Number Of Active Motor Units Research Articles

How many motor units is enough? An assessment of the influence of the number of motor units on firing rate calculations

The number of motor units included in calculations of mean firing rates varies widely in the literature. It is unknown how the number of decomposed motor units included in the calculation of firing rate per participant compares to the total number of active motor units in the muscle, and if this is different for males and females. Bootstrapped distributions and confidence intervals (CI) of mean motor unit firing rates decomposed from the tibialis anterior were used to represent the total number of active motor units for individual participants in trials from 20 to 100 % of maximal voluntary contraction. Bootstrapped distributions of mean firing rates were constructed using different numbers of motor units, from one to the maximum number for each participant, and compared to the CIs. A probability measure for each number of motor units involved in firing rate was calculated and then averaged across all individuals. Motor unit numbers required for similar levels of probability increased as contraction intensity increased (p < 0.001). Increased levels of probability also required higher numbers of motor units (p < 0.001). There was no effect of sex (p ≥ 0.97) for any comparison. This methodology should be repeated in other muscles, and aged populations.

Detection of Steps and Rotation in the Gliding Motility of Mycoplasma mobile.

Mycoplasma mobile is one of the fastest gliding bacteria, gliding with a speed of 4.5μms-1. This gliding motility is driven by a concerted movement of 450 supramolecular motor units composed of three proteins, Gli123, Gli349, and Gli521, in the gliding motility machinery. With general experimental setups, it is difficult to obtain the information on how each motor unit works. This chapter describes strategies to decrease the number of active motor units to extract stepwise cell movements driven by a minimum number of motor units. We also describe an unforeseen motility mode in which the leg motions convert the gliding motion into rotary motion, which enables us to characterize the motor torque and energy-conversion efficiency by adding some more assumptions.

Detecting anatomical characteristics of single motor units by combining high density electromyography and ultrafast ultrasound: a simulation study.

Muscle force production is the result of a sequence of electromechanical events that translate the neural drive issued to the motor units (MUs) into tensile forces on the tendon. Current technology allows this phenomenon to be investigated non-invasively. Single MU excitation and its mechanical response can be studied through high-density surface electromyography (HDsEMG) and ultrafast ultrasound (US) imaging respectively. In this study, we propose a method to integrate these two techniques to identify anatomical characteristics of single MUs. Specifically, we tested two algorithms, combining the tissue velocity sequence (TVS, obtained from ultrafast US images), and the MU firings (extracted from HDsEMG decomposition). The first is the Spike Triggered Averaging (STA) of the TVS based on the occurrences of individual MU firings, while the second relies on the correlation between the MU firing patterns and the TVS spatio-temporal independent components (STICA). A simulation model of the muscle contraction was adapted to test the algorithms at different degrees of neural excitation (number of active MUs) and MU synchronization. The performances of the two algorithms were quantified through the comparison between the simulated and the estimated characteristics of MU territories (size, location). Results show that both approaches are negatively affected by the number of active MU and synchronization levels. However, STICA provides a more robust MU territory estimation, outperforming STA in all the tested conditions. Our results suggest that spatio-temporal independent component decomposition of TVS is a suitable approach for anatomical and mechanical characterization of single MUs using a combined HDsEMG and ultrafast US approach.

Changes in neural drive to calf muscles during steady submaximal contractions after repeated static stretches

Repeated static-stretching interventions consistently increase the range of motion about a joint and decrease total joint stiffness, but findings on the changes in muscle and connective-tissue properties are mixed. The influence of these stretch-induced changes on muscle function at submaximal forces is unknown. To address this gap in knowledge, the changes in neural drive to the plantar flexor muscles after a static-stretch intervention were estimated. Neural drive to the plantar flexor muscles during a low-force contraction increased after repeated static stretches. These findings suggest that adjustments in motor unit activity are necessary at low forces to accommodate reductions in the force-generating and transmission capabilities of the muscle-tendon unit after repeated static stretches of the calf muscles. Static stretching decreases stiffness about a joint, but its influence on muscle-tendon unit function and muscle activation is unclear. We investigated the influence of three static stretches on changes in neural drive to the plantar flexor muscles, both after a stretch intervention and after a set of maximal voluntary contractions (MVCs). Estimates of neural drive were obtained during submaximal isometric contractions by decomposing high-density electromyographic signals into the activity of individual motor units from medial gastrocnemius, lateral gastrocnemius and soleus. Motor units were matched across contractions and an estimate of neural drive to the plantar flexors was calculated by normalizing the cumulative spike train to the number of active motor units (normalized neural drive). Mean discharge rate increased after the stretch intervention during the 10% MVC task for all recorded motor units and those matched across conditions (all, P=0.0046; matched only, P=0.002), recruitment threshold decreased for motor units matched across contractions (P=0.022), and discharge rate at recruitment was elevated (P=0.004). Similarly, the estimate of normalized neural drive was significantly greater after the stretch intervention at 10% MVC torque (P=0.029), but not at 35% MVC torque. The adjustments in motor unit activity required to complete the 10% MVC task after stretch may have been partially attenuated by a set of plantar flexor MVCs. The increase in neural drive required to produce low plantar-flexion torques after repeated static stretches of the calf muscles suggests stretch-induced changes in muscle and connective tissue properties.

Recursive Decomposition of Electromyographic Signals With a Varying Number of Active Sources: Bayesian Modeling and Filtering.

This paper describes a sequential decomposition algorithm for single-channel intramuscular electromyography (iEMG) generated by a varying number of active motor neurons. As in previous work, we establish a hidden Markov model of iEMG, in which each motor neuron spike train is modeled as a renewal process with inter-spike intervals following a discrete Weibull law and motor unit action potentials are modeled as impulse responses of linear time-invariant systems with known prior. We then expand this model by introducing an activation vector associated with the state vector of the hidden Markov model. This activation vector represents recruitment/derecruitment of motor units and is estimated together with the state vector using Bayesian filtering. Non-stationarity of the model parameters is addressed by means of a sliding window approach, thus making the algorithm adaptive to variations in contraction force and motor unit action potential waveforms. The algorithm was validated using simulated and experimental iEMG signals with varying number of active motor units. The experimental signals were acquired from the tibialis anterior and abductor digiti minimi muscles by fine wire and needle electrodes. The decomposition accuracy in both simulated and experimental signals exceeded 90%. The recruitment/derecruitment was successfully tracked by the algorithm. Because of its parallel structure, this algorithm can be efficiently accelerated, which lays the basis for its real-time applications in human-machine interfaces. The proposed method substantially broadens the domains of applicability of the algorithm.

A model computation of how synchronization and clustering of motor unit action potentials alter the power spectra of electromyograms

Abstract Introduction The duration of bursts of muscle activity e.g. while running or walking, is too short for long pulse trains of motor unit action potentials (MUAPs) to develop. A pool of motor units is likely activated simultaneously which generates clustered MUAPs. The hypothesis is that the EMG power spectra are modulated by the fact that MUAPs cluster. The purpose is to quantify this modulation analytically. Methods A model of an EMG signal is presented that includes clustered MUAPs. Results According to the model the influence of MUAPs clustering is shown to be largest at lower frequencies and increases when the width of the time window containing the clusters decreases. Discussion The power at frequencies below 60 Hz strongly reflects changes of the degree of clustering. The mean frequency of the EMG therefore decreases when MUAPs cluster more tightly. Thus, clustering of MUAPs competes with other physiological properties that influence the mean frequency. The EMG power is proportional to the number of active MUAPs at high frequencies but approaches a value proportional to the square of the number of active MUAPs at very low frequencies. To obtain a measure of amplitude that is proportional to the number of active motor units, one should focus on the higher frequency power components only, however, to monitor the effect of clustering of MUAP one should focus on the lower frequency power. That could become relevant for comparing pre- and post-operative clinical gait studies where changes in MUAPs clustering may play a significant role.

The effects of local forearm muscle cooling on motor unit properties.

Muscle cooling impairs maximal force. Using needle electromyography (EMG) to assess motor unit properties during muscle cooling, is limited and equivocal. Therefore, we aimed to determine the impact of local muscle cooling on motor unit firing properties using surface EMG decomposition. Twenty participants (12M, 8F) completed maximal, evoked, and trapezoidal contractions during thermoneutral and cold muscle conditions. Forearm muscle temperature was manipulated using 10-min neutral (~ 32°C) or 20-min cold (~ 3°C) water baths. Twitches and maximal voluntary contractions were performed prior to, and after, forearm immersion in neutral or cold water. Motor unit properties were assessed during trapezoidal contractions to 50% baseline force using surface EMG decomposition. Impaired contractile properties from muscle cooling were evident in the twitch amplitude, duration, and rate of force development indicating that the muscle was successfully cooled from the cold water bath (all d ≥ 0.5, P < 0.05). Surface EMG decomposition showed muscle cooling increased the number of motor units (d = 0.7, P = 0.01) and motor unit action potential (MUAP) duration (d = 0.6, P < 0.001), but decreased MUAP amplitude (d = 0.2, P = 0.012). Individually, neither motor unit firing rates (d = 0.1, P = 0.843) nor recruitment threshold (d = 0.1, P = 0.746) changed; however, the relationship between the recruitment threshold and motor unit firing rate was steeper (d = 1.0, P < 0.001) and had an increased y-intercept (d = 0.9, P = 0.007) with muscle cooling. Since muscle contractility is impaired with muscle cooling, these findings suggest a compensatory increase in the number of active motor units, and small but coupled changes in motor unit firing rates and recruitment threshold to produce the same force.

Robust estimation of average twitch contraction forces of populations of motor units in humans

The characteristics of motor unit force twitch profiles provide important information for the understanding of the muscle force generation. The twitch force is commonly estimated with the spike-triggered averaging technique, which, despite the many limitations, has been important for clarifying central issues in force generation. In this study, we propose a new technique for the estimation of the average twitch profile of populations of motor units with uniform contractile properties. The method encompasses a model-based deconvolution of the force signal using the identified discharge times of a population of motor units. The proposed technique was validated using simulations and tested on signals recorded during voluntary activation. The results of the simulations showed that the proposed method provides accurate estimates (relative error <25%) of the main parameters of the average twitch force when the number of identified motor units is between 5% and 15% of the total number of active motor units. It is discussed that current detection and decomposition methods of multi-channel surface EMG signals allow decoding this relative sample of the active motor unit pool. However, even when this condition is not met, our results show that the estimates provided by the new method are anyway always superior to those obtained by the spike triggered average approach, especially for high motor unit synchronization levels and when a relatively small number of triggers is available. In conclusion, we present a new method that overcome the main limitations of the spike-triggered average for the study of contractile properties of individual motor units. The method provides a new reliable tool for the investigation of the determinants of muscle force.

The Etiology of Muscle Fatigue Differs between Two Electrical Stimulation Protocols.

This study aimed at investigating the mechanisms involved in the force reduction induced by two electrical stimulation (ES) protocols that were designed to activate motor units differently. The triceps surae of 11 healthy subjects (8 men; age, ~28 yr) was activated using ES applied over the tibial nerve. Two ES protocols (conventional [CONV]: 20 Hz, 0.05 ms vs wide-pulse high-frequency [WPHF]: 80 Hz, 1 ms) were performed and involved 40 trains (6 s on-6 s off) delivered at an intensity (IES) evoking 20% of maximal voluntary contraction. To analyze the mechanical properties of the motor units activated at IES, force-frequency relation was evoked before and after each protocol. H-reflex and M-wave responses evoked by the last stimulation pulse were also assessed during each ES protocol. Electromyographic responses (∑EMG) were recorded after each train to analyze the behavior of the motor units activated at IES. Metabolic variables, including relative concentrations of phosphocreatine and inorganic phosphate as well as intracellular pH, were assessed using P-MR spectroscopy during each protocol. Larger H-reflex amplitudes were observed during WPHF as compared with CONV, whereas opposite findings were observed for M-wave amplitudes. Despite this difference, both the force reduction (-26%) and metabolic changes were similar between the two protocols. The CONV protocol induced a rightward shift of the force-frequency relation, whereas a significant reduction of the ∑EMG evoked at IES was observed only for the WPHF. These results suggest that a decreased number of active motor units mainly contributed to WPHF-induced force decrease, whereas intracellular processes were most likely involved in the force reduction occurring during CONV stimulation.

Biomechanical benefits of the onion-skin motor unit control scheme

Muscle force is modulated by varying the number of active motor units and their firing rates. For the past five decades, the notion that the magnitude of the firing rates is directly related to motor unit size and recruitment threshold has been widely accepted. This construct, here named the After-hyperpolarization scheme evolved from observations in electrically stimulated cat motoneurons and from reported observations in voluntary contractions in humans. It supports the assumption that the firing rates of motor units match their mechanical properties to “optimize” force production, so that the firing rate range corresponds to that required for force-twitch fusion (tetanization) and effective graduation of muscle force. In contrast, we have shown that, at any time and force during isometric voluntary constant-force contractions in humans, the relationship between firing rate and recruitment threshold is inversely related. We refer to this construct as the Onion-Skin scheme because earlier-recruited motor units always have greater firing rates than latter-recruited ones. By applying a novel mathematical model that calculates the force produced by a muscle for the two schemes we found that the Onion-Skin scheme is more energy efficient, provides smoother muscle force at low to moderate force levels, and appears to be more conducive to evolutionary survival than the After-hyperpolarization scheme.

Identification of common synaptic inputs to motor neurons from the rectified electromyogram

Oscillatory common inputs of cortical or peripheral origin can be identified from the motor neuron output with coherence analysis. Linear transmission is possible despite the motor neuron non-linearity because the same input is sent commonly to several neurons. Because of the linear transmission, common input components to motor neurons can be investigated from the surface EMG, for example by EEG-EMG or EMG-EMG coherence. In these studies, there is an open debate on the utility and appropriateness of EMG rectification. The present study addresses this issue using an analytical, simulation and experimental approach. The main novel theoretical contribution that we report is that the spectra of both the rectified and the raw EMG contain input spectral components to motor neurons. However, they differ by the contribution of amplitude cancellation which influences the rectified EMG spectrum when extracting common oscillatory inputs. Therefore, the degree of amplitude cancellation has an impact on the effectiveness of EMG rectification in extracting input spectral peaks. The theoretical predictions were exactly confirmed by realistic simulations of a pool of motor neurons innervating a muscle in a cylindrical volume conductor of EMG generation and by experiments conducted on the first dorsal interosseous and the abductor pollicis brevis muscles of seven healthy subjects during pinching. It was concluded that when the contraction level is relatively low, EMG rectification may be preferable for identifying common inputs to motor neurons, especially when the energy of the action potentials in the low frequency range is low. Nonetheless, different levels of cancellation across conditions influence the relative estimates of the degree of linear transmission of oscillatory inputs to motor neurons when using the rectified EMG.

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.

A simulation study on the relation between muscle motor unit numbers and the non-Gaussianity/non-linearity levels of surface electromyography

Recent research has demonstrated that surface electromyography (sEMG) signals have non-Gaussianity and non-linearity properties. It is known that more muscle motor units are recruited and firing rates (FRs) increase as exertion increases. A hypothesis was proposed that the Gaussianity test (S (g)) and linearity test (S (ℓ)) levels of sEMG signals are associated with the number of active motor units (nMUs) and the FR. The hypothesis has only been preliminarily discussed in experimental studies. We used a simulation sEMG model involving spatial (active MUs) and temporal (three FRs) information to test the hypothesis. Higher-order statistics (HOS) from the bi-frequency domain were used to perform S (g) and S (ℓ). Multivariate covariance analysis and a correlation test were employed to determine the nMUs-S (g) relationship and the nMUs-S (ℓ) relationship. Results showed that nMUs, the FR, and the interaction of nMUs and the FR all influenced the S (g) and S (ℓ) values. The nMUs negatively correlated to both the S (g) and S (ℓ) values. That is, at the three FRs, sEMG signals tended to a more Gaussian and linear distribution as exertion and nMUs increased. The study limited experiment factors to the sEMG non-Gaussianity and non-linearity levels. The study quantitatively described nMUs and the FR of muscle that are not directly available from experiments. Our finding has guiding significance for muscle capability assessment and prosthetic control.

Recruitment of motor units in the medial gastrocnemius muscle during human quiet standing: is recruitment intermittent? What triggers recruitment?

The recruitment and the rate of discharge of motor units are determinants of muscle force. Within a motoneuron pool, recruitment and rate coding of individual motor units might be controlled independently, depending on the circumstances. In this study, we tested whether, during human quiet standing, the force of the medial gastrocnemius (MG) muscle is predominantly controlled by recruitment or rate coding. If MG control during standing was mainly due to recruitment, then we further asked what the trigger mechanism is. Is it determined internally, or is it related to body kinematics? While seven healthy subjects stood quietly, intramuscular electromyograms were recorded from the MG muscle with three pairs of wire electrodes. The number of active motor units and their mean discharge rate were compared for different sway velocities and positions. Motor unit discharges occurred more frequently when the body swayed faster and forward (Pearson R = 0.63; P < 0.0001). This higher likelihood of observing motor unit potentials was explained chiefly by the recruitment of additional units. During forward body shifts, the median number of units detected increased from 3 to 11 (P < 0.0001), whereas the discharge rate changed from 8 ± 1.1 (mean ± SD) to 10 ± 0.9 pulses/s (P = 0.001). Strikingly, motor units did not discharge continuously throughout standing. They were recruited within individual, forward sways and intermittently, with a modal rate of two recruitments per second. This modal rate is consistent with previous circumstantial evidence relating the control of standing to an intrinsic, higher level planning process.

Neuromuscular control of wingbeat kinematics in Anna's hummingbirds (Calypte anna)

Hummingbirds can maintain the highest wingbeat frequencies of any flying vertebrate - a feat accomplished by the large pectoral muscles that power the wing strokes. An unusual feature of these muscles is that they are activated by one or a few spikes per cycle as revealed by electromyogram recordings (EMGs). The relatively simple nature of this activation pattern provides an opportunity to understand how motor units are recruited to modulate limb kinematics. Hummingbirds made to fly in low-density air responded by moderately increasing wingbeat frequency and substantially increasing the wing stroke amplitude as compared with flight in normal air. There was little change in the number of spikes per EMG burst in the pectoralis major muscle between flight in normal and low-density heliox (mean=1.4 spikes cycle(-1)). However the spike amplitude, which we take to be an indication of the number of active motor units, increased in concert with the wing stroke amplitude, 1.7 times the value in air. We also challenged the hummingbirds using transient load lifting to elicit maximum burst performance. During maximum load lifting, both wing stroke amplitude and wingbeat frequency increased substantially above those values during hovering flight. The number of spikes per EMG burst increased to a mean of 3.3 per cycle, and the maximum spike amplitude increased to approximately 1.6 times those values during flight in heliox. These results suggest that hummingbirds recruit additional motor units (spatial recruitment) to regulate wing stroke amplitude but that temporal recruitment is also required to maintain maximum stroke amplitude at the highest wingbeat frequencies.

Interpretation of EMG integral or RMS and estimates of “neuromuscular efficiency” can be misleading in fatiguing contraction

In occupational and sports physiology, reduction of neuromuscular efficiency (NME) and elevation of amplitude characteristics, such as root mean square (RMS) or integral of surface electromyographic (EMG) signals detected during fatiguing submaximal contraction are often related to changes in neural drive. However, there is data showing changes in the EMG integral ( I EMG) and RMS due to peripheral factors. Causes for these changes are not fully understood. On the basis of computer simulation, we demonstrate that lengthening of intracellular action potential (IAP) profile typical for fatiguing contraction could affect EMG amplitude characteristics stronger than alteration in neural drive (central factors) defined by number of active motor units (MUs) and their firing rates. Thus, relation of these EMG amplitude characteristics only to central mechanisms can be misleading. It was also found that to discriminate between changes in RMS or I EMG due to alterations in neural drive from changes due to alterations in peripheral factors it is better to normalize RMS of EMG signals to the RMS of M-wave. In massive muscles, such normalization is more appropriate than normalization to either peak-to-peak amplitude or area of M-wave proposed in literature.

Mechanomyographic and Electromyographic Responses During Submaximal to Maximal Eccentric Isokinetic Muscle Actions of the Biceps Brachii

The purpose of this investigation was to determine the mechanomyography (MMG) and electromyography (EMG) amplitude and mean power frequency (MPF) vs. eccentric isokinetic torque relationships for the biceps brachii muscle. Nine adults (mean +/- SD age = 23.1 +/- 2.9 years) performed submaximal to maximal eccentric isokinetic muscle actions of the dominant forearm flexors. After determination of isokinetic peak torque (PT), the subjects randomly performed submaximal step muscle actions in 10% increments from 10 to 90% PT. Polynomial regression analyses indicated that the MMG amplitude vs. eccentric isokinetic torque relationship was best fit with a quadratic model (R(2) = 0.951), where MMG amplitude increased from 10 to 60% PT and then plateaued from 60 to 100% PT. There were linear increases in MMG MPF (r(2) = 0.751) and EMG amplitude (r(2) = 0.988) with increases in eccentric isokinetic torque, but there was no significant change in EMG MPF from 10 to 100% PT. The results suggested that for the biceps brachii, eccentric isokinetic torque was increased to approximately 60% PT through concurrent modulation of the number of active motor units and their firing rates, whereas additional torque above 60% PT was produced only by increases in firing rates. These findings contribute to current knowledge of motor-control strategies during eccentric isokinetic muscle actions and could be useful in the design of training programs.

Influence of motor unit properties on the size of the simulated evoked surface EMG potential

The purpose of the study was to quantify the influence of selected motor unit properties on the simulated amplitude and area of evoked muscle potentials detected at the skin surface. The study was restricted to a motor unit population simulating a hand muscle whose potentials were recorded on the skin over the muscle. Peak-to-peak amplitude and area of the evoked potential were calculated from the summed motor unit potentials and compared across conditions that simulated variation in different motor unit properties. The simulations involved varying the number of activated motor units, muscle fiber conduction velocities, axonal conduction velocities, neuronal activation times, the shape of the intracellular action potential, and recording configurations commonly used over hand muscles. The results obtained for the default condition simulated in this study indicated that ~7% of the motor unit potentials were responsible for 50% of the size of the evoked potential. Variation in the amplitude and area of the evoked muscle potential was directly related to the number of active motor units only when the stimulus activated motor units randomly, and not when activation was based on a parameter such as motor unit size. Independent adjustments in motor unit properties had variable effects on the size of the evoked muscle potential, including when the stimulus activated only a subpopulation of motor units. These results provide reference information that can be used to assist in the interpretation of experimentally observed changes in the size of evoked muscle potentials.

Reinnervation of motor units in intrinsic muscles of a transplanted hand

Functional recovery of transplanted hand can be evaluated clinically but until now there has been no direct assessment of muscle control. In October 2000 we transplanted the right hand of a brain-dead man aged 43 onto a man aged 35 who had lost his right dominant hand 22 years before. Starting from day 205 after the transplant, multi-channel surface electromyographic (EMG) signals were recorded from intrinsic muscles of the transplanted hand in order to assess their degree of reinnervation. Eleven months post-operatively, the first motor unit action potential train was detected from the abductor digiti minimi. One month later, also the abductor pollicis brevis and the opponens pollicis muscles showed motor unit activity, while, after 15 and 24 months, the first dorsal interosseous and the first lumbricalis muscles, respectively, showed activation of their first motor units. An increase in the number of active motor units was observed after the first signs of reinnervation, although the process was rather slow. In sustained maximal contractions, the motor unit discharge rate decreased from (mean ± S.D.) 34.0 ± 6.7 pps to 23.4 ± 5.1 pps in 60 s for the abductor digiti minimi, although the subject was verbally encouraged to maintain a maximal activation. Moreover, the subject was able to perform basic control tasks involving voluntary modulation of motor unit discharge rate. With a visual feedback, he could increase discharge rate of the abductor digiti minimi approximately linearly over time, from 13.4 ± 6.7 pps to 32.5 ± 11.2 pps in 60 s. In conclusion, we showed reinnervation of single motor units in a transplanted hand after 22 years of denervation. Moreover, voluntary modulation of discharge rates of these motor units could be performed since the first sign of reinnervation.

Power Spectrum Analysis

In the analysis of EMG signal during dynamic movement, we have proposed an estimation algorithm for the time varying parameters. The parameters correspond to less biased time varying reflection coefficients. We determine the less biased estimation using a locally quasi-stationary model and name these parameters “K-parameters”. We estimated K-parametes upto the fifth order for the surface EMG signals of masseter muscle during rapid open-close movement of the lower jaw, a ballistics contraction, and fatigue. According to the results, the time causes of the K- parameters displayed remarkable properties. In order to study the behaviour of K-parameters physiologically, we produce a muscle-structured stimulation model based on anatomical and physiological data. The stimulation results suggested that the behaviour of the third parameter is related to the number of active motor units (MU's) at the shallow layer of a muscle.