Motor unit control and force fluctuation during fatigue

Muscle fatigue increases beta-band coherence between the firing times of simultaneously active motor units in the first dorsal interosseous muscle

Synchronization between the firing times of simultaneously active motor units (MUs) is generally assumed to increase during fatiguing contractions. To date, however, estimates of MU synchronization have relied on indirect measures, derived from surface electromyographic (EMG) interference signals. This study used intramuscular coherence to investigate the correlation between MU discharges in the first dorsal interosseous muscle during and immediately following a submaximal fatiguing contraction, and after rest. Coherence between composite MU spike trains, derived from decomposed surface EMG, were examined in the delta (1-4 Hz), alpha (8-12 Hz), beta (15-30 Hz), and gamma (30-60 Hz) frequency band ranges. A significant increase in MU coherence was observed in the delta, alpha, and beta frequency bands postfatigue. In addition, wavelet coherence revealed a tendency for delta-, alpha-, and beta-band coherence to increase during the fatiguing contraction, with subjects exhibiting low initial coherence values displaying the greatest relative increase. This was accompanied by an increase in MU short-term synchronization and a decline in mean firing rate of the majority of MUs detected during the sustained contraction. A model of the motoneuron pool and surface EMG was used to investigate factors influencing the coherence estimate. Simulation results indicated that changes in motoneuron inhibition and firing rates alone could not directly account for increased beta-band coherence postfatigue. The observed increase is, therefore, more likely to arise from an increase in the strength of correlated inputs to MUs as the muscle fatigues.

Acute effects of concentric vs. eccentric exercise on force steadiness and electromyographic responses of the forearm flexors

The purpose of this study was to examine the acute effects of concentric (CON) vs. eccentric (ECC) exercise on isometric strength, force steadiness, and surface electromyographic (EMG) responses of the forearm flexors. Fifteen resistance-trained men (mean ± SD: age = 23.7 ± 3.5 years; height = 178.9 ± 4.7 cm; body weight = 86.2 ± 9.8 kg) performed 6 sets of 10 maximal CON isokinetic or ECC isokinetic muscle actions using the dominant forearm flexors on 2 separate experimental visits. Before and immediately after the exercise interventions, isometric strength testing and submaximal trapezoid isometric contractions were performed, with bipolar EMG signals detected from the biceps brachii. The coefficient of variation of the force output from the mid 8-second portion of each submaximal trapezoid isometric contraction was calculated to assess force steadiness. In addition, the EMG signal was selected from the same portion as the force signal. The results showed that both CON and ECC caused similar isometric strength losses, but ECC caused a greater loss of force steadiness than CON. In addition, EMG amplitude increased similarly after both exercise interventions, but the magnitude of the increase in EMG mean frequency after ECC tended to be smaller, when compared with that after CON. These findings suggested that, even for resistance-trained individuals that are more resistant to ECC exercise-induced muscle damage than untrained individuals, their ability to maintain a steady submaximal force can be impaired after a bout of ECC exercise.

The effect of cognitive fatigue on prefrontal cortex correlates of neuromuscular fatigue in older women

BACKGROUND

As the population of adults aged 65 and above is rapidly growing, it is crucial to identify physical and cognitive limitations pertaining to daily living. Cognitive fatigue has shown to adversely impact neuromuscular function in younger adults, however its impact on neuromuscular fatigue, and associated brain function changes, in older adults is not well understood. The aim of the study was to examine the impact of cognitive fatigue on neuromuscular fatigue and associated prefrontal cortex (PFC) activation patterns in older women.

METHODS

Eleven older (75.82 (7.4) years) females attended two sessions and performed intermittent handgrip exercises at 30 % maximum voluntary contraction (MVC) until voluntary exhaustion after a 60-min control (watching documentary) and 60-min cognitive fatigue (performing Stroop Color Word and 1-Back tests) condition. Dependent measures included endurance time, strength loss, PFC activity (measured using fNIRS), force fluctuations, muscle activity, cardiovascular responses, and perceived discomfort.

RESULTS

Participants perceived greater cognitive fatigue after the 60-min cognitive fatigue condition when compared to the control condition. While neuromuscular fatigue outcomes (i.e., endurance time, strength loss, perceived discomfort), force fluctuations, and muscle activity were similar across both the control and cognitive fatigue conditions, greater decrements in PFC activity during neuromuscular fatigue development after the cognitive fatigue condition were observed when compared to the control condition.

CONCLUSION

Despite similar neuromuscular outcomes, cognitive fatigue was associated with blunted PFC activation during the handgrip fatiguing exercise that may be indicative of neural adaptation with aging in an effort to maintain motor performance. Examining the relationship between cognitive fatigue and neuromuscular output by imaging other motor-related brain regions are needed to provide a better understanding of age-related compensatory adaptations to perform daily tasks that involve some levels of cognitive demand and physical exercise, especially when older adults experience them sequentially.

Synchronization of motor unit firings: an epiphenomenon of firing rate characteristics not common inputs

Synchronous motor unit firing instances have been attributed to anatomical inputs shared by motoneurons. Yet, there is a lack of empirical evidence confirming the notion that common inputs elicit synchronization under voluntary conditions. We tested this notion by measuring synchronization between motor unit action potential trains (MUAPTs) as their firing rates progressed within a contraction from a relatively low force level to a higher one. On average, the degree of synchronization decreased as the force increased. The common input notion provides no empirically supported explanation for the observed synchronization behavior. Therefore, we investigated a more probable explanation for synchronization. Our data set of 17,546 paired MUAPTs revealed that the degree of synchronization varies as a function of two characteristics of the motor unit firing rate: the similarity and the slope as a function of force. Both are measures of the excitation of the motoneurons. As the force generated by the muscle increases, the firing rate slope decreases, and the synchronization correspondingly decreases. Different muscles have motor units with different firing rate characteristics and display different amounts of synchronization. Although this association is not proof of causality, it consistently explains our observations and strongly suggests further investigation. So viewed, synchronization is likely an epiphenomenon, subject to countless unknown neural interactions. As such, synchronous firing instances may not be the product of a specific design and may not serve a specific physiological purpose. Our explanation for synchronization has the advantage of being supported by empirical evidence, whereas the common input does not.

Knee extension torque variability after exercise in ACL reconstructed knees

The purpose of this study was to compare knee extension torque variability in patients with ACL reconstructed knees before and after exercise. Thirty two patients with an ACL reconstructed knee (ACL-R group) and 32 healthy controls (control group) completed measures of maximal isometric knee extension torque (90° flexion) at baseline and following a 30-min exercise protocol (post-exercise). Exercise included 30-min of repeated cycles of inclined treadmill walking and hopping tasks. Dependent variables were the coefficient of variation (CV) and raw-change in CV (ΔCV): CV = (torque standard deviation/torque mean x 100), ΔCV = (post-exercise - baseline). There was a group-by-time interaction (p = 0.03) on CV. The ACL-R group demonstrated greater CV than the control group at baseline (ACL-R = 1.07 ± 0.55, control = 0.79 ± 0.42, p = 0.03) and post-exercise (ACL-R = 1.60 ± 0.91, control = 0.94 ± 0.41, p = 0.001). ΔCV was greater (p = 0.03) in the ACL-R group (0.52 ± 0.82) than control group (0.15 ± 0.46). CV significantly increased from baseline to post-exercise (p = 0.001) in the ACL-R group, while the control group did not (p = 0.06). The ACL-R group demonstrated greater knee extension torque variability than the control group. Exercise increased torque variability more in the ACL-R group than control group.

Local muscle endurance is associated with fatigue-based changes in electromyographic spectral properties, but not with conduction velocity

The purpose of this study was to examine the associations amongst muscle fiber action potential conduction velocity (CV), spectral characteristics of the surface electromyographic (EMG) signal, and endurance time during a sustained submaximal isometric muscle action. Eleven men (mean±SD age=23±4yrs) performed a sustained, submaximal isometric muscle action of the dominant forearm flexors at 60% of the maximum voluntary contraction (MVC) until the designated force level could no longer be maintained. Sixteen separate bipolar surface EMG signals were detected from the biceps brachii with a linear electrode array during this contraction. Two channels from this array were used to measure CV, and one of these two channels was used for further EMG signal processing. The channels that provided the highest signal quality were used for the CV measurements and further data analysis. A wavelet analysis was then used to analyze the bipolar EMG signal, and the resulting wavelet spectrum was decomposed with a nonparametric spectral decomposition procedure. The results showed that the time to exhaustion during the sustained contraction was not correlated with the rate of decrease in CV, but it was highly correlated with both the decrease in high-frequency spectral power (r=0.947) and the increase in low-frequency spectral power (r=0.960). These findings are particularly interesting, considering that the decrease in traditional EMG spectral variables (e.g., mean frequency or median frequency) with fatigue is generally attributed to reductions in CV. While this may indeed be true, the present results suggested that other factors (i.e., other than CV) that can affect the shape of the EMG frequency spectrum during fatigue are more important in determining the endurance capabilities of the muscle than is CV.

Fatigue reduces the complexity of knee extensor torque fluctuations during maximal and submaximal intermittent isometric contractions in man

Neuromuscular fatigue increases the amplitude of fluctuations in torque output during isometric contractions, but the effect of fatigue on the temporal structure, or complexity, of these fluctuations is not known. We hypothesised that fatigue would result in a loss of temporal complexity and a change in fractal scaling of the torque signal during isometric knee extensor exercise. Eleven healthy participants performed a maximal test (5 min of intermittent maximal voluntary contractions, MVCs), and a submaximal test (contractions at a target of 40% MVC performed until task failure), each with a 60% duty factor (6 s contraction, 4 s rest). Torque and surface EMG signals were sampled continuously. Complexity and fractal scaling of torque were quantified by calculating approximate entropy (ApEn), sample entropy (SampEn) and the detrended fluctuation analysis (DFA) scaling exponent α. Fresh submaximal contractions were more complex than maximal contractions (mean ± SEM, submaximal vs. maximal: ApEn 0.65 ± 0.09 vs. 0.15 ± 0.02; SampEn 0.62 ± 0.09 vs. 0.14 ± 0.02; DFA α 1.35 ± 0.04 vs. 1.55 ± 0.03; all P < 0.005). Fatigue reduced the complexity of submaximal contractions (ApEn to 0.24 ± 0.05; SampEn to 0.22 ± 0.04; DFA α to 1.55 ± 0.03; all P < 0.005) and maximal contractions (ApEn to 0.10 ± 0.02; SampEn to 0.10 ± 0.02; DFA α to 1.63 ± 0.02; all P < 0.01). This loss of complexity and shift towards Brownian-like noise suggests that as well as reducing the capacity to produce torque, fatigue reduces the neuromuscular system's adaptability to external perturbations.

Statistically rigorous calculations do not support common input and long-term synchronization of motor-unit firings

Over the past four decades, various methods have been implemented to measure synchronization of motor-unit firings. In this work, we provide evidence that prior reports of the existence of universal common inputs to all motoneurons and the presence of long-term synchronization are misleading, because they did not use sufficiently rigorous statistical tests to detect synchronization. We developed a statistically based method (SigMax) for computing synchronization and tested it with data from 17,736 motor-unit pairs containing 1,035,225 firing instances from the first dorsal interosseous and vastus lateralis muscles--a data set one order of magnitude greater than that reported in previous studies. Only firing data, obtained from surface electromyographic signal decomposition with >95% accuracy, were used in the study. The data were not subjectively selected in any manner. Because of the size of our data set and the statistical rigor inherent to SigMax, we have confidence that the synchronization values that we calculated provide an improved estimate of physiologically driven synchronization. Compared with three other commonly used techniques, ours revealed three types of discrepancies that result from failing to use sufficient statistical tests necessary to detect synchronization. 1) On average, the z-score method falsely detected synchronization at 16 separate latencies in each motor-unit pair. 2) The cumulative sum method missed one out of every four synchronization identifications found by SigMax. 3) The common input assumption method identified synchronization from 100% of motor-unit pairs studied. SigMax revealed that only 50% of motor-unit pairs actually manifested synchronization.

Motor unit firing rate patterns during voluntary muscle force generation: a simulation study

OBJECTIVE

Muscle force is generated by a combination of motor unit (MU) recruitment and changes in the discharge rate of active MUs. There have been two basic MU recruitment and firing rate paradigms reported in the literature, which describe the control of the MUs during force generation. The first (termed the reverse 'onion skin' profile), exhibits lower firing rates for lower threshold units, with higher firing rates occurring in higher threshold units. The second (termed the 'onion skin' profile), exhibits an inverse arrangement, with lower threshold units reaching higher firing rates.

APPROACH

Using a simulation of the MU activity in a hand muscle, this study examined the force generation capacity and the variability of the muscle force magnitude at different excitation levels of the MU pool under these two different MU control paradigms. We sought to determine which rate/recruitment scheme was more efficient for force generation, and which scheme gave rise to the lowest force variability.

MAIN RESULTS

We found that the force output of both firing patterns leads to graded force output at low excitation levels, and that the force generation capacity of the two different paradigms diverged around 50% excitation. In the reverse 'onion skin' pattern, at 100% excitation, the force output reached up to 88% of maximum force, whereas for the 'onion skin' pattern, the force output only reached up to 54% of maximum force at 100% excitation. The force variability was lower at the low to moderate force levels under the 'onion skin' paradigm than with the reverse 'onion skin' firing patterns, but this effect was reversed at high force levels.

SIGNIFICANCE

This study captures the influence of MU recruitment and firing rate organization on muscle force properties, and our results suggest that the different firing organizations can be beneficial at different levels of voluntary muscle force generation and perhaps for different tasks.

Swing kinematics of male and female skilled golfers following prolonged putting practice

Given that males and females respond differently to endurance-based tasks, prolonged putting practice may provide an avenue to examine gender-related differences in golf swing kinematics. The aim of this project was to determine if 40 min of putting affects thorax and pelvis kinematics during the full swing of males and females. Three-dimensional trunk kinematics were collected during the swings of 19 male (age: 26 ± 7 years, handicap: 0.6 ± 1.1) and 17 female (age: 24 ± 7 years, handicap: 1.4 ± 1.7) golfers before and after 40 min of putting. Angular displacement at address, top of backswing and ball contact for the pelvis, thorax, and pelvis-thorax interaction were calculated, in addition to the magnitude of peak angular velocity and repeatability of continuous segment angular velocities. Female golfers had less pelvis and thorax anterior-posterior tilt at address, less thorax and thorax-pelvis axial rotation at top of backswing, and less pelvis and thorax axial rotation and pelvis lateral tilt at ball contact pre- to post-putting. Analysis of peak angular velocities revealed that females had significantly lower thorax-pelvis lateral tilt velocity pre- to post-putting. In conclusion, an endurance-based putting intervention affects females' thorax and pelvis orientation angles and velocities to a greater extent than males.

Fatigue effect on low-frequency force fluctuations and muscular oscillations during rhythmic isometric contraction

Continuous force output containing numerous intermittent force pulses is not completely smooth. By characterizing force fluctuation properties and force pulse metrics, this study investigated adaptive changes in trajectory control, both force-generating capacity and force fluctuations, as fatigue progresses. Sixteen healthy subjects (20-24 years old) completed rhythmic isometric gripping with the non-dominant hand to volitional failure. Before and immediately following the fatigue intervention, we measured the gripping force to couple a 0.5 Hz sinusoidal target in the range of 50-100% maximal voluntary contraction. Dynamic force output was off-line decomposed into 1) an ideal force trajectory spectrally identical to the target rate; and 2) a force pulse trace pertaining to force fluctuations and error-correction attempts. The amplitude of ideal force trajectory regarding to force-generating capacity was more suppressed than that of the force pulse trace with increasing fatigue, which also shifted the force pulse trace to lower frequency bands. Multi-scale entropy analysis revealed that the complexity of the force pulse trace at high time scales increased with fatigue, contrary to the decrease in complexity of the force pulse trace at low time scales. Statistical properties of individual force pulses in the spatial and temporal domains varied with muscular fatigue, concurrent with marked suppression of gamma muscular oscillations (40-60 Hz) in the post-fatigue test. In conclusion, this study first reveals that muscular fatigue impairs the amplitude modulation of force pattern generation more than it affects the amplitude responsiveness of fine-tuning a force trajectory. Besides, motor fatigue results disadvantageously in enhancement of motor noises, simplification of short-term force-tuning strategy, and slow responsiveness to force errors, pertaining to dimensional changes in force fluctuations, scaling properties of force pulse, and muscular oscillation.

Synchronization of low- and high-threshold motor units

INTRODUCTION

We examined the degree of synchronization for both low- and high-threshold motor unit (MU) pairs at high force levels.

METHODS

MU spike trains were recorded from the quadriceps during high-force isometric leg extensions. Short-term synchronization (between -6 and 6 ms) was calculated for every unique MU pair for each contraction.

RESULTS

At high force levels, earlier recruited motor unit pairs (low-threshold) demonstrated relatively low levels of short-term synchronization (approximately 7.3% extra firings than would have been expected by chance). However, the magnitude of synchronization increased significantly and linearly with mean recruitment threshold (reaching 22.1% extra firings for motor unit pairs recruited above 70% MVC).

CONCLUSIONS

Three potential mechanisms that could explain the observed differences in synchronization across motor unit types are proposed and discussed.

Age-related modifications to the magnitude and periodicity of neuromuscular noise

Background

Evaluation of task related outcomes within geriatric and fall-prone populations is essential not only for identification of neuromuscular deficits, but also for effective implementation of fall prevention strategies. As most tasks and activities of daily living are performed at submaximal force levels, restoration of muscle strength often does not produce the expected benefit in functional capacity. However, it is known that muscular control plays a key role in the performance of functional tasks, but it remains unclear to what degree muscular control and the associated neuromuscular noise (NmN) is age-related, particularly in the lower-extremities.

Objectives

The aim of this study was to determine the effects of age and fall-pathology on the magnitude as well as the frequency of NmN during lower extremity force production.

Methods

Sixteen young healthy adults, as well as seventy elderly women (36 healthy, 34 elderly fallers), performed force production tests at moderate levels (15% of maximum voluntary isometric contractions).

Results

Elderly fallers exhibited the highest magnitude of NmN, while the highest frequency components of NmN tended to occur in the healthy elderly. Young subjects exhibited significantly more power in the low frequency ranges than either of the elderly groups, and had the lowest levels of NmN.

Conclusion

These data suggest increased degeneration of muscular control through greater NmN in elderly fallers compared to healthy elderly or young subjects. This could possibly be associated with muscle atrophy and lower levels of motor unit synchronisation.

Spatial reorganisation of muscle activity correlates with change in tangential force variability during isometric contractions

The aim of this study was to quantify the effects of spatial reorganisation of muscle activity on task-related and tangential components of force variability during sustained contractions. Three-dimensional forces were measured from isometric elbow flexion during submaximal contractions (50s, 5-50% of maximal voluntary contraction (MVC)) and total excursion of the centre of pressure was extracted. Spatial electromyographic (EMG) activity was recorded from the biceps brachii muscle. The centroids of the root mean square (RMS) EMG and normalised mutual information (NMI) maps were computed to assess spatial muscle activity and spatial relationship between EMG and task-related force variability, respectively. Result showed that difference between the position of the centroids at the beginning and at the end of the contraction of the RMS EMG and the NMI maps were different in the medial-lateral direction (P<0.05), reflecting that muscle regions modulate their activity without necessarily modulating the contribution to the task-related force variability over time. Moreover, this difference between shifts of the centroids was positively correlated with the total excursion of the centre of pressure at the higher levels of contractions (>30% MVC, R(2)>0.30, P<0.05), suggesting that changes in spatial muscle activity could impact on the modulation of tangential forces. Therefore, within-muscle adaptations do not necessarily increase force variability, and this interaction can be quantified by analysing the RMS EMG and the NMI map centroids.

Obesity-related differences in neural correlates of force control

BACKGROUND

Greater body segment mass due to obesity has shown to impair gross and fine motor functions and reduce balance control. While recent studies suggest that obesity may be linked with altered brain functions involved in fine motor tasks, this association is not well investigated.

OBJECTIVE

The purpose of this study was to examine the neural correlates of motor performance in non-obese and obese adults during force control of two upper extremity muscles.

METHODS

Nine non-obese and eight obese young adults performed intermittent handgrip and elbow flexion exertions at 30% of their respective muscle strengths for 4 min. Functional near infrared spectroscopy was employed to measure neural activity in the prefrontal cortex bilaterally, joint steadiness was computed using force fluctuations, and ratings of perceived exertions (RPEs) were obtained to assess perceived effort.

RESULTS

Obesity was associated with higher force fluctuations and lower prefrontal cortex activation during handgrip exertions, while RPE scores remained similar across both groups. No obesity-related differences in neural activity, force fluctuation, or RPE scores were observed during elbow flexion exertions.

CONCLUSION

The study is one of the first to examine obesity-related differences on prefrontal cortex activation during force control of the upper extremity musculature. The study findings indicate that the neural correlates of motor activity in the obese may be muscle-specific. Future work is warranted to extend the investigation to monitoring multiple motor-function related cortical regions and examining obesity differences with different task parameters (e.g., longer duration, increased precision demands, larger muscles, etc.).

Decomposition of intramuscular EMG signals using a knowledge -based certainty classifier algorithm

An automated system for resolving an intramuscular electromyographic (EMG) signal into its constituent motor unit potential trains (MUPTs) is presented. The system is intended mainly for clinical applications where several physiological parameters for each motor unit (MU), such as the motor unit potential (MUP) template and mean firing rate, are required. The system decomposes an EMG signal off-line by filtering the signal, detecting MUPs, and then grouping the detected MUPs using a clustering and a supervised classification algorithm. Both the clustering and supervised classification algorithms use MUP shape and MU firing pattern information to group MUPs into several MUPTs. Clustering is partially based on the K-means clustering algorithm. Supervised classification is implemented using a certainty-based classifier technique that employs a knowledge-based system to merge trains, detect and correct invalid trains, as well as adjust the assignment threshold for each train. The accuracy (93.2%±5.5%), assignment rate (93.9%±2.6%), and error in estimating the number of MUPTs (0.3±0.5) achieved for 10 simulated EMG signals comprised of 3-11 MUPTs are encouraging for using the system for decomposing various EMG signals.

Strength asymmetry increases gait asymmetry and variability in older women

PURPOSE

The aim of the research was to determine how knee extensor strength asymmetry influences gait asymmetry and variability because these gait parameters have been related to mobility and falls in older adults.

METHODS

Strength of the knee extensors was measured in 24 older women (65-80 yr). Subjects were separated into symmetrical strength (SS, n = 13) and asymmetrical strength (SA, n = 11) groups using an asymmetry cutoff of 20%. Subjects walked at a standard speed of 0.8 m·s and at maximal speed on an instrumented treadmill while kinetic and spatiotemporal gait variables were measured. Gait and strength asymmetry were calculated as the percentage difference between legs and gait variability as the coefficient of variation over 20 sequential steps.

RESULTS

SA had greater strength asymmetry (27.4% ± 5.5%) than SS (11.7% ± 5.4%, P < 0.001). Averaged across speeds, SA had greater single- (7.1% vs. 2.5%) and double-limb support time asymmetry (7.0% vs. 4.3%) than SS and greater single-limb support time variability (9.7% vs. 6.6%, all P < 0.05). Group × speed interactions occurred for weight acceptance force variability (P = 0.02) and weight acceptance force asymmetry (P = 0.017) with greater variability at the maximal speed in SA (5.0% ± 2.4% vs. 3.7% ± 1.2%) and greater asymmetry at the maximal speed in SA (6.4% ± 5.3% vs. 2.5% ± 2.3%).

CONCLUSION

Gait variability and asymmetry are greater in older women with strength asymmetry and increase when they walk near their maximal capacities. The maintenance of strength symmetry, or development of symmetry through unilateral exercise, may be beneficial in reducing gait asymmetry, gait variability, and fall risk in older adults.

Neural control of muscle force: indications from a simulation model

We developed a model to investigate the influence of the muscle force twitch on the simulated firing behavior of motoneurons and muscle force production during voluntary isometric contractions. The input consists of an excitatory signal common to all the motor units in the pool of a muscle, consistent with the "common drive" property. Motor units respond with a hierarchically structured firing behavior wherein at any time and force, firing rates are inversely proportional to recruitment threshold, as described by the "onion skin" property. Time- and force-dependent changes in muscle force production are introduced by varying the motor unit force twitches as a function of time or by varying the number of active motor units. A force feedback adjusts the input excitation, maintaining the simulated force at a target level. The simulations replicate motor unit behavior characteristics similar to those reported in previous empirical studies of sustained contractions: 1) the initial decrease and subsequent increase of firing rates, 2) the derecruitment and recruitment of motor units throughout sustained contractions, and 3) the continual increase in the force fluctuation caused by the progressive recruitment of larger motor units. The model cautions the use of motor unit behavior at recruitment and derecruitment without consideration of changes in the muscle force generation capacity. It describes an alternative mechanism for the reserve capacity of motor units to generate extraordinary force. It supports the hypothesis that the control of motoneurons remains invariant during force-varying and sustained isometric contractions.

Adaptations to fatigue of a single digit violate the principle of superposition in a multi-finger static prehension task

We investigated the effects of exercise-induced fatigue of a digit on the biomechanics of a static prehension task. The participants were divided into two groups. One group performed the fatiguing exercise using the thumb (group-thumb) and the second group performed the exercise using the index finger (group-index). We analyzed the prehensile action as being based on a two-level hierarchy. Our first hypothesis was that fatigue of the thumb would have stronger effects at the upper level (action shared between the thumb and all four fingers combined-virtual finger) and fatigue of the index finger would have stronger effects at the lower level of the hierarchy (action of the virtual finger shared among actual fingers). We also hypothesized that fatigue would cause a decrease in the normal force applied by the exercised digit and correspondingly lead to a decrease in the normal force applied by the opposing digit(s). Our third hypothesis was that fatigue would leave the tangential forces unaffected. Fatigue led to a significant drop in the normal force of both exercised and non-exercised (opposing) digits. The tangential forces of the exercised digits increased after fatigue. This led to a drop in the safety margin in the group-thumb, but not group-index. As such, the results supported the first two hypotheses but not the third hypothesis. Overall, the results suggested that fatigue triggered a chain reaction that involved both forces and moments of force produced by individual digits leading to a violation of the principle of superposition. The findings are interpreted within the framework of the referent configuration hypothesis.

Increases of quadriceps inter-muscular cross-correlation and coherence during exhausting stepping exercise

The aim of this study was to examine the change of the intermuscular cross-correlation and coherence of the rectus femoris (RF), vastus medialis (VM) and vastus lateralis (VL) during exhausting stepping exercise. Eleven healthy adults repeated the stepping exercise up to their individual endurance limits (RPE score reached 20), and the cross-correlation and coherence were assessed by surface electromyography (EMG) recordings. The coefficient and time lag of cross-correlation and the coherence areas in the alpha (8–12 Hz), beta (15–30 Hz), gamma (30–60 Hz) and high-gamma (60–150 Hz) bands among the three muscle pairs (RF-VM, RF-VL and VM-VL) were calculated. As muscle fatigue, RF-VM and VM-VL showed increases of coefficients and the shortening of time lags. RF-VM and RF-VL showed increases of beta-band coherence in the ascent and descent phases, respectively. The increased intermuscular cross-correlation and beta-band coherence may be a compensatory strategy for maintaining the coordination of knee synergistic muscles during fatigue due to the fatigue-related disturbance of the corticospinal transmission. Therefore, the intermuscular cross-correlation and beta-band coherence may be a potential index for assessing muscle fatigue and monitoring the central control of motor function during dynamic fatiguing exercise.

EMG signal decomposition using motor unit potential train validity

A system to resolve an intramuscular electromyographic (EMG) signal into its component motor unit potential trains (MUPTs) is presented. The system is intended mainly for clinical applications where several physiological parameters of motor units (MUs), such as their motor unit potential (MUP) templates and mean firing rates, are of interest. The system filters an EMG signal, detects MUPs, and clusters and classifies the detected MUPs into MUPTs. Clustering is partially based on the K-means algorithm, and the supervised classification is implemented using a certainty-based algorithm. Both clustering and supervised classification algorithms use MUP shape and MU firing pattern information along with signal dependent assignment criteria to obtain robust performance across a variety of EMG signals. During classification, the validity of extracted MUPTs are determined using several supervised classifiers; invalid trains are corrected and the assignment threshold for each train is adjusted based on the estimated validity (i.e., adaptive classification). Performance of the developed system in terms of accuracy (A(c)), assignment rate (A(r)), correct classification rate (CC(r)) , and the error in estimating the number of MUPTs represented in the set of detected MUPs (E(NMUPTs)) was evaluated using 32 simulated and 30 real EMG signals comprised of 3-11 and 3-15 MUPTs, respectively. The developed system, with average CC(r) of 86.4% for simulated and 96.4% for real data, outperformed a previously developed EMG decomposition system, with average CC(r) of 71.6% and 89.7% for simulated and real data, by 14.7% and 6.7%, respectively. In terms of E(NMUPTs), the new system, with average E(NMUPTs) of 0.3 and 0.2 for simulated and real data respectively, was better able to estimate the number of MUPTs represented in a set of detected MUPs than the previous system, with average E(NMUPTs) of 2.2 and 0.8 for simulated and real data respectively. For both the simulated and real data used, variations in A(c), A(r), and E(NMUPTs) for the newly developed system were lower than for the previous system, which demonstrates that the new system can successfully adjust the assignment criteria based on the characteristics of a given signal to achieve robust performance across a wide variety of EMG signals, which is of paramount importance for successfully promoting the clinical application of EMG signal decomposition techniques.

A subject-independent method for automatically grading electromyographic features during a fatiguing contraction

Many studies have attempted to monitor fatigue from electromyogram (EMG) signals. However, fatigue affects EMG in a subject-specific manner. We present here a subject-independent framework for monitoring the changes in EMG features that accompany muscle fatigue based on principal component analysis and factor analysis. The proposed framework is based on several time- and frequency-domain features, unlike most of the existing work, which is based on two to three features. Results show that latent factors obtained from factor analysis on these features provide a robust and unified framework. This framework learns a model from EMG signals of multiple subjects, that form a reference group, and monitors the changes in EMG features during a sustained submaximal contraction on a test subject on a scale from zero to one. The framework was tested on EMG signals collected from 12 muscles of eight healthy subjects. The distribution of factor scores of the test subject, when mapped onto the framework was similar for both the subject-specific and subject-independent cases.

Evaluation of muscle fatigue of wheelchair basketball players with spinal cord injury using recurrence quantification analysis of surface EMG

Wheelchair basketball is the most popular exercise activity among individuals with spinal cord injury (SCI). The purpose of this study was to investigate muscular endurance and fatigue in wheelchair basketball athletes with SCI using surface electromyography (SEMG) and maximal torque values. SEMG characteristics of 10 wheelchair basketball players (WBP) were compared to 13 able-bodied basketball players and 12 sedentary able-bodied subjects. Participants performed sustained isometric elbow flexion at 50% maximal voluntary contraction until exhaustion. Elbow flexion torque and SEMG signals were recorded from three elbow flexor muscles: biceps brachii longus, biceps brachii brevis and brachioradialis. SEMG signals were clustered into 0.5-s epochs with 50% overlap. Root mean square (RMS) and median frequency (MDF) of SEMG signals were calculated for each muscle and epoch as traditional fatigue monitoring. Recurrence quantification analysis was used to extract the percentage of determinism (%DET) of SEMG signals. The slope of the %DET for basketball players and WBP showed slower increase with time than the sedentary able-bodied control group for three different elbow flexor muscles, while no difference was observed for the slope of the %DET between basketball and WBP. This result indicated that the athletes are less fatigable during the task effort than the nonathletes. Normalized MDF slope decay exhibited similar results between the groups as %DET, while the slope of the normalized RMS failed to show any significant differences among the groups (p > 0.05). MDF and %DET could be useful for the evaluation of muscle fatigue in wheelchair basketball training. No conclusions about special training for WBP could be determined.

Augmenting the decomposition of EMG signals using supervised feature extraction techniques

Electromyographic (EMG) signal decomposition is the process of resolving an EMG signal into its constituent motor unit potential trains (MUPTs). In this work, the possibility of improving the decomposing results using two supervised feature extraction methods, i.e., Fisher discriminant analysis (FDA) and supervised principal component analysis (SPCA), is explored. Using the MUP labels provided by a decomposition-based quantitative EMG system as a training data for FDA and SPCA, the MUPs are transformed into a new feature space such that the MUPs of a single MU become as close as possible to each other while those created by different MUs become as far as possible. The MUPs are then reclassified using a certainty-based classification algorithm. Evaluation results using 10 simulated EMG signals comprised of 3-11 MUPTs demonstrate that FDA and SPCA on average improve the decomposition accuracy by 6%. The improvement for the most difficult-to-decompose signal is about 12%, which shows the proposed approach is most beneficial in the decomposition of more complex signals.

Optimality versus variability: effect of fatigue in multi-finger redundant tasks

We used two methods to address two aspects of multi-finger synergies and their changes after fatigue of the index finger. Analytical inverse optimization (ANIO) was used to identify cost functions and corresponding spaces of optimal solutions over a broad range of task parameters. Analysis within the uncontrolled manifold (UCM) hypothesis was used to quantify co-variation of finger forces across repetitive trials that helped reduce variability of (stabilized) performance variables produced by all the fingers together. Subjects produced steady-state levels of total force and moment of force simultaneously as accurately as possible by pressing with the four fingers of the right hand. Both before and during fatigue, the subjects performed single trials for many force-moment combinations covering a broad range; the data were used for the ANIO analysis. Multiple trials were performed at two force-moment combinations; these data were used for analysis within the UCM hypothesis. Fatigue was induced by 1-min maximal voluntary contraction exercise by the index finger. Principal component (PC) analysis showed that the first two PCs explained over 90% of the total variance both before and during fatigue. Hence, experimental observations formed a plane in the four-dimensional finger force space both before and during fatigue conditions. Based on this finding, quadratic cost functions with linear terms were estimated from the experimental data. The dihedral angle between the plane of optimal solutions and the plane of experimental observations (D (ANGLE)) was very small (a few degrees); it increased during fatigue. There was an increase in fatigue of the coefficient at the quadratic term for the index finger force balanced by a drop in the coefficients for the ring and middle fingers. Within each finger pair (index-middle and ring-little), the contribution of the "central" fingers to moment production increased during fatigue. An index of antagonist moment production dropped with fatigue. Fatigue led to higher co-variation indices during pronation tasks (index finger is an agonist) but opposite effects during supination tasks. The results suggest that adaptive changes in co-variation indices that help stabilize performance may depend on the role of the fatigued element, agonist or antagonist.

Decorrelation of cortical inputs and motoneuron output

Oscillations in the primary motor cortex are transmitted through the corticospinal tract to the motoneuron pool. This pathway is believed to produce an effective and direct command from the motor cortex to the spinal motoneurons for the modulation of the force output. In this study, we used a computational model of a population of motoneurons to investigate the factors that can influence the transmission of the cortical input to the output of motoneurons, since it can be quantified by coherence analysis. The simulations demonstrated that, despite the nonlinearity of the motoneurons, oscillations present in the cortical input are transmitted to the output of the motoneuron pool at the same frequency. However, the interference introduced by the nonlinearity of the system increases the variability of the oscillations in output, introducing spectral lines whose frequency depends on the input frequencies and the motoneuron discharge rates. Moreover, an additional source of synaptic input common to all motoneurons but independent from the corticospinal component decorrelates the cortical input and motoneuron output and, thus, decreases the magnitude of the estimated coherence, even if the effective cortical drive does not change. These results indicate that the corticospinal input can effectively be sampled by a small population of motoneurons. However, the transmission of a corticospinal drive to the motoneuron pool is influenced by the nonlinearity of the spiking processes of the active motoneurons and by synaptic inputs common to the motoneuron population but independent from the cortical input.

Effects of resistance training on force steadiness and common drive

The purpose of this study was to investigate the influence of an 8-week resistance training program on force steadiness and common drive for the vastus lateralis muscle. Eight untrained men performed a resistance training program. Before the program and at the end of each week, the subjects performed a trapezoid isometric muscle action of the leg extensors, and bipolar surface electromyographic signals were recorded from the vastus lateralis. The signals were decomposed into action potential trains that were cross-correlated to measure common drive. Force steadiness was quantified as the standard deviation of force during the constant-force portion of the trapezoid muscle action. The training program did not consistently affect force steadiness or common drive for any of the subjects. Although future studies are needed with different muscles and training programs, changes in the overall motor control scheme are not likely with resistance training.

Running injury and stride time variability over a prolonged run

Locomotor variability is inherent to movement and, in healthy systems, contains a predictable structure. In this study, detrended fluctuation analysis (DFA) was used to quantify the structure of variability in locomotion. Using DFA, long-range correlations (α) are calculated in over ground running and the influence of injury and fatigue on α is examined. An accelerometer was mounted to the tibia of 18 runners (9 with a history of injury) to quantify stride time. Participants ran at their preferred 5k pace±5% on an indoor track to fatigue. The complete time series data were divided into three consecutive intervals (beginning, middle, and end). Mean, standard deviation (SD), coefficient of variation (CV) and α of stride times were calculated for each interval. Averages for all variables were calculated per group for statistical analysis. No significant interval, group or interval×group effects were found for mean, SD or CV of stride time. A significant linear trend in α for interval occurred with a reduction in α over the course of the run (p=0.01) indicating that over the run, stride times of runners became more unpredictable. This was likely due to movement errors associated with fatigue necessitating frequent corrections. The injured group exhibited lower α (M=0.79, CI(95)=0.70, 0.88) than the non-injured group (p=0.01) (M=0.96, CI(95)=0.88, 1.05); a reduction hypothesized to be associated with altered complexity. Overall, these findings suggest injury and fatigue influence neuromuscular output during running.

Hierarchical domain adaptation for SEMG signal classification across multiple subjects

Large variations in Surface Electromyogram (SEMG) signal across different subjects make the process of automated signal classification as a generalized tool, challenging. In this paper, we propose a domain adaptation methodology that addresses this challenge. In particular we propose a hierarchical sample selection methodology, that selects samples from multiple training subjects, based on their similarity with the target subject at different levels of granularity. We have validated our framework on SEMG data collected from 8 people during a fatiguing exercise. Comprehensive experiments conducted in the paper demonstrate that the proposed method improves the subject independent classification accuracy by 21% to 23% over the cases without domain adaptation methods and by 14% to 20% over the existing state-of-the-art domain adaptation methods.

A model of motoneuron behavior and muscle-force generation for sustained isometric contractions

A model for the simulation of motoneuron firing behavior and muscle force during sustained constant-force isometric contractions was developed. It provides a non-linear relationship between the excitation to the motoneuron pool of a muscle and the firing behavior of motor units; it implements muscle mechanical changes induced by fatigue and it comprises a feedback loop to maintain the muscle force at a given target level. We simulated a series of repeated force contractions sustained at 20% MVC with the first dorsal interosseous muscle of the hand and the vastus lateralis muscle of the thigh. The model generates force and firing behaviors which are consistent with experimental findings and underscores the influence of muscle mechanical changes on the control behavior of motor units during sustained contractions. The model predicts the increase of force fluctuation with fatigue in both muscles, likely due to recruitment of high-threshold high-amplitude twitch motor units. Force variability is greater in the first dorsal interosseous muscle than in the vastus lateralis muscle at any time during the contraction series, due to the different electrical and mechanical properties of the muscles.

Common synaptic input to the human hypoglossal motor nucleus

The tongue plays a key role in various volitional and automatic functions such as swallowing, maintenance of airway patency, and speech. Precisely how hypoglossal motor neurons, which control the tongue, receive and process their often concurrent input drives is a subject of ongoing research. We investigated common synaptic input to the hypoglossal motor nucleus by measuring the coordination of spike timing, firing rate, and oscillatory activity across motor units recorded from unilateral (i.e., within a belly) or bilateral (i.e., across both bellies) locations within the genioglossus (GG), the primary protruder muscle of the tongue. Simultaneously recorded pairs of motor units were obtained from 14 healthy adult volunteers using tungsten microelectrodes inserted percutaneously into the GG while the subjects were engaged in volitional tongue protrusion or rest breathing. Bilateral motor unit pairs showed concurrent low frequency alterations in firing rate (common drive) with no significant difference between tasks. Unilateral motor unit pairs showed significantly stronger common drive in the protrusion task compared with rest breathing, as well as higher indices of synchronous spiking (short-term synchrony). Common oscillatory input was assessed using coherence analysis and was observed in all conditions for frequencies up to ∼ 5 Hz. Coherence at frequencies up to ∼ 10 Hz was strongest in motor unit pairs recorded from the same GG belly in tongue protrusion. Taken together, our results suggest that cortical drive increases motor unit coordination within but not across GG bellies, while input drive during rest breathing is distributed uniformly to both bellies of the muscle.

Effect of fatigue on force fluctuations in knee extensors in young adults

This study investigated the hypothesis that fatiguing exercises led to increased force fluctuations during submaximal isometric knee extensions and to decreased accuracy and steadiness in the time and frequency domains. Sixteen young adults (eight males, eight females) were tested, in a seated posture with 90 degrees knee flexion, to assess their ability to reproduce target extensor torques set at 15 per cent and 20 per cent of their maximum voluntary isometric contraction, both before and after fatiguing exercises. Normalized mean (NMAE) and peak (NPAE) of the absolute error were both used to quantify accuracy, whereas normalized standard deviation of the absolute error (NSAE) was used to quantify steadiness of the torque trials in the time domain. Mean and median power frequencies (MnPF, MdPF) and normalized peak power (NPkP) were used to assess the spectral structure of the torque signals. NMAE, NSAE and NPAE all showed excellent intra- as well as intersession reliabilities (intraclass correlation values greater than 0.75 and low standard error of measurement values), demonstrating repeatability of the test set-up. NMAE, NSAE and NPAE increased significantly post-fatigue (greater than 42%), together with a shift towards higher frequency (MnPF and MdPF) components, indicating that the set-up was sensitive enough to detect the decreased force accuracy and steadiness of the musculature after fatigue. Increased force variability in both the time and frequency domains could therefore explain decreased steadiness after fatigue.

High-yield decomposition of surface EMG signals

OBJECTIVE

Automatic decomposition of surface electromyographic (sEMG) signals into their constituent motor unit action potential trains (MUAPTs).

METHODS

A small five-pin sensor provides four channels of sEMG signals that are in turn processed by an enhanced artificial intelligence algorithm evolved from a previous proof-of-principle. We tested the technology on sEMG signals from five muscles contracting isometrically at force levels ranging up to 100% of their maximal level, including those that were covered with more than 1.5cm of adipose tissue. Decomposition accuracy was measured by a new method wherein a signal is first decomposed and then reconstructed and the accuracy is measured by comparison. Results were confirmed by the more established two-source method.

RESULTS

The number of MUAPTs decomposed varied among muscles and force levels and mostly ranged from 20 to 30, and occasionally up to 40. The accuracy of all the firings of the MUAPTs was on average 92.5%, at times reaching 97%.

CONCLUSIONS

Reported technology can reliably perform high-yield decomposition of sEMG signals for isometric contractions up to maximal force levels.

SIGNIFICANCE

The small sensor size and the high yield and accuracy of the decomposition should render this technology useful for motor control studies and clinical investigations.

Fatigue and motor redundancy: adaptive increase in finger force variance in multi-finger tasks

We studied the effects of fatigue of the index finger on indices of force variability in discrete and rhythmic accurate force production tasks performed by the index finger and by all four fingers pressing in parallel. An increase in the variance of the force produced by the fatigued index finger was expected. We hypothesized that the other fingers would also show increased variance of their forces, which would be accompanied by co-variation among the finger forces resulting in relatively preserved accuracy of performance. The subjects performed isometric tasks including maximal voluntary contraction (MVC) and accurate force production before and after a 1-min MVC fatiguing exercise by the index finger. During fatigue, there was a significant increase in the root mean square index of force variability during accurate force production by the index finger. In the four-finger tasks, the variance of the individual finger force increased for all four fingers, while the total force variance showed only a modest change. We quantified two components of variance in the space of hypothetical commands to fingers, finger modes. There was a large increase in the variance component that did not affect total force and a much smaller increase in the component that did. The results suggest an adaptive increase in force variance by nonfatigued elements as a strategy to attenuate effects of fatigue on accuracy of multi-element performance. These effects were unlikely to originate at the level of synchronization of motor units across muscle compartments but rather involved higher control levels.

Fatigue related changes in electromyographic coherence between synergistic hand muscles

The aim of this study was to examine coherence between surface electromyographic (EMG) signals from two index finger flexor muscles, the first dorsal interosseous (FDI) and flexor digitorum superficialis (FDS), during and immediately following sustained, fatiguing isometric contraction. Coherence was observed between the FDI and FDS EMG signals in the tremor (8-12 Hz), beta (15-35 Hz) and gamma (35-60 Hz) bands in all subjects. A significant increase in EMG-EMG coherence in the beta and gamma frequency bands was observed immediately following the fatiguing contraction. No significant difference was observed in the tremor band coherence before and after fatigue. Coherence was observed between EMG and force in the tremor band during both the pre- and post-fatigue contractions and a significant increase in the FDI EMG-force coherence post-fatigue was observed. It is suggested that the increase in beta and gamma band coherence with fatigue may be due to increased levels of corticomotoneuronal drive to both muscles. Alternatively, the increased EMG-EMG coherence may reflect an increased contribution of peripheral afferents to coupling across the muscle with fatigue. Although the functional significance is not clear, the increase in coherence may help to overcome reduced motoneuron excitability with fatigue, to bind together different sensorimotor elements or to coordinate force generation across muscles in a more synergistic manner as the force generating capacity of the muscle is decreased.