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1Department of Integrative Physiology, University of Colorado at Boulder, Boulder, Colorado; 2Laboratorio di Ingegneria del Sistema Neuromuscolare, Dipartimento di Elettronica, Politecnico di Torino, Torino, Italy; and 3Center for Sensory-Motor Interaction (SMI), Department of Health Science and Technology, Aalborg University, Aalborg, Denmark
Submitted 18 August 2004 ; accepted in final form 14 September 2004
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ABSTRACT |
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 TOP ABSTRACT METHODSRESULTSDISCUSSIONGRANTSREFERENCES |
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85%. Differences in the amount of amplitude cancellation were observed across all simulated conditions, and resulted in substantial changes in the absolute magnitude of the EMG signal. The most profound factors influencing amplitude cancellation were the number of active motor units and the duration of the action potentials. The effects of amplitude cancellation were minimal (<5%) when the EMG amplitude was normalized to maximal values, with the exception of variations in peak discharge rate and recruitment range, which resulted in differences up to 17% in the normalized EMG signal across conditions. These results indicate the amount of amplitude cancellation that can occur in various experimental conditions and its influence on absolute and relative measures of EMG amplitude. computer simulations; peak discharge rate; fatigue; motor unit; normalization
Many techniques are limited by amplitude cancellation in the EMG, including the decomposition of an interference EMG signal into its constituent motor unit potentials (24), the estimation of changes in central conduction from the amplitude of motor evoked potentials (52), and spike-triggered averaging of the interference EMG (19). Furthermore, amplitude cancellation likely confounds interpretation of changes in the surface EMG, such as assessing correlated activity in surface EMG signals from pairs of muscles (27, 35) and explaining the failure of EMG amplitude to reach maximal levels at the endurance limit during a submaximal fatiguing contraction (23).
Although problems and limitations due to amplitude cancellation have been recognized for several decades (1, 44, 49), only one previous experimental study quantified amplitude cancellation in the interference EMG (5). Groups of motor units were stimulated in a cat hindlimb muscle, and amplitude cancellation was quantified by computing the difference between EMG amplitude derived from rectified and unrectified trains of motor unit potentials. At maximal levels of imposed excitation, amplitude cancellation reduced EMG amplitude by 50%. Due to the simultaneous activation of many motor units, however, Day and Hulliger (5) suggested that the actual amount of amplitude cancellation might be greater during a voluntary contraction. Furthermore, to generalize the results of the experimental study it is necessary to determine the sensitivity of amplitude cancellation to variation in the relevant physiological parameters.
Computational models have proven useful in characterizing the sensitivity of the surface EMG to the parameters of the systems involved in its generation and detection (4, 15, 16), and the application of these models has been suggested as a strategy for understanding amplitude cancellation (55). The purpose of the study was to quantify the influence of selected motor unit properties and patterns of activity on amplitude cancellation in the simulated surface EMG. The expectation was that increases in the amount of overlap between action potentials, such as occurs with conditions that increase the numbers and durations of motor unit potentials, would enhance amplitude cancellation and confound the use of the surface EMG as a population index of motor unit activity. Some of these data were presented in abstract form (34).
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METHODS |
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The model was implemented in Matlab version 6.5 (The Mathworks, Natick, MA). The basic parameters in the model were similar to those published previously (56, 57). The distributions of properties across the motor unit pool were based on the Size Principle (29), and these included recruitment thresholds, innervation number, motor unit territory, and the conduction velocity of muscle fiber action potentials. Activation of the motor unit pool was modeled as a ramp-and-hold function, with a 1-s ramp increase in excitation to a mean level that was constant for 4 s. Input was uniformly distributed across the motor neuron pool and all neurons received the same level of excitation, thereby allowing simulated motor neuron input-output functions to be specified by well-established relations between discharge rate and injected current (28). Maximal excitation was denoted as the level of input necessary to bring the last recruited motor neuron to its assigned peak discharge rate and values of excitation were expressed as a percent of the calculated maximum. The distribution of recruitment thresholds for the motor neurons was determined from an exponential function with many low-threshold neurons and progressively fewer high-threshold neurons (12). Each motor unit began discharging at 8 pulses per second (pps) once excitation exceeded the assigned recruitment threshold of the unit, and discharge rates increased linearly with increased excitation (3 pps per 10% increase in excitation). As described by Fuglevand et al. (21), the first recruited unit (MU 1) had a maximal discharge rate of 35 pps, whereas peak discharge rate decreased linearly with increasing recruitment threshold, with the last recruited unit (MU 120) assigned a peak discharge rate of 25 pps. The discharge rate was modeled as a random process with a Gaussian distribution, varying the coefficient of variation for discharge rate from 10 to 40%.
Motor unit territories.
The simulated muscle had a circular cross-section with a radius of 8.67 mm, derived from physiological cross-sectional areas calculated by Keen et al. (33). The number of muscle fibers was 66,000, based on an average fiber diameter of 56 µm (8), a muscle radius of 8.67 mm, and an assumption that the noncontractile tissue accounted for 20% of the cross-sectional area. These values are similar to those used originally by Fuglevand et al. (21) (71,747 muscle fibers and a muscle radius of 7.5 mm). The number of fibers innervated by a single motor neuron and the cross-sectional area of the motor unit increased exponentially from MU 1 (26 muscle fibers, 1.3 mm2) to MU 120 (2,510 muscle fibers, 125.5 mm2). An exponential increase in motor unit territories reflected the skewed distribution of motor unit forces, with more motor units that exert small forces (42) and the high correlation between innervation number and tetanic force of a motor unit (32). The fibers of a motor unit were scattered over a broad region of the muscle cross-section and intermingled with fibers belonging to many other units. Motor unit territories were randomly distributed within the muscle and were circular, except when constrained by the muscle boundary (e.g., MU 120 in Fig. 1). The density of fibers within the territory of the motor unit was assumed to be 20 fibers/mm2 but was increased when a portion of the motor unit territory was constrained by the muscle boundary. The result was little change in fiber density for small motor units, but a greater fiber density for the largest motor units, consistent with experimental findings (32).
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Simulation Conditions
Selected conditions were simulated to determine the influence of specific physiological and signal-detection parameters on EMG amplitude and amplitude cancellation. The model parameter values are shown in Table 1; the condition marked with asterisks is referred to as the default condition. Although the default parameters characterized the first dorsal interosseus muscle, the parameters of fiber length, subcutaneous tissue thickness, peak discharge rate, and recruitment range were varied to investigate the effect of changes within this muscle and across other muscles. For each condition, 11 levels of excitatory drive to the motor unit population were simulated: 5, 10, 20, 30, 40, 50, 60, 70, 80, 90, and 100% maximal excitation. The EMG was sampled at a rate of 4,096 samples/s.
Recording configuration. The simulated signals in the default condition were detected by using a bipolar configuration with an interelectrode distance of 10 mm and circular electrodes (4 mm diameter). The center of the recording configuration was halfway between the innervation zone and the distal tendon. The simulated bipolar recordings were compared with a belly-tendon configuration in which one electrode was placed over the belly of the muscle and the other near the metacarpophalangeal joint (53, 63). The belly-tendon configuration had one recording electrode halfway along the muscle and the other electrode was 32.4 mm away, past the distal tendon region.
Activation pattern. Most motor units in first dorsal interosseus are recruited at forces <50% maximal voluntary contraction (MVC) force (42). In other muscles, such as biceps brachii, recruitment has been observed at forces up to 85% MVC (7, 38). It has been suggested that variation in recruitment range may contribute to the different EMG-force relations observed experimentally (3, 21). The possibility that amplitude cancellation might vary with recruitment range was examined by simulating narrow and broad recruitment ranges. The upper limit of recruitment was 41% of maximal excitation for the narrow range and 68% of maximal excitation for the broad range.
As excitation to the motor neuron pool increases, the discharge rates of motor neurons increase up to a level where little further change in discharge rate is observed. Peak discharge rates vary across muscles (2, 59) and are sometimes greater for low-threshold motor units (6, 30), whereas others reported that high-threshold motor units reach greater discharge rates (25, 43). The influence of an increase in peak discharge rate on amplitude cancellation was examined by increasing peak discharge rates from the default condition (35–25 pps for MU 1 and MU 120, respectively) to 55–45 pps. In addition, a condition where high-threshold motor units achieved greater peak rates was simulated (25–35 pps), as well as a condition where the peak discharge rate was the same (30 pps) for the entire motor unit pool.
The increase in EMG amplitude that occurs when motor units discharge action potentials at about the same time, a condition known as motor unit synchronization, might be caused by a reduction in amplitude cancellation (37, 61). To assess this possibility, motor unit synchronization was examined by adjusting the timing of selected action potentials to impose a temporal association with action potentials discharged by different motor neurons (61). A function was applied that selected between 20 and 30% of the action potentials discharged by each motor unit to be synchronized with approximately eight other motor units with similar recruitment thresholds. Motor unit synchronization was quantified with the common input strength (CIS) index as the frequency of extra synchronous discharges (48). This function fixed CIS values near a value of two across the motor unit pool at all levels of excitation. To determine the level of motor unit synchronization across the motor unit pool, CIS values were calculated for every motor unit with the 15 preceding units and the 15 succeeding motor units.
Fiber length and subcutaneous tissue thickness. Fiber length and average location of the innervation zone in the first dorsal interosseus were determined experimentally using a linear electrode array consisting of 16-pin electrodes with 2.5 mm distance between electrodes. The bipolar recordings were amplified, band-pass filtered (10–500 Hz), digitized at 2,048 samples/s, and the resultant 15 channels were displayed on a computer monitor. The innervation zone was marked by visual inspection as the location where motor unit potentials began propagating in two directions. The tendon ending was denoted as the location where the propagation of the motor unit potential ceased (40). The Local Ethics Committee of the Health Department of Region Piemonte in Italy approved the measurements. On the basis of measurements from five men, average fiber length in the default condition was set at 40 mm and the center of the innervation zone was located 40% along the length of the fibers distal to the proximal attachment. Insertion of each fiber into the tendons varied randomly (uniform distribution) over a range of 5 mm, resulting in fiber lengths of 35–45 mm.
The properties of the tissues separating the muscle fibers and the recording electrodes are known to influence surface recordings (14, 50). An increase in subcutaneous tissue thickness attenuates the amplitude of the EMG signal and changes the frequency content of the signal (18, 50). To determine the default value for subcutaneous tissue thickness in the model, ultrasound recordings (FFsonic UF-4000L, Fukuda Denshi) were taken from the first dorsal interosseus of 12 individuals (11 men, age range: 22–59 yr), under approval of the Local Ethics Committee, with the probe (7.5 MHz transducer) positioned between the innervation zone and distal tendon. Thickness values ranged from 1.3 to 2.4 mm. On the basis of these recordings, the thickness of the subcutaneous tissue was set at 1.5 mm in the default condition.
Surface recordings of muscle-fiber action potentials are influenced by the propagation of the intracellular action potential along the fiber and its extinction at the end of the fiber. The end-of-fiber components influence the shape and the power spectrum of surface detected potentials (16). The relative influence of end-of-fiber components with respect to the propagating signal components depends on fiber length, thickness of the subcutaneous layers, and depth of the fiber (17). To evaluate the effect of surface-potential shape on amplitude cancellation, fiber lengths of 20 mm and 100 mm and subcutaneous tissue thickness of 1.0 and 3.5 mm were simulated and compared with the default condition (Table 1).
Motor unit properties. To examine the combined influence of motor unit properties on amplitude cancellation, simulations included factors that are known to change with advancing age: a reduction in the number of motor units and of the innervated muscle fibers, increased density of motor unit fibers and increased motor unit territory, increased area of the innervation zone, increased variability of the diameter of muscle fibers within a motor unit, and decreased diameter of large muscle fibers (11, 31, 36, 39, 46, 58). Table 1 summarizes the values that were used to simulate advancing age.
Data Analysis
The dependent variables of this study were the amplitude of the simulated EMG and the percent amplitude cancellation as a function of excitation level. Average values for the rectified EMG (average EMG) were determined over the interval from 1 to 5 s at each level of excitation. Amplitude cancellation involves the loss of signal when unrectified action potentials are summed together and there is an overlap of positive and negative phases of the potentials. Cancellation does not occur when individual action potentials are rectified before summation (Fig. 2). Percent loss in amplitude due to cancellation was quantified at each excitation level by computing the difference between EMG amplitude derived from rectified (No Cancellation) and unrectified (Cancellation) trains of motor unit potentials, expressed relative to the EMG amplitude in the No-Cancellation condition (5).
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The activation pattern was identical for all simulations with the exception of simulations for motor unit synchronization, recruitment range, peak discharge rate, and reduced motor unit number. Therefore, only the characteristics of the motor unit potentials changed between conditions. Four parameters describing the motor unit potential were calculated for each condition: peak-to-peak amplitude, area, duration, and normalized duration [area divided by amplitude (47)]. Correlation coefficients were calculated to determine the relation between these parameters of the motor unit potentials and the percent amplitude cancellation at 10, 50, and 100% excitation. Each parameter was calculated as the mean value for all 120 motor units across the 20 random motor unit locations.
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RESULTS |
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Quantification of Amplitude Cancellation in the Surface EMG
The difference between average EMGs computed from the sum of the rectified potentials (No Cancellation) and unrectified potentials (Cancellation) at each excitation level indicated that the amount of amplitude cancellation was substantial (Fig. 3A). In the default model, percent amplitude cancellation increased up to 61.7% at 100% maximal excitation. The values across all excitation levels for the default model are reported in Table 2.
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The convexity in normalized EMG values at intermediate levels of excitation may be caused by the recruitment of progressively larger motor units and therefore motor unit potentials with greater amplitudes. The possibility that the range of potential amplitudes influenced the amount of cancellation was examined by simulating a condition where each action potential had the same amplitude. Specifically, the potential for MU 1, MU 60, or MU 120 in the default condition was assigned to all 120 motor units. Identical motor unit potentials resulted in the same nonlinear relation depicted in Fig. 3. However, the percent amplitude cancellation increased up to 88% for MU 1, 85% for MU 60, and 80% for MU 120 at maximal levels of excitation (Table 2). Thus decreased variability in the range of amplitudes of the motor unit potentials increased amplitude cancellation, but it did not contribute to the nonlinear relation between excitation and EMG amplitude.
Amplitude Estimation and Recording Configuration
The EMG signal is often recorded using either the bipolar or belly-tendon recording configuration, and amplitude is commonly estimated by calculating either the average EMG or the root mean square (RMS) value. The RMS values were larger (Fig. 4A) and amplitude cancellation was less (Fig. 4B) for the RMS estimates compared with average EMG, regardless of the recording configuration that was simulated. However, when the absolute EMG values were normalized to the value at maximal excitation, the largest difference between the normalized values was <5% at 40% excitation (Fig. 4C).
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The influence of discharge rate variability on amplitude cancellation was examined by varying the coefficient of variation for discharge rate from 10 to 40%. The percent amplitude cancellation, averaged across excitation levels, was 49.8, 49.7, 49.7, and 49.5% when the coefficient of variation for discharge rate was 10, 20, 30, and 40%, respectively. Due to the minor change in percent cancellation with discharge rate variability, only one activation pattern (coefficient of variation = 20%) was used across those conditions that did not involve a direct examination of activation pattern.
The influence of recruitment range was investigated by simulating narrow and broad upper limits of motor unit recruitment. A broad recruitment range decreased normalized EMG values (Fig. 5A) and increased amplitude cancellation (Fig. 5C) at intermediate levels of excitation, with the largest difference (16%) in normalized values occurring near the point where motor unit recruitment was complete for the narrow recruitment range (41% maximal excitation). The influence of peak discharge rate was examined by varying the peak rate based on the recruitment threshold of the motor unit (Fig. 5, B and D). In contrast to the decrease in normalized values at intermediate levels of excitation with a broad recruitment range, normalized EMG values were 17% greater than the default condition when high-threshold motor units achieved higher discharge rates, with the largest difference occurring at 30% maximal excitation (Fig. 5B).
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Compared with the default condition, longer muscle fibers and thicker subcutaneous tissue decreased average EMG at maximal excitation by 10 and 42%, respectively (Fig. 7A). Amplitude cancellation was 10–15% greater for the longer fibers compared with shorter fibers, and thicker subcutaneous tissue caused only modest increases (
5%) in percent amplitude cancellation (Fig. 7B). The substantial increase in amplitude cancellation with increased fiber length appears to be attributable to corresponding increases in motor unit potential duration (results presented below). Normalized values showed the same relation depicted in Fig. 4C, with the greatest difference being 3% at 30% excitation.
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DISCUSSION |
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Identifying Neural Strategies from the Surface EMG
As a population index of motor unit activity, the surface EMG is used to examine neural strategies in a variety of conditions. For example, the surface EMG is used to compare the capabilities of young and old individuals and to evaluate adaptations in the same muscle before and after various interventions. In addition to the many factors known to influence EMG amplitude (16), however, the results of this study indicate that amplitude cancellation imposes a significant impediment to the identification of neural strategies from absolute surface EMG values.
The absolute amplitude of the surface EMG is commonly used in studies that compare young and old adults to determine whether differences exist in the ability of the nervous system to activate muscle (33, 45). For example, the finding of similar increases in maximal EMG amplitude in young and old adults after a training program has been interpreted as an increase in the neural drive to the trained muscles in both young and old adults (26). Such an interpretation is problematic because cancellation causes EMG amplitude to change due to factors that are independent of variation in neural drive, and EMG amplitude may be relatively insensitive to increases in motor unit activity at high excitation levels. For example, one would expect that an increase in the number of active motor units and muscle fibers would be accompanied by a large increase in the amplitude of the surface EMG. However, when the number of motor units was increased from 60 to 120 and the corresponding number of muscle fibers increased from 46,200 to 66,000, there was only a 15% increase in the amplitude of the EMG at maximal levels of excitation (Fig. 8A). The small increase in EMG amplitude with a doubling in motor unit number and a 43% increase in fiber number was due to an increase in amplitude cancellation (Fig. 8B). The results of this study demonstrate that amplitude cancellation confounds the interpretation of changes in absolute EMG amplitudes and limits the usefulness of measures that rely on absolute EMG values such as neuromuscular efficiency (9, 45).
Many factors influence EMG amplitude during muscle fatigue and confound its use as a measure of neural drive to muscle (10). It has been reported previously that although EMG amplitude increases during submaximal fatiguing contractions, the amplitude of the EMG is significantly less than maximum at the endurance limit for most subjects (23). It was proposed that the reduced EMG amplitude was due to a deficit in the ability to activate the muscle maximally, but two additional factors that enhance amplitude cancellation during a fatiguing contraction could also contribute to this observation. First, there is a decrease in muscle fiber conduction velocity that results in an increase in the duration of motor unit potentials during sustained contractions (54), leading to greater overlap between potentials (20) and an increase in amplitude cancellation (Figs. 8B and 9). However, the increase in potential duration can also augment EMG amplitude as the area of each motor unit potential increases (Fig. 8A). Second, sustained activation preferentially decreases the amplitude and area of the largest motor unit potentials (13), resulting in a more narrow range of amplitudes for the motor unit potentials. The current study demonstrated that a reduction in the range of potential amplitudes causes large increases in amplitude cancellation (Table 2). Hence, changes in the duration and range of amplitudes for the motor unit potentials can contribute to the inability of EMG amplitude to reach maximal levels after a fatiguing contraction, independent of any deficit in the capacity to activate the muscle.
Normalized EMG Values
It is common practice to normalize EMG values to the amplitude of the EMG at maximal levels of excitation so that comparisons can be made across muscles, between subjects, and between days. Normalized EMG values are less variable than absolute values, and therefore considered a more reliable index of muscle activation (60). Although the nonlinear increase in EMG values with increasing excitation has been demonstrated previously (5, 44, 49), the impact of this nonlinear relation on the normalized surface EMG values has not been addressed.
The greater probability of cancellation with increased motor unit activity has been referred to as a "saturation" effect (49) and as a downward nonlinearity (5) due to the failure of the EMG to increase at the same rate as motor unit activity. The current study demonstrates that amplitude cancellation did not increase linearly across excitation levels (Fig. 3), which resulted in an overestimation of motor neuron activity at intermediate levels of excitation when the EMG was normalized to maximal levels. Furthermore, variation in the range of amplitudes for the motor unit potentials did not alter the normalized EMG values and neither the method used to estimate the amplitude (RMS or average EMG) nor the recording technique (bipolar or belly-tendon) influenced the relation between normalized EMG and excitation (Fig. 4B). Therefore, the nonlinear relation between EMG and excitation was due to an increase in the probability of cancellation with increasing levels of motor unit activity.
The importance of this nonlinearity between normalized EMG and excitation likely depends on the type of comparison being made. Examination of those figures depicting percent amplitude cancellation across excitation levels (Figs. 4B; 5, B and D; 7B; and 8B) demonstrates that whereas the absolute amount of cancellation may vary across conditions, variation in specific conditions resulted in little change in normalized EMG values. This finding likely explains the reduced variability and increased reliability in normalized EMG values compared with absolute EMG values (41, 60). The two conditions that demonstrated the largest change in normalized EMG values (variation in recruitment range and peak discharge rates) resulted in a difference with the default condition of up to 17%, and this difference was limited to intermediate levels of excitation. The results of the study suggest caution in interpreting different levels of normalized surface EMG in muscles where recruitment range or peak discharge rates may vary, particularly at intermediate levels of excitation.
Motor Unit Synchronization
The current study found that EMG amplitude increased with motor unit synchronization, but the increase was much less than that reported previously (37, 61). There are at least two factors that may explain this difference. First, variability in the timing of synchronization between surface-recorded motor unit potentials is influenced by variability in motor unit conduction velocities, innervation zone locations, and tendon endings (Fig. 6). Each source of variability contributes to the failure of EMG amplitude to increase with motor unit synchronization. Second, constraining the imposed synchrony to motor units with similar recruitment thresholds reduced the chance of all motor units in the pool being synchronized with one another. Because high levels of synchrony involve many discharges that are nearly coincidental, the increase in overlap between potentials generates both in-phase and out-of-phase alignment between potentials and causes both increased and decreased amounts of amplitude cancellation with increases in motor unit synchronization. Even if higher levels of motor unit synchronization were imposed, a minimal increase in EMG amplitude would be expected due to the generation of both in-phase and out-of-phase alignments. In contrast, Zhou and Rymer (62) observed that modeling only variation in the timing of the synchronized motor units resulted in less out-of-phase alignments as the duration of the motor unit potentials increased and, therefore, there was less cancellation. Variation in conduction velocities and the random location of the innervation zones simulated in the current study influenced the increase in amplitude with synchronization. Thus systematic evaluation of the variability in the timing of the motor unit potentials suggests that motor unit synchronization has only a modest effect on EMG amplitude.
Limitations
There is a lack of information regarding the range of motor unit properties in a muscle (12), with limited information on the distribution of motor unit numbers, conduction velocities, peak discharge rates, and motor unit synchronization across the entire population. The information that does exist suggests great variability in many of the relevant physiological parameters that influence the EMG signal. The current study was limited in scope and identified selected motor unit properties that are likely to vary in different muscles and across different populations. Accordingly, measurements were made to provide realistic values for subcutaneous tissue thickness and fiber length. The surface EMG model of Fuglevand et al. (22) was updated with a model that has been validated to produce realistic motor unit potentials (15). Also the modeling approach allowed the assessment of the contribution of individual parameters to the surface EMG, something rarely possible during experimental studies. Despite the assumptions used in the current modeling study, however, the results are consistent with the one experimental study that systematically quantified amplitude cancellation using an experimental protocol (5).
In summary, up to 62% of the surface EMG signal amplitude was lost due to cancellation. The degree of signal loss depended on selected physiological parameters, especially the number of active motor units and the duration of the action potentials. Nonetheless, normalization of the surface EMG amplitude to the values obtained with maximal activation increases the reliability of the measurement. Although normalized EMG values overestimate the amount of motor unit activity at intermediate levels of activation by up to 13%, the importance of this nonlinearity is likely minimized as normalized values are largely invariant to changes in different parameters. These results have implications for identifying neural strategies from the surface EMG, particularly when comparing absolute EMG values or when assessing fatigue-related changes in EMG.
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The costs of publication of this article were defrayed in part by the payment of page charges. The article must therefore be hereby marked "advertisement" in accordance with 18 U.S.C. Section 1734 solely to indicate this fact.
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J. Duchateau, J. G. Semmler, and R. M. Enoka Training adaptations in the behavior of human motor units J Appl Physiol, December 1, 2006; 101(6): 1766 - 1775. [Abstract] [Full Text] [PDF]
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B. Pasquet, A. Carpentier, and J. Duchateau Specific modulation of motor unit discharge for a similar change in fascicle length during shortening and lengthening contractions in humans J. Physiol., December 1, 2006; 577(2): 753 - 765. [Abstract] [Full Text] [PDF]
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M. Amann, L. M. Romer, D. F. Pegelow, A. J. Jacques, C. J. Hess, and J. A. Dempsey Effects of arterial oxygen content on peripheral locomotor muscle fatigue J Appl Physiol, July 1, 2006; 101(1): 119 - 127. [Abstract] [Full Text] [PDF]
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 J P Weir, T W Beck, J T Cramer, T J Housh, T D Noakes, A St Clair Gibson, and E V Lambert Is fatigue all in your head? A critical review of the central governor model * Commentary. Br. J. Sports Med., July 1, 2006; 40(7): 573 - 586. [Abstract] [Full Text] [PDF]
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K. G. Keenan, D. Farina, R. Merletti, and R. M. Enoka Amplitude cancellation reduces the size of motor unit potentials averaged from the surface EMG J Appl Physiol, June 1, 2006; 100(6): 1928 - 1937. [Abstract] [Full Text] [PDF]
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C. K. Thomas, R. S. Johansson, and B. Bigland-Ritchie EMG Changes in Human Thenar Motor Units With Force Potentiation and Fatigue J Neurophysiol, March 1, 2006; 95(3): 1518 - 1526. [Abstract] [Full Text] [PDF]
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B. Pasquet, A. Carpentier, and J. Duchateau Change in Muscle Fascicle Length Influences the Recruitment and Discharge Rate of Motor Units During Isometric Contractions J Neurophysiol, November 1, 2005; 94(5): 3126 - 3133. [Abstract] [Full Text] [PDF]
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M. Shinohara, C. T. Moritz, M. A. Pascoe, and R. M. Enoka Prolonged muscle vibration increases stretch reflex amplitude, motor unit discharge rate, and force fluctuations in a hand muscle J Appl Physiol, November 1, 2005; 99(5): 1835 - 1842. [Abstract] [Full Text] [PDF]
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M. Levenez, C. Kotzamanidis, A. Carpentier, and J. Duchateau Spinal reflexes and coactivation of ankle muscles during a submaximal fatiguing contraction J Appl Physiol, September 1, 2005; 99(3): 1182 - 1188. [Abstract] [Full Text] [PDF]
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K. S. Maluf and R. M. Enoka Task failure during fatiguing contractions performed by humans J Appl Physiol, August 1, 2005; 99(2): 389 - 396. [Abstract] [Full Text] [PDF]
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M. Gazzoni, F. Camelia, and D. Farina Conduction Velocity of Quiescent Muscle Fibers Decreases During Sustained Contraction J Neurophysiol, July 1, 2005; 94(1): 387 - 394. [Abstract] [Full Text] [PDF]
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 E. Simoneau, A. Martin, and J. Van Hoecke Muscular Performances at the Ankle Joint in Young and Elderly Men J. Gerontol. A Biol. Sci. Med. Sci., April 1, 2005; 60(4): 439 - 447. [Abstract] [Full Text] [PDF]
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C Westad and R. H Westgaard The influence of contraction amplitude and firing history on spike-triggered averaged trapezius motor unit potentials J. Physiol., February 1, 2005; 562(3): 965 - 975. [Abstract] [Full Text] [PDF]
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