fatigue progressed. The only significant interaction found between effort and time was for the motor unit index when comparing
Fig 1. Fatigue during 30% MVC. Graphs of S-EMG, mean firing rate (FR), motor unit index, and mean S-MUAP amplitude as a percentage of initial values obtained at the onset of the first effort versus time expressed as a percentage of total duration of the contraction. (A) first effort; (B) second effort after 30 minutes of rest; and (C) third effort after 30 minutes of rest.
the second to the first effort, implying that the number of active motor units changed differently with time during the second effort. Significant differences between effort were found for firing rate and S-EMG amplitude, but not for S-MUAP size. A Arch Phys Med Rehabil Vol 81, September 2000
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Table 1: Significance Levels From Repeated-Measure Analysis of Variance Models at 30% MVC
Effort Full model Univariate* Time Full model Univariate* Effort · Time: Full model Subject (Effort): Full model
S-MUAP Amplitude
Mean Firing Rate
S-EMG
Motor Unit Index
.126 .000
.002 .000
.02 .000
.993 .966
.000 .000 .011 .000
.001 .001 .904 .009
.000 .000 .085 .000
.006 .006 .055 .000
* Univariate represents post hoc analysis for effort and time.
random effect was observed for time showing that individuals performed somewhat differently during the efforts. 10% MVC Four subjects (1 man, 3 women; age range, 22–49yr) sustained this level of exertion for 15 to 35 minutes during the first effort, and for shorter time periods (13–16min) for the second effort after 30 minutes of rest. S-EMG and S-MUAP amplitude showed an approximately fivefold increase as the contractions proceeded during both efforts, while firing rate was relatively stable and the motor unit index increased slowly during the second effort (fig 2). The mixed effects analysis for 10% MVC (table 2) found that all four variables had significant changes over time. In addition, the quadratic term for time was significant for firing rate and for motor unit index. A significant interaction was found between the effort number and time for S-EMG amplitude, but not for firing rate, S-MUAP, or motor unit index. This suggests that S-EMG changed differently during the course of the two fatiguing efforts, while the motor unit measures behaved similarly. A significant random effect across efforts implied that subjects behaved somewhat differently with respect to their responses to fatigue. Comparing average motor unit characteristics with S-EMG amplitude revealed that the motor unit index stayed relatively constant across each effort. This observation suggests that particularly during the first effort 10% MVC, there was not a large increase in the number of active motor units over time. Effect of Changing MVC Over Time In our previous work,20,21 as percentage of MVC increased, S-MUAP amplitude increased linearly. The large increase in S-EMG and S-MUAP amplitude across time during the sustained contractions at 10% and 30% MVC suggested that as fatigue progressed a change in the percentage of MVC occurred during the course of the sustained contraction. To test this hypothesis, four subjects sustained contractions of 30% of initial MVC to fatigue, with the current MVC measured at 1-minute intervals. The current MVCs were measured between 30-second motor unit data collection epochs, following which the subjects immediately returned to maintaining the 30% of initial MVC. S-EMG and S-MUAP amplitude both increased over time, while firing rate declined (fig 3). At the same time, MVC declined by 30% to 40% during the course of the sustained contraction, so that the percentage of MVC eventually being maintained approached 50% (ie, 150% to 160% of the initial percentage of MVC being sustained during the contraction). The change in the percentage of MVC during the course of the contraction paralleled the changes observed in both S-EMG and S-MUAP amplitude, while the percentage Arch Phys Med Rehabil Vol 81, September 2000
Fig 2. Fatigue at 10% MVC. Graphs of S-EMG, mean firing rate (FR), motor unit index, and mean S-MUAP amplitude at 10% MVC for a percentage of initial values obtained at the onset of (A) the first effort and (B) the second effort, versus time.
decline in MVC was similar to the decline in firing rate. A mixed effects model was utilized to test whether the change in S-EMG amplitude was only explained by the changes in percentage of MVC being maintained. In the analysis, no random effects were found. S-MUAP amplitude, firing rate, and the increase in percentage of MVC represented by the force generated independently contributed to S-EMG amplitude changes ( p ⬍ .05). Thus, the change in MVC, ie, the relative increase in percentage of MVC maintained, was not the only factor that accounted for the large increases in S-EMG amplitude.
Table 2: Significance Levels From Repeated-Measure Models at 10% MVC
Effort Time Time2 Effort · Time Subject (Effort)
S-MUAP Amplitude
Mean Firing Rate
S-EMG
Motor Unit Index
.136 .002 .729 .000 .000
.868 .000 .000 .570 .000
.009 .000 .433 .000 .000
.268 .001 .083 .683 .000
FATIGUE EFFECTS ON MOTOR UNIT ACTIVITY, Conwit
Fig 3. Effect of changing MVC over time for 4 subjects. Graph of mean S-EMG, mean firing rate (FR), mean S-MUAP amplitude, and % of force level relative to first effort values, expressed as a percentage of total duration of effort.
DISCUSSION Fatigue has an important impact on motor units and maintenance of muscle strength during sustained contractions, as observed by the lack of full motor unit recovery after 30 minutes of rest following both 10% and 30% MVC maintained contractions. The result was the need for greater effort with recruitment of larger motor units, and greater overall muscle activation (as assessed by S-EMG amplitude), but yet a decline in firing rate. The lack of full recovery between efforts and the more rapid development of fatigue during subsequent efforts with the required activation of larger motor units could have a negative impact on maximizing the rate of recovery in rehabilitation. A fatiguing effort leads to a decline in strength, such that any subsequent similar effort requires a larger portion of available strength. Rantanen and colleagues25 argued that this type of circular effect is an important contributor to disability in the elderly. Chan and coworkers3 observed that motor units behave differently when trained at 40Hz, resulting in some that become stronger and some that become weaker with training. One explanation for such results depends on the differential fatigability of motor units, and the cumulative impact of fatigue. The amount of increase in S-EMG appears to depend on time rather than force level and on whether the muscle had been previously fatigued. During the third 30% MVC effort, over the 1- to 2.5-minute contractions, S-EMG increased to about 325% of the S-EMG measured during the initial epoch of the first effort. For both efforts at 10% MVC, which lasted 10 to 36 minutes, S-EMG reached close to 500% of the initial, first effort, epoch value. In addition, the average size of active motor units, as indicated by S-MUAP amplitude, increased as the contractions progressed. The motor unit index increased consistently only for the first effort at 30% MVC and for the second effort at 10% MVC, indicating that the relationship between surface EMG and S-MUAP size changed during these specific trials. Two mechanisms may explain the findings. The first has to do with progressive use of larger motor units. The second possibility is by synchronous firing of motor units, ie, when two motor units are firing together in perfect synchrony, force production increases.26 While the large change in size and the constancy of the surface motor unit potential would support larger unit
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recruitment, we were unable to assess adequately synchrony using our research methodology. Epoch mean firing rates also started at higher levels during subsequent efforts and showed a decline during each contraction maintained at both 10% and 30% MVC. During 10% MVC maintained contractions, the decrease in firing rate, compared with the increase in S-EMG and S-MUAP amplitude, was less over the course of the contraction, and firing rate appeared to show better recovery between trials than during the 30% MVC efforts. Rate coding did not seem to be as important a factor during 10% MVCs as it was during 30% MVCs. The results from 30% MVC are consistent with other studies that have reported a decrease in firing rates during MVC.2,10,15,27 The results from the second and third efforts to maintain 30% MVCs show that once fatigued to exhaustion, motor units did not fully recover, and that the partially recovered system had to use larger motor units and initially higher firing rates, which subsequently declined. The changes in MVC over time imply that there is an increase in the percentage of MVC maintained during a constant force contraction (fig 3). Therefore, what is initially a 30% MVC represents at least a 50% MVC by the end of an effort. Nevertheless, S-EMG amplitude shows a larger increase than the change in the percentage MVC, suggesting that changes in S-EMG amplitude are only partially explained by this change in the percentage of MVC maintained. The mixed effects model supports this by showing that both S-MUAP amplitude and firing rate significantly increased the amount of S-EMG increase that could be accounted for compared with that which could be accounted for by considering the increased percentage of MVC maintained alone. Significant subject effects were found, implying that subjects used different strategies of motor unit activation to compensate for progressing fatigue during sustained contractions. For example, one subject increased S-EMG and S-MUAP amplitude rapidly, while a second subject had a slower more linear increase, gradually increasing muscle activity. This study is unique in that a ‘‘pool’’ or ‘‘population’’ of motor units was evaluated. In comparison, Marsden and associates9 examined fatigue using tetanic contractions at different frequencies in single or multiple motor units controlled as a single unit, while DeLuca2,27 concentrated on a frequency analysis of S-EMG signals during voluntary muscle fatigue. The various approaches for motor unit physiology assessments allow the evaluation of fatigue from different perspectives. The methods used by Marsden and others were exacting, but examined few motor units in very controlled research settings. The methods used by DeLuca and others rely on surface EMG signals. Using a number of assumptions and sophisticated models, DeLuca and his colleagues have made significant contributions to understanding muscle and motor unit physiology. Our spike-triggered averaging method is based on previous work done over the past 20 or more years.22 Using powerful new algorithms for identifying individual motor unit contributions to EMG signals (detected with intramuscular needle electrodes) and ensemble averaging techniques, one may examine the surface waveforms of individual active motor units along with the composite S-EMG signal reflecting the activity of the whole muscle. By examining both the composite surface EMG signal and the S-MUAPs detected using an intramuscular needle, more information can be obtained about the motor unit pool that is active during muscle contractions. Sustained moderate activity at 10% to 30% of MVC leads to a progressive loss of strength and changes the way the motor unit pool maintains an effort. The greater the effort, the earlier Arch Phys Med Rehabil Vol 81, September 2000
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that the larger, more fatigable units are recruited. At 30% MVC, in our healthy subjects, these changes began almost immediately. The impact of fatigue in patients requiring physical rehabilitation, or in frail elderly, is likely to be more severe, and during maintained contractions this impact will be present at lower force levels. Once fatigue has developed, motor unit recovery is slow and affects subsequent contractions. The findings argue for short bouts of exercise, interspersed with adequate rest to avoid excessive fatigue. Acknowledgments: We thank Michele Watt, Megan McHugh, and Alison Cowl for their technical support. Also, our gratitude is extended to Dr. William F. Brown, Dr. Brian Tracy, and Arvind Bakhru for their efforts including constructive comments on the manuscript. References 1. Bigland-Ritchie B, Woods JJ. Changes in muscle contractile properties and neural control. Muscle Nerve 1984;7:691-9. 2. DeLuca CJ. Myoelectrical manifestations of localized muscular fatigue in humans. Crit Rev Biomed Eng 1985;11:251-79. 3. Chan KM, Andres LP, Polykovskaya Y, Brown WF. The effects of training through high-frequency electrical stimulation on the physiological properties of single human thenar motor units. Muscle Nerve 1999;22:186-95. 4. Chan KM, Doherty TJ, Andres LP, Porter MM, Brown T, Brown WF. Longitudinal study of the contractile and electrical properties of single human thenar motor units. Muscle Nerve 1998;21: 839-49. 5. Robinson LR, Mustovic EH, Lieber PS, Haidet PM, Irgang JJ, McLane T, et al. A technique for quantifying and determining the site of isometric muscle fatigue in the clinical setting. Arch Phys Med Rehabil 1990;71:901-4. 6. Miller RG. Advances in single motor unit physiology. No. 9. Rochester (MN): American Academy of Electrodiagnostic Medicine; Jan. 1979. 7. Burke RE, Tsairis P. Anatomy and innervation ratios in motor units of cat gastrocnemius. J Physiol 1973;234:749-65. 8. Bigland-Ritchie B, Johansson RS, Lippold OCJ. Contractile speed and EMG changes during fatigue of sustained maximal voluntary contractions. J Neurophysiol 1983;50:313-24. 9. Marsden CD, Meadows JC, Merton PA. ‘‘Muscular wisdom’’ that minimizes fatigue during prolonged effort in man: peak rates of motoneuron discharge and slowing of discharge during fatigue. In: Desmedt JE, editor. Advances in neurology. New York: Raven Pr; 1983. p. 169-211. 10. Grimby L, Tollback A, Muller U, Larsson L. Fatigue of chronically overused motor units in prior polio patients. Muscle Nerve 1996;19:728-37. 11. Leisman G, Zehausern R, Ferentz A, Tefera T, Zemcov A. EMG effects of fatigue and task repetition on the validity of estimates of strong and weak muscles in applied kinesiological muscle-testing procedures. Percept Mot Skills 1995;80:963-77.
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12. Dorfman LJ, Howard JE, McGill KC. Triphasic behavioral response of motor units to submaximal fatiguing exercise. Muscle Nerve 1990;13:621-8. 13. Enoka RM, Robinson GA, Kossev AR. Task and fatigue effect on low-threshold motor units in human hand muscle. J Neurophysiol 1989;62:1344-59. 14. Garland SJ, Enoka RM, Serrano LP, Robinson A. Behavior of motor units in human biceps brachii during a submaximal fatiguing contraction. J Appl Physiol 1994;76:2411-9. 15. Kukulka CG, Clamann HP. Comparison of the recruitment and discharge properties of motor units in human brachial biceps and adductor pollicis during isometric contractions. Brain Res 1981;219: 45-55. 16. Christova P, Kossev A. Motor unit activity during long-lasting intermittent muscle contraction in humans. Eur J Appl Physiol 1998;77:379-87. 17. Stashuk DW, Qu Y. A robust method for estimating motor unit firing pattern statistics. Med Biol Eng Comput 1996;34:50-7. 18. Stashuk DW, Doherty TJ, Brown WF. EMG signal decomposition applied to motor unit estimates [abstract]. Muscle Nerve 1992;15: 1204A. 19. Stashuk DE, Qu Y. Adaptive motor unit action potential clustering using shape and temporal information. Med Biol Eng Comput 1996;34:41-9. 20. Conwit R, Tracy B, Jamison C, McHugh M, Stashuk D, Brown WF, et al. Decomposition enhanced spike triggered averaging: contraction level effects. Muscle Nerve 1997;20:976-82. 21. Conwit R, Tracy B, Cowl A, McHugh M, Stashuk D, Brown WF, et al. Firing rate analysis using decomposition-enhanced spike triggered averaging in the quadriceps femoris. Muscle Nerve 1998;21: 1338-40. 22. Doherty T, Simmons Z, O’Connell B, Felice KJ, Conwit R, Ming Chan K, et al. Methods of estimating the numbers of motor units in human muscles. J Clin Neurophysiol 1995;12:565-84. 23. Hedeker D, Gibbons RD. MIXREG: a computer program for mixed-effects regression analysis with autocorrelated errors. Comput Methods Programs Biomed 1996;49:229-52. 24. Goldstein H, Rasbash J, Plewis I, Draper D, Browne W, Yang M, et al. A user’s guide to MLwin. London: Institute of Education; 1998. 25. Rantanen T, Guralnik JM, Sakari-Rantala R, Leveille S, Simonsick EM, Ling S, et al. Disability, physical activity, and muscle strength in older women: The Women’s Health and Aging Study. Arch Phys Med Rehabil 1999;80:130-5. 26. Stalberg EV. Macro EMG. No. 20. Rochester (MN): American Academy of Electrodiagnostic Medicine; Nov. 1983. 27. DeLuca CJ, Foley PJ, Erim Z. Motor unit control properties in constant-force isometric contractions. J Neurophysiol 1996;76: 1503-16. Suppliers a. Model 125E; Chattecx, 4717 Adams Rd, PO Box 489, Chattanooga, TN 37343-0489. b. TECA/Oxford, 3 Campus Dr, Pleasantville, NY 10570. c. SPSS Inc., 233 S Wacker Dr, Chicago, IL 60606.