Motor Unit Template Estimation Using Integral Shape Averaging.

In this study, we investigated the effects of the motor unit (MU) location and size and the fibres pennation on the ability of anisotropic and almost isotropic spatial filters used to detect surface electromyographic (EMG) signals to make a distinction between motor unit action potentials (MUAPs) generated from two MUs. The study was based on simulated MUAPs. The fibres orientation was performed by varying the fibres pennation angle (FPA).The root mean square error (RMSE) between MUAPs generated from two MUs was used as a criterion to evaluate the ability of the investigated filters to distinguish between two generated MUAPs. The location of a MU was fixed and the second MU moved away from the first MU in the transversal direction for the first case and in the depth direction in the second case to take five different locations in every case.We showed that the capability of the studied filters to more separate two MUAPs strongly depended on MU location, MU size and FPA. This capability of separation was best with large distances between the two MUs and with large sizes of them. Furthermore, the main survey of this work was that the BiTDD filter has the best ability of separation of two MUAPs than the other filters in a given FPA interval. The number of pennation angles in this interval is related to the location and size of the moved MU.

The theoretical field of a motor unit (MU) action potential (MUP) was considered. It has been proved that in normal muscles the shape of a smooth threephasic MUP curve is determined mostly by the spatial distribution of MU muscle fibres. Phenomena called "time dispersion" are of prime importance in pathology, where they complicate normal threephasic MUP. Amplitudes and time parameters of model threephasic MUP were analyzed as a function of the radial distance R from the geometrical centre of the motor unit territory (MUT) and approximated by mathematical expressions. It appeared that analysis of radial variability of MUP curve allows conclusions to be made about the MUT size and the spatial distribution of MU muscle fibres. These anatomical features of a MU are often changed in pathological muscles, thus the proposed methods of their evaluation could be helpful in diagnosis of neuromuscular diseases.

The duration of action potentials of motor units (MU) of the gastrocnemius and tibialis muscles was studied in patients with spinal cord trauma by the method of local electromyography. The duration of action potentials of gastrocnemius MU was found to be reduced on average by 27%, and of tibialis MU by 38% of the age norm. The degree of shortening of the action potentials of the gastrocnemius and tibialis MU was not directly dependent on the level of spinal cord injury, the length of time after trauma, or the severity of the spastic syndrome. Changes in the duration of action potentials of MU are evidently due to differences in the degree of atrophy developing as a result of prolonged adynamia.

The neuromuscular strategies employed to compensate for fatigue-induced muscle force deficits are not clearly understood. This study utilizes surface electromyography (sEMG) together with recordings of a population of individual motor unit action potentials (MUAPs) to investigate potential compensatory alterations in motor unit (MU) behavior immediately following a sustained fatiguing contraction and after a recovery period. EMG activity was recorded during abduction of the first dorsal interosseous in 12 subjects at 20% maximum voluntary contraction (MVC), before and directly after a 30% MVC fatiguing contraction to task failure, with additional 20% MVC contractions following a 10-min rest. The amplitude, duration and mean firing rate (MFR) of MUAPs extracted with a sEMG decomposition system were analyzed, together with sEMG root-mean-square (RMS) amplitude and median frequency (MPF). MUAP duration and amplitude increased immediately postfatigue and were correlated with changes to sEMG MPF and RMS, respectively. After 10 min, MUAP duration and sEMG MPF recovered to prefatigue values but MUAP amplitude and sEMG RMS remained elevated. MU MFR and recruitment thresholds decreased postfatigue and recovered following rest. The increase in MUAP and sEMG amplitude likely reflects recruitment of larger MUs, while recruitment compression is an additional compensatory strategy directly postfatigue. Recovery of MU MFR in parallel with MUAP duration suggests a possible role for metabolically sensitive afferents in MFR depression postfatigue. This study provides insight into fatigue-induced neuromuscular changes by examining the properties of a large population of concurrently recorded single MUs and outlines possible compensatory strategies involving alterations in MU recruitment and MFR.

The purpose of this study was to develop an algorithm for surface electromyogram (SEMG) decomposition and classification of surface motor unit (MU) action potential (MUAP) detected during isovelocity elbow flexion. In our proposed algorithm, firstly the measured SEMG was extracted for 3 seconds by every 1.5 seconds. SEMG was decomposed with Independent Component Analysis (ICA) technique, and classified with template matching. Finally, the MUAP trains were identified under the firing time of the MUAPs classified in each extracted period. The SEMG was measured from the biceps short head muscle during voluntary elbow flexion of 0 to 90 degrees at constant velocity 9 degree/s against a constant load torque of 10%MVC and the MUAPs were classified with our proposed algorithm. As a result, calculated MUs firing rates were almost same as the results in the previous studies. It was shown that the proposed algorithm was useful for decomposing SEMG detected during flexion movements.

The ability to maintain an absolute, submaximal torque level during fatiguing contractions is controlled, in part, by the recruitment of larger motor units. These motor units are commonly identified based on greater action potential peak-to-peak amplitude values. It is unclear, however, if motor unit action potential (MUAP) amplitude values during low torque, fatiguing contractions reach similar levels as those observed during non-fatigued, high torque contractions. To establish a clearer understanding of motor unit control during fatigue, we compared MUAP amplitude during 50 and 80% maximum voluntary contraction (MVC) torque contractions and at the beginning, middle, and end of a 30% MVC fatigue protocol. Eleven untrained men (mean age = 24years) performed isometric contractions at 50 and 80% MVC, followed by repeated contractions at 30% MVC. Surface electromyographic (EMG) signals were detected from the vastus lateralis and decomposed to quantify the peak-to-peak amplitude of individual MUAPs. A two-level multilevel model was estimated, allowing examination of simultaneous measures of MUAP amplitude within participants and controlling for the dependence between measures within participants. Results from the multilevel analyses suggested that there were not statistically significant differences in MUAP amplitude between 80% MVC and end fatigue. Separate repeated-measures analyses of variance indicated that there were not statistically significant mean differences in greatest MUAP or surface EMG amplitude between 80% MVC and end fatigue. MUAP and surface EMG amplitude values during a 30% MVC fatiguing protocol appear to be comparable to those observed during a non-fatigued 80% MVC condition.

This study aims to characterize motor unit (MU) features associated with muscle fatigue, using high-density surface electromyography (HD-sEMG). The same MUs recruited before / after, and during muscle fatigue were identified for analysis. The surface location of the innervation zones (IZs) of the MUs was identified from the HD-sEMG bipolar motor unit action potential (MUAP) map. The depth of the MU was also identified from the decay pattern of the MUAP along the muscle fiber transverse direction. Both the surface IZ location and the MU depth information were utilized to ensure the same MU was examined during the contraction before / after muscle fatigue. The MUAP similarity, defined as the correlation coefficient between MUAP morphology, was adopted to reveal the alterations in MU characteristics under the condition of fatigue. The biomarkers of the same MUs were compared before / after fatigue (task 1) at 5%, 10%, and 15% maximal voluntary contraction (MVC) and in the process of continuous fatigue (task 2) at 20% MVC. Our results indicate that the MUAP morphology similarity of the same MUs was 0.91 ± 0.06 (task 1) and 0.93 ± 0.04 (task 2). The results showed that MUAP morphology maintained good stability before / after, and during muscle fatigue. The findings of this study may advance our understanding of the mechanism of MU neuromuscular fatigue.

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.

The aim of this study was to investigate motor unit (MU) characteristics of the biceps brachii in poststroke patients using high-density surface electromyography (sEMG). Eighteen chronic hemiparetic stroke patients took part. The Fugl-Meyer score for the upper extremity was assessed. Subjects performed an isometric step contraction consisting of force levels from 5%-50% maximal voluntary contraction while sEMG of the biceps brachii was recorded with a two-dimensional 16-channel electrode array. This was repeated for both sides. Motor unit action potentials (MUAPs) were extracted from the EMG signals, and their root-mean-square value (RMS(MUAP), reflecting MU size) and mean frequency of the power spectrum (FMEAN(MUAP), reflecting recruitment threshold) were calculated. FMEAN(MUAP) was smaller on the affected than on the unaffected side, indicating an increased contribution of low-threshold MUs, possibly related to degeneration of high-threshold MUs. The ratio of RMS(MUAP) on the affected side divided by that on the unaffected side correlated significantly with the Fugl-Meyer score. This ratio may reflect the extent to which reinnervation has occurred on the affected side.

Trigeminal motoneurons were electrically stimulated in order to investigate the electromyographic (EMG) behavior in relation to the contractile properties of motor units of the masseter muscle. A total of 80 motor units were studied in situ in male New Zealand White rabbits ( n=46). The motor units were separated into two groups, each exposed to a specific fatiguing stimulation regimen. Motor unit action potential (MUAP) features, which comprised the amplitude (AMP) and inter-peak time (IPT), and the tetanic force were measured. All motor units were classified as fast (F) units. Forty-one motor units underwent a prolonged standard fatigue regimen of 40-Hz trains at 1 Hz for 20 min. While the MUAP showed an immediate decrease of mean AMP at the beginning of the stimulation, the mean force and IPT increased. After 2 min, the force declined, while the IPT continued to increase until 20 min. Only after 3 min of stimulation, did the degree of force decrease parallel the decline in MUAP AMP. After 20 min of stimulation, the majority of motor units ( n=34) still generated a force larger than 50% of the initial value, but only 17 motor units showed MUAP AMP of less than 50% of the initial EMG response. A more intensive fatigue regimen (40-Hz trains at 1.5 Hz) was applied to another group of 39 motor units. A rapid decline of force and MUAP amplitude to almost 50% was observed within the first 5 min of stimulation. After 20 min, only four motor units were still able to produce a tetanic force of more than 50% of the initial. Most strikingly, motor units with twitch contraction times faster than 22 ms exhibited a decrease in force more than in MUAP AMP, whereas the reverse was seen for units slower than 22 ms; motor units with a twitch contraction time of 22 ms showed equal decrease in AMP and force. This finding is suggestive of a division of fast masseter motor units into two classes, those which fatigue more rapidly mechanically and those which fatigue more readily electrically.

This work is an exposition of research supporting efforts to automate quality assessment in surface electromyography (sEMG). Electromyography measures electrical activity from skeletal muscles, which are the muscles associated with voluntary movements. Skeletal muscles can consist of tens to hundreds of thousands of contractile fibers which are grouped into functional units called Motor Units (MUs). Each MU is driven to contract its fibers by electrochemical impulses sent from a motor neuron, and a muscle may contain anywhere from tens to hundreds of MUs. When an MU is activated, all fibers associated with it are simultaneously activated. When fibers are activated, an electrochemical impulse propagates along each of them to cause contraction. This impulse is known as a Single Fiber Action Potential (SFAP). A Motor Unit Action Potential (MUAP) is the summation of all SFAPs corresponding to an activated MU. To generate a continuous contraction, MUs are repeatedly activated, producing a train of MUAPs, and this pulse train is called the Motor Unit Action Potential Train (MUAPT). The combined electrical activity of all of the MUAPTs associated with a contraction, as recorded on the surface of the skin using non-invasive electrodes, is a surface electromyography (sEMG) signal. In general, it is not possible to directly observe the SFAPs, MUAPs, and MUAPTs non-invasively (though there have been algorithmic efforts to decompose sEMG signals into its constituent MUAPTs). SFAPs and MUAPTs can be observed by inserting needle electrodes into specific muscle regions for high spatial selectivity; however, such techniques are invasive, making surface measurements a desirable alternative. sEMG signals have been used in a wide variety of applications, including fatigue assessment, myoelectric control, diagnosis of neuromuscular disorders, and tracking performance in sports.

Diabetic polyneuropathy (DPN) is a progressive axonopathy marked by loss of motor fibers, compensatory collateral reinnervation and reduced stability of neuromuscular transmission. Our objective was to assess the degree of reinnervation and motor unit instability in patients with DPN using decomposition‐based quantitative electromyography (DQEMG). Additionally, relationships between motor unit stability and muscle function were examined. The tibialis anterior (TA) muscle was tested in twelve patients with DPN (65 ± 15 yrs) and 12 age‐matched controls (63 ± 15 yrs). DQEMG was used to analyze surface and intramuscular EMG signals recorded from the TA during moderate voluntary dorsiflexion contractions. Individual motor unit action potential (MUP) trains were identified and analyzed for: MUP size (peak to peak amplitude, area), complexity (turns, fiber dispersion) and stability (near fiber jiggle). DPN patients featured larger (+45% MUP area), more complex (+40% fiber dispersion), and less stable (+30% near fiber jiggle) MUPs (p<0.05). No significant relationships were found between MUP stability and muscular denervation, or strength. MUP complexity and instability were positively related in DPN patients (r=0.46; p<0.05) and controls (r=0.37; p<0.05). DPN is associated with neuromuscular remodeling which leads to increasingly impaired neuromuscular transmission that is detectable using DQEMG.Grant Funding Source: NSERC

We have measured the firing rate and amplitude of 4551 motor unit action potentials (MUAPs) recorded with concentric needle electrodes from the brachial biceps muscles of 10 healthy young adults before, during, and after 45 minutes of intermittent isometric exercise at 20% of maximum voluntary contraction (MVC), using an automatic method for decomposition of electromyographic activity (ADEMG). During and after exercise, MUAPs derived from contractions of 30% MVC showed progressive increase in mean firing rate (P less than or equal to .01) and amplitude (P less than or equal to .05). The firing rate increase preceded the rise in mean amplitude, and was evident prior to the development of fatigue, defined as reduction of MVC. Analysis of individual potentials revealed that the increase in firing rate and in amplitude reflected different MUAP subpopulations. A short-term (less than 1 minute) reduction in MUAP firing rates (P less than or equal to .05) was also observed at the onset of each test contraction. These findings suggest that motor units exhibit a triphasic behavioral response to prolonged submaximal exercise: (1) short-term decline and stabilization of onset firing rates, followed by (2) gradual and progressive increase in firing rates and firing variability, and then by (3) recruitment of additional (larger) motor units. The (2) and (3) components presumably compensate for loss of force-generating capacity in the exercising muscle, and give rise jointly to the well-known increase in total surface EMG which accompanies muscle fatigue.

Objective.Decomposition of high-density surface electromyography (HDsEMG) signals allows identification of individual motor unit firing times and provides a spatiotemporal image of their action potential waveforms. The ability to reliably match and track motor unit action potentials (MUAPs) from the same motor unit across multiple recordings allows changes in their recruitment and firing properties to be identified, however, similarities in MUAP shape can present challenges for reliable tracking.Approach.A new method for matching MUAP waveforms using a multi-dimensional (MD) representation is presented. MUAPs are represented as trajectories in high-dimensional space, where each HDsEMG channel corresponds to a different dimension. Trajectories are compared using MD features to measure the similarity between pairs of MUAP waveforms. Feature reduction and clustering are then used to classify pairs of MUAPs as belonging to the same or different motor units. The ability of the MD method to correctly identify pairs of matching MUAPs was assessed using MUAPs from simulated and experimental datasets and compared with two-dimensional cross-correlation (CC) using a threshold of 0.7, 0.8 or 0.9.Main results.The proposed MD method resulted in significantly higher F1 scores and lower false positive and false negative rates in both simulated and experimental datasets (p< 0.001). Across all datasets examined, the MD method correctly identified a greater number of matching MUAP pairs (89.8 ± 18.4%) compared with the best performing CC threshold (73.3 ± 21.0%). This was accompanied by a 49.6% lower false positive rate for the MD method.Significance.This study demonstrates that MD representations of MUAP trajectories recorded from high density arrays can more accurately identify MUAPs from the same motor unit, improving motor unit tracking compared with traditional correlation based approaches.

as the final common pathway from the nervous system to muscle, the motor unit transmits an activation signal generated by the nervous system to engage the contractile proteins and produce the muscle forces needed for reflex responses, automatic behaviors, and voluntary actions ([11][1]). The net