Correlation-based decomposition of surface electromyograms at low contraction forces

Acute effects of caffeine or quercetin ingestion on motor unit firing pattern before and after resistance exercise

The aim of the present study was to investigate the acute effect of caffeine or quercetin ingestion on motor unit firing patterns and muscle contractile properties before and after resistance exercise. High-density surface electromyography (HDs-EMG) during submaximal contractions and electrically elicited torque in knee extensor muscles were measured before (PRE) and 60 min after (POST1) ingestion of caffeine, quercetin glycosides, or placebo, and after resistance exercise (POST2) in ten young males. The Convolution Kernel Compensation technique was used to identify individual motor units of the vastus lateralis muscle for the recorded HDs-EMG. Ingestion of caffeine or quercetin induced significantly greater decreases in recruitment thresholds (RTs) from PRE to POST1 compared with placebo (placebo: 94.8 ± 9.7%, caffeine: 84.5 ± 16.2%, quercetin: 91.9 ± 36.7%), and there were significant negative correlations between the change in RTs (POST1-PRE) and RT at PRE for caffeine (rs = - 0.448, p < 0.001) and quercetin (rs =  - 0.415, p = 0.003), but not placebo (rs =  - 0.109, p = 0.440). Significant positive correlations between the change in firing rates (POST2-POST1) and RT at PRE were noted with placebo (rs = 0.380, p = 0.005) and quercetin (rs = 0.382, p = 0.007), but not caffeine (rs = 0.069, p = 0.606). No significant differences were observed in electrically elicited torque among the three conditions. These results suggest that caffeine or quercetin ingestion alters motor unit firing patterns after resistance exercise in different threshold-dependent manners in males.

A fast gradient convolution kernel compensation method for surface electromyogram decomposition

Decomposition of EMG signals provides the decoding of motor unit (MU) discharge timings. In this study, we propose a fast gradient convolution kernel compensation (fgCKC) decomposition algorithm for high-density surface EMG decomposition and apply it to an offline and real-time estimation of MU spike trains. We modified the calculation of the cross-correlation vectors to improve the calculation efficiency of the gradient convolution kernel compensation (gCKC) algorithm. Specifically, the new fgCKC algorithm considers the past gradient in addition to the current gradient. Furthermore, the EMG signals are divided by sliding windows to simulate real-time decomposition, and the proposed algorithm was validated on simulated and experimental signals. In the offline decomposition, fgCKC has the same robustness as gCKC, with sensitivity differences of 2.6 ± 1.3 % averaged across all trials and subjects. Nevertheless, depending on the number of MUs and the signal-to-noise ratio of signals, fgCKC is approximately 3 times faster than gCKC. In the real-time part, the processing only needed 240 ms average per window of EMG signals on a regular personal computer (IIntel(R) Core(TM) i5-12490F 3 GHz, 16 GB memory). These results indicate that fgCKC achieves real-time decomposition by significantly reducing processing time, providing more possibilities for non-invasive neuronal behavior research.

Prediction of 1-year change in knee extension strength by neuromuscular properties in older adults

Improving muscle strength and preventing muscle weakness are important for older adults. The change in strength can be effectively explained by skeletal muscle mass and neural factors. Neural factors are important for older adults because the variation of neural components is greater in older than in young adults, and any decline in strength cannot solely be explained by a decrease in skeletal muscle mass. The purpose of the present study was to investigate whether skeletal muscle mass or motor unit firing properties could explain the change in muscle strength after 1 year. Thirty-eight older adults (75.0 ± 4.7 years, 156.6 ± 7.7 cm, 55.5 ± 9.4 kg, 26 women) performed maximum voluntary knee extension and their skeletal muscle mass was measured using a bioimpedance device. During a submaximal contraction task, high-density surface electromyography was recorded and the signals were decomposed into individual motor unit firing. As an index of motor unit firing properties, the slope and y-intercept (MU intercept) were calculated from the regression line between recruitment thresholds and firing rates in each participant. After 1 year, their maximum knee extension torque was evaluated again. A stepwise multiple regression linear model with sex and age as covariates indicated that MU intercept was a significant explanation with a negative association for the 1-year change in muscle strength (β =  - 0.493, p = 0.004), but not skeletal muscle mass (p = 0.364). The results suggest that neural components might be predictors of increasing and decreasing muscle strength rather than skeletal muscle mass.

The dose-response relationship of quercetin on the motor unit firing patterns and contractile properties of muscle in men and women

Quercetin is one type of ergogenic aid and its effects on the neuromuscular system have recently attracted interest, but its dose-effect is not yet fully understood. The aim of this study was to examine the effect of different doses of quercetin ingestion on motor unit firing patterns and muscle contractile properties in humans. Thirteen young males and females conducted neuromuscular performance tests before (PRE) and 60 min after (POST) ingestions of 500 or 200 mg of quercetin glycosides (Qg500/Qg200, respectively) or placebo (PLA) on three different days. At PRE and POST, motor unit firing rates were calculated from high-density surface electromyography of the vastus lateralis muscle during 120-s isometric contraction of knee extension at 10% of maximal voluntary contraction. Electrically elicited forces in knee extensor muscles were also measured. After 60 s of voluntary contraction, motor unit firing rates, normalized by the exerted muscle force at POST, were significantly lower at POST than PRE with Qg500 and Qg200 (p < 0.05), but not with PLA (p > 0.05). Changes in motor unit firing rates normalized by the exerted force from PRE to POST were significantly greater with Qg500 than Qg200 at the end of contraction (p < 0.05). Under all three conditions, the electrically elicited force did not significantly change from PRE to POST (p > 0.05). These results suggest that both 500 and 200-mg quercetin ingestions alter motor unit firing patterns, and that quercetin's effect is at least partially dose-dependent.

Footedness but not dominance influences force steadiness during isometric dorsiflexion in young men

The aim of the study was to assess the potential influence of footedness and dominance on maximal force, force fluctuations and neural drive during dorsiflexion. Fifteen left-footed (LF) and fifteen right-footed (RF) young adults performed 2 maximal voluntary contractions (MVC) and 3 steady submaximal isometric contractions at five target forces (5, 10, 20, 40 and 60% MVC) with the dorsiflexors of both legs. High-density electromyography (EMG) was used to record the discharge characteristics of motor units (MUs) of Tibialis Anterior. MVC force and EMG amplitude (root mean square) were similar between the two legs and groups (p > 0.05). Force fluctuations (Coefficient of Variation, CoV for force), mean discharge rate of MUs, discharge variability (CoV of interspike interval), and variability in neural drive (standard deviation of filtered cumulative spike train) were greater (p < 0.05) and the input-output gain of the MUs (ΔDR/ΔF) was lower (p < 0.05) for the LF relative to the RF group. The differences in force fluctuations during steady contractions with the dorsiflexors were associated with footedness but not with dominance. They reflect greater variability in motor neuron output, as suggested by coefficient of variation for interspike interval (independent input) and the standard deviation of the smoothed discharge times (common input).

High-Density Surface EMG Decomposition by Combining Iterative Convolution Kernel Compensation With an Energy-Specific Peel-off Strategy

Objective- This study aims to develop a novel framework for high-density surface electromyography (HD-sEMG) signal decomposition with superior decomposition yield and accuracy, especially for low-energy MUs. Methods- An iterative convolution kernel compensation-peel off (ICKC-P) framework is proposed, which consists of three steps: decomposition of the motor units (MUs) with relatively large energy by using the iterative convolution kernel compensation (ICKC) method and extraction of low-energy MUs with a Post-Processor and novel 'peel-off' strategy. Results- The performance of the proposed framework was evaluated by both simulated and experimental HD-sEMG signals. Our simulation results demonstrated that, with 120 simulated MUs, the proposed framework extracts more MUs compared to K-means convolutional kernel compensation (KmCKC) approach across six noise levels. And the proposed 'peel-off' strategy estimates more accurate MUAP waveforms at six noise levels than the 'peel-off' strategy proposed in the progressive FastICA peel-off (PFP) framework. For the experimental sEMG signals recorded from biceps brachii, an average of 16.1 ±3.4 MUs were identified from each contraction, while only 10.0 ± 2.8 MUs were acquired by the KmCKC method. Conclusion- The high yield and accuracy of MUs decomposed from simulated and experimental HD-sEMG signals demonstrate the superiority of the proposed framework in decomposing low-energy MUs compared to existing methods for HD-sEMG signal decomposition. Significance- The proposed framework enables us to construct a more representative motor unit pool, consequently enhancing our understanding pertaining to various neuropathological conditions and providing invaluable information for the diagnosis and treatment of neuromuscular disorders and motor neuron diseases.

Advances in EMG measurement techniques, analysis procedures, and the impact of muscle mechanics on future requirements for the methodology

Muscular coordination enables locomotion and interaction with the environment. For more than 50 years electromyography (EMG) has provided insights into the central nervous system control of individual muscles or muscle groups, enabling both fine and gross motor functions. This information is available either at individual motor units (Mus) level or on a more global level from the coordination of different muscles or muscle groups. In particular, non-invasive EMG methods such as surface EMG (sEMG) or, more recently, spatial mapping methods (High-Density EMG - HDsEMG) have found their place in research into biomechanics, sport and exercise, ergonomics, rehabilitation, diagnostics, and increasingly for the control of technical devices. With further technical advances and a growing understanding of the relationship between EMG and movement task execution, it is expected that with time, especially non-invasive EMG methods will become increasingly important in movement sciences. However, while the total number of publications per year on non-invasive EMG methods is growing exponentially, the number of publications on this topic in journals with a scope in movement sciences has stagnated in the last decade. This review paper contextualizes non-invasive EMG development over the last 50 years, highlighting methodological progress. Changes in research topics related to non-invasive EMG were identified. Today non-invasive EMG procedures are increasingly used to control technical devices, where muscle mechanics have a minor influence. In movement science, however, the effect of muscle mechanics on the EMG signal cannot be neglected. This explains why non-invasive EMG's relevance in movement sciences has not developed as expected.

Alternating or Bilateral Exercise Training does not Influence Force Control during Single-Leg Submaximal Contractions with the Dorsiflexors

The aim of the study was to assess the influence of habitual training history on force steadiness and the discharge characteristics of motor units in tibialis anterior during submaximal isometric contractions. Fifteen athletes whose training emphasized alternating actions (11 runners and 4 cyclists) and fifteen athletes who relied on bilateral actions with leg muscles (7 volleyball players, 8 weight-lifters) performed 2 maximal voluntary contractions (MVC) with the dorsiflexors, and 3 steady contractions at 8 target forces (2.5%, 5%, 10%, 20%, 30%, 40%, 50% and 60% MVC). The discharge characteristics of motor units in tibialis anterior were recorded using high-density electromyography grids. The MVC force and the absolute (standard deviation) and normalized (coefficient of variation) amplitudes of the force fluctuations at all target forces were similar between groups. The coefficient of variation for force decreased progressively from 2.5% to 20% MVC force, then it plateaued until 60% MVC force. Mean discharge rate of the motor units in tibialis anterior was similar at all target forces between groups. The variability in discharge times (coefficient of variation for interspike interval) and the variability in neural drive (coefficient of variation of filtered cumulative spike train) was also similar for the two groups. These results indicate that athletes who have trained with either alternating or bilateral actions with leg muscles has similar effects on maximal force, force control, and variability in the independent and common synaptic input during a single-limb isometric task with the dorsiflexors.

Bio-robotics research for non-invasive myoelectric neural interfaces for upper-limb prosthetic control: a 10-year perspective review

A decade ago, a group of researchers from academia and industry identified a dichotomy between the industrial and academic state-of-the-art in upper-limb prosthesis control, a widely used bio-robotics application. They proposed that four key technical challenges, if addressed, could bridge this gap and translate academic research into clinically and commercially viable products. These challenges are unintuitive control schemes, lack of sensory feedback, poor robustness and single sensor modality. Here, we provide a perspective review on the research effort that occurred in the last decade, aiming at addressing these challenges. In addition, we discuss three research areas essential to the recent development in upper-limb prosthetic control research but were not envisioned in the review 10 years ago: deep learning methods, surface electromyogram decomposition and open-source databases. To conclude the review, we provide an outlook into the near future of the research and development in upper-limb prosthetic control and beyond.

Acute changes in motor unit discharge property after concentric versus eccentric contraction exercise in knee extensor

This study aimed to investigate the motor unit firing property immediately after concentric or eccentric contraction exercise. Eighteen healthy men performed repetitive maximal isokinetic knee extension exercises with only concentric or eccentric contraction until they exerted less than 80% of the baseline strength. Before and after the fatiguing exercise, high-density surface electromyography of the vastus lateralis was recorded during submaximal ramp-up isometric contraction and individual motor units were identified. Only motor units that could be tracked before and after exercise were analyzed. Muscle cross-sectional area of the vastus lateralis was measured using ultrasound, and electrically evoked torque was recorded before and after the exercise. Sixty-five and fifty-three motor units were analyzed before and after the concentric and eccentric contractions, respectively. The results showed that motor units with moderate to high recruitment thresholds significantly decreased recruitment thresholds under both conditions, and the motor unit discharge rates significantly increased after concentric contraction compared to eccentric contraction. A greater muscle cross-sectional area was observed with concentric contraction. The evoked torque was significantly decreased under both conditions, but no difference between the conditions. These results suggest that fatiguing exercise with concentric contraction contributes to greater neural input to muscles and metabolic responses than eccentric contraction.

Motor unit firing patterns of lower leg muscles during isometric plantar flexion with flexed knee joint position

The ankle flexor and extensor muscles are essential for pedal movements associated with car driving. Neuromuscular activation of lower leg muscles is influenced by the posture during a given task, such as the flexed knee joint angle during car driving. This study aimed to investigate the influence of flexion of the knee joint on recruitment threshold-dependent motor unit activity in lower leg muscles during isometric contraction. Twenty healthy participants performed plantar flexor and dorsiflexor isometric ramp contractions at 30 % of the maximal voluntary contraction (MVC) with extended (0°) and flexed (130°) knee joint angles. High-density surface electromyograms were recorded from medial gastrocnemius (MG), soleus (SOL), and tibialis anterior (TA) muscles and decomposed to extract individual motor units. The torque-dependent change (Δpps /Δ%MVC) of the motor unit activity of MG (recruited at 15 %MVC) and SOL (recruited at 5 %MVC) muscles was higher with a flexed compared with an extended knee joint (p < 0.05). The torque-dependent change of TA MU did not different between the knee joint angles. The motor units within certain limited recruitment thresholds recruited to exert plantar flexion torque can be excited to compensate for the loss of MG muscle torque output with a flexed knee joint.

Leg Dominance Does Not Influence Maximal Force, Force Steadiness, or Motor Unit Discharge Characteristics

PURPOSE

The aim of our study was to compare maximal force, force steadiness, and discharge characteristics of motor units in tibialis anterior during contractions with the dorsiflexors of the dominant and nondominant legs at low-to-moderate target forces and three ankle angles.

METHODS

Twenty young adults performed maximal and submaximal isometric contractions (5%, 10%, 20%, 40%, and 60% of maximal voluntary contraction (MVC)) with the dorsiflexors of the dominant and nondominant legs at three ankle angles (75°, short length; 90°, intermediate length; 105°, long length). High-density EMG signals from the tibialis anterior muscle of each leg were recorded.

RESULTS

Maximal force (average dominant, 182.9 ± 64.5 N; nondominant, 179.0 ± 58.8 N) and the fluctuations in force, quantified as absolute (SD) and normalized amplitudes (coefficient of variation (CoV)), were similar between the two legs across the three ankle angles (average CoV for dominant, 1.5% ± 1.0%; nondominant, 1.7% ± 1.3%). The CoV for force for both legs decreased from 5% to 20% MVC force, and then it plateaued at 40% and 60% MVC force. EMG amplitude, mean discharge rate of motor units, discharge variability (interspike interval), and the variability in neural drive (filtered cumulative spike train) were similar between the two legs across the submaximal contractions.

CONCLUSIONS

MVC force and force steadiness were similar across ankle angles and target forces between the dominant and nondominant legs. The attributes that underlie the self-reported identification of a dominant leg were not associated with the force capacity or the control of force for the dorsiflexor muscles, at least during isometric contractions.

Segment-Wise Decomposition of Surface Electromyography to Identify Discharges Across Motor Neuron Populations

OBJECTIVE

The surface electromyography (EMG) decomposition techniques have shown promising results in neurophysiologic investigations, clinical diagnosis, and human-machine interfacing. However, current decomposition methods could only decode a limited number of motor units (MUs) because of the local convergence. The number of identified MUs remains similar even though more muscles or movements are involved, where multiple motor neuron populations are activated. The objective of this study was to develop a segment-wise decomposition strategy to increase the number of MU decoded from multiple motor neuron populations.

METHODS

The EMG signals were divided into several segments depending on the number of involved movements. The motor neurons, activated during each movement, were regarded as a population. The convolution kernel compensation (CKC) method was applied individually for each segment to decode the motor unit discharges from each motor neuron population. The MU filters were obtained in each segment and filtrated to estimate the MU spike trains (MUSTs) from the global EMG signals. The decomposition performance was validated on synthetic and experimental EMG signals.

MAIN RESULTS

From synthetic EMG signals generated by two motor neuron populations, the proposed segment-wise CKC (swCKC) decoded significantly more MUs during low and medium excitation levels, with an increased rate of 16.3% to 75.4% compared with the conventional CKC. From experimental signals recorded during ten motor tasks, 133±24 MUs with the pulse-to-noise ratio of 36.6±6.5 dB were identified for each subject by swCKC, whereas the conventional CKC identified only 43±12 MUs.

CONCLUSION AND SIGNIFICANCE

These results indicate the feasibility and superiority of the proposed swCKC to decode MU activities across motor neuron populations, extending the potential applications of EMG decomposition for neural decoding during multiple motor tasks.

Detecting motor unit abnormalities in amyotrophic lateral sclerosis using high-density surface EMG

OBJECTIVE

The purpose of this study was to detect specific motor unit (MU) abnormalities in people with amyotrophic lateral sclerosis (ALS) compared to controls using high-density surface electromyography (HD-SEMG).

METHODS

Sixteen people with ALS and 16 control subjects. The participants performed ramp up and sustained contractions at 30% of their maximal voluntary contraction. HD-SEMG signals were recorded in the vastus lateralis muscle and decomposed into individual MU firing behavior using a convolution blind source separation method.

RESULTS

In total, 339 MUs were detected (people with ALS; n = 93, control subjects; n = 246). People with ALS showed significantly higher mean firing rate, recruitment threshold, coefficient of variation of the MU firing rate, MU firing rate at recruitment, and motoneurons excitability than those of control subjects (p < 0.001). The number of MU, MU firing rate, recruitment threshold, and MU firing rate at recruitment were significantly correlated with disease severity (p < 0.001). Multivariable analysis revealed that an increased MU firing rate at recruitment was independently associated with ALS.

CONCLUSIONS

These results suggest increased excitability at recruitment, which is consistent with neurodegeneration results in a compensatory increase in MU activity.

SIGNIFICANCE

Abnormal MU firing behavior provides an important physiological index for understanding the pathophysiology of ALS.

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.

Neuromuscular characteristics of front and back legs in junior fencers

In elite fencers, muscle strength and muscle mass of the front leg (FL) are greater than those of the back leg (BL) due to characteristic physiological and biomechanical demands placed on each leg during fencing. However, the development of laterality in their neural and muscular components is not well-understood. The present study investigated neuromuscular characteristics of FL and BL in junior fencers. Nineteen junior fencers performed neuromuscular performance tests for FL and BL, separately. There were no significant differences in the isometric knee extension strength (MVC), unilateral vertical jump (UVJ), vastus lateralis muscle thickness (MT), or motor unit firing rate of the vastus lateralis muscle (MUFR) between FL and BL (p > 0.05). In subgroup analyses, a significantly greater MUFR in FL than BL was noted only in fencers with > 3 years of fencing experience, and significantly greater UVJ in FL than BL was observed solely in fencers with < 3 years of fencing experience (p < 0.05). Strong positive correlations between FL and BL were identified in MVC, MT, and MUFR in fencers with > 3 years of fencing experience, but not in those with < 3 years of experience. These findings suggest that in junior fencers, laterality in neuromuscular performance has not manifested, whereas longer fencing experience induces fencing-dependent laterality in neural components, and laterality in dynamic muscle strength is decreased with fencing experience.

Fundamental Concepts of Bipolar and High-Density Surface EMG Understanding and Teaching for Clinical, Occupational, and Sport Applications: Origin, Detection, and Main Errors

Surface electromyography (sEMG) has been the subject of thousands of scientific articles, but many barriers limit its clinical applications. Previous work has indicated that the lack of time, competence, training, and teaching is the main barrier to the clinical application of sEMG. This work follows up and presents a number of analogies, metaphors, and simulations using physical and mathematical models that provide tools for teaching sEMG detection by means of electrode pairs (1D signals) and electrode grids (2D and 3D signals). The basic mechanisms of sEMG generation are summarized and the features of the sensing system (electrode location, size, interelectrode distance, crosstalk, etc.) are illustrated (mostly by animations) with examples that teachers can use. The most common, as well as some potential, applications are illustrated in the areas of signal presentation, gait analysis, the optimal injection of botulinum toxin, neurorehabilitation, ergonomics, obstetrics, occupational medicine, and sport sciences. The work is primarily focused on correct sEMG detection and on crosstalk. Issues related to the clinical transfer of innovations are also discussed, as well as the need for training new clinical and/or technical operators in the field of sEMG.

Physical and electrophysiological motor unit characteristics are revealed with simultaneous high-density electromyography and ultrafast ultrasound imaging

Electromyography and ultrasonography provide complementary information about electrophysiological and physical (i.e. anatomical and mechanical) muscle properties. In this study, we propose a method to assess the electrical and physical properties of single motor units (MUs) by combining High-Density surface Electromyography (HDsEMG) and ultrafast ultrasonography (US). Individual MU firings extracted from HDsEMG were used to identify the corresponding region of muscle tissue displacement in US videos. The time evolution of the tissue velocity in the identified region was regarded as the MU tissue displacement velocity. The method was tested in simulated conditions and applied to experimental signals to study the local association between the amplitude distribution of single MU action potentials and the identified displacement area. We were able to identify the location of simulated MUs in the muscle cross-section within a 2 mm error and to reconstruct the simulated MU displacement velocity (cc > 0.85). Multiple regression analysis of 180 experimental MUs detected during isometric contractions of the biceps brachii revealed a significant association between the identified location of MU displacement areas and the centroid of the EMG amplitude distribution. The proposed approach has the potential to enable non-invasive assessment of the electrical, anatomical, and mechanical properties of single MUs in voluntary contractions.

Association of Muscle Strength With Muscle Thickness and Motor Unit Firing Pattern of Vastus Lateralis Muscle in Youth Athletes

Purpose: Contributions of neural and muscular factors to muscle strength change with growth, but such changes remain unclear in young populations. This study aimed to clarify the association between muscle strength and neural and muscular factors in youth athletes. Methods: Maximal voluntary contraction (MVC) during isometric knee extension, the motor unit firing rate (MUFR), and muscle thickness (MT) of the vastus lateralis were measured in 70 youth male soccer players (mean [SD]; chronological age = 16.3 [0.6] y, peak height velocity age = 13.1 [1.0] y). MUFR and MT were measured with high-density surface electromyography and ultrasonography, respectively. Results: For MUFR and MT, correlations with MVC were calculated and the values of different MVC groups were compared. A significant correlation between MVC and MT (r = .49, P < .01) was noted, but not MUFR (r = .03, P > .05). There was also no significant correlation between MT and MUFR (r = −.33, P > .05). In addition, comparison among groups (higher-/middle-/lower-strength groups) revealed that MT in the lower-strength group was significantly lower than in middle-and higher-strength groups (P < .01). Conclusion: In youth athletes, muscle strength is associated with muscular factors, rather than neural factors, and muscular and neural factors may independently contribute to muscle strength.

Motor unit firing patterns on increasing force during force and position tasks

Different neurophysiological strategies are used to perform angle adjustments during motor tasks such as car driving and force-control tasks using a fixed-rigid pedal. However, the difference in motor unit behavior in response to an increasing exerted force between tasks is unknown. This study aimed to investigate the difference in motor unit responsiveness on increasing force between force and position tasks. Twelve healthy participants performed ramp and hold contractions during ankle plantarflexion at 20% and 30% of the maximal voluntary contraction using a rigid pedal (force task) and a free pedal with an inertial load (position task). High-density surface electromyograms were recorded of the medial gastrocnemius muscle and decomposed into individual motor unit firing patterns. Ninety and hundred and nine motor units could be tracked between different target torques in each task. The mean firing rate increased and firing rate variability decreased on 10% maximal voluntary contraction force gain during both force and position tasks. There were no significant differences in these responses between the two tasks. Our results suggest that the motor unit firing rate is similarly regulated between force and position tasks in the medial gastrocnemius muscle with an increase in the exerted force.NEW & NOTEWORTHY Different neurophysiological strategies are used to perform a force control task and angle adjustment task. Our results showed that motor unit firing rate is similarly regulated between the two tasks in the medial gastrocnemius muscle with an increase in the exerted force. Although it is reported that position tasks contribute to early fatigue, it does not seem to be a particular problem for the increase in force.

Association between the Degree of Pre-Synaptic Dopaminergic Pathway Degeneration and Motor Unit Firing Behavior in Parkinson's Disease Patients

The relationship between motor unit (MU) firing behavior and the severity of neurodegeneration in Parkinson’s disease (PD) is not clear. This study aimed to elucidate the association between degeneration with dopaminergic pathways and MU firing behavior in people with PD. Fourteen females with PD (age, 72.6 ± 7.2 years, disease duration, 3.5 ± 2.1 years) were enrolled in this study. All participants performed a submaximal, isometric knee extension ramp-up contraction from 0% to 80% of their maximal voluntary contraction strength. We used high-density surface electromyography with 64 electrodes to record the muscle activity of the vastus lateralis muscle and decomposed the signals with the convolution kernel compensation technique to extract the signals of individual MUs. We calculated the degree of degeneration of the central lesion-specific binding ratio by dopamine transporter single-photon emission computed tomography. The primary, novel results were as follows: (1) moderate-to-strong correlations were observed between the degree of degeneration of the central lesion and MU firing behavior; (2) a moderate correlation was observed between clinical measures of disease severity and MU firing behavior; and (3) the methods of predicting central nervous system degeneration from MU firing behavior abnormalities had a high detection accuracy with an area under the curve >0.83. These findings suggest that abnormalities in MU activity can be used to predict central nervous system degeneration following PD.

The length of tibialis anterior does not influence force steadiness during submaximal isometric contractions with the dorsiflexors

The purpose of the study was to assess the influence of short, intermediate, and long muscle lengths on dorsiflexor force steadiness and the discharge characteristics of motor units in tibialis anterior during submaximal isometric contractions. Steady contractions were performed at 5 target forces (5, 10, 20, 40, and 60% maximal voluntary contraction, MVC) for 3 ankle angles (75°, 90°, and 105°). MVC force was less (p = 0.043) at the smallest joint angle compared with the other two angles. The absolute (standard deviation) and normalised amplitudes (coefficient of variation) of the force fluctuations were similar for all 3 ankle angles at each target force. The coefficient of variation for force decreased progressively from 5% to 20% MVC force and then it plateaued at 40% and 60% MVC force. At all target forces, the mean discharge rate (MDR) of the motor units at 75° was greater than at 90° (p = 0.006) and 105° (p = 0.034). Moreover, the MDR was similar for 5% and 10% MVC forces and then increased gradually until 60% MVC force (p < 0.005). The variability in discharge times (coefficient of variation for interspike interval) and variability in neural drive (coefficient of variation of filtered cumulative spike train) were similar at all ankle angles. Variability in neural drive had a greater influence on force steadiness than did the variability in discharge times. Changes in ankle-joint angle did not influence either the normalised amplitude force fluctuations during steady submaximal contractions or the underlying modulation of the discharge characteristics of motor units in tibialis anterior.

Quercetin ingestion modifies human motor unit firing patterns and muscle contractile properties

Quercetin is a polyphenolic flavonoid that has reported to block the binding of adenosine to A1 receptors at central nervous system and increase calcium release from the sarcoplasmic reticulum at skeletal muscle. The aim of the present study was to investigate the acute effect of quercetin ingestion on motor unit activation and muscle contractile properties. High-density surface electromyography during submaximal contractions and electrically elicited contraction torque in knee extensor muscles were measured before (PRE) and 60 min after (POST) quercetin glycosides or placebo ingestions in 13 young males. Individual motor units of the vastus lateralis muscle were identified from high-density surface electromyography by the Convolution Kernel Compensation technique. Firing rates of motor units recruited at 30–50% of the maximal voluntary contraction torque (MVC) were increased from PRE to POST only with quercetin (9.0 ± 2.3 to 10.5 ± 2.0 pps, p = 0.034). Twitch torque during doublet stimulation was decreased from PRE to POST with placebo (77.1 ± 17.1 to 73.9 ± 17.6 Nm, p = 0.005), but not with quercetin (p > 0.05). For motor units recruited at < 10% of MVC, normalized firing rate were decreased with quercetin (1.52 ± 0.33 to 1.58 ± 0.35%MVC/pps, p = 0.002) but increased with placebo (1.61 ± 0.32 to 1.57 ± 0.31%MVC/pps, p = 0.005). These results suggest that ingested quercetin has the functional roles to: mitigate reduction in the muscle contractile properties, enhance activations of relatively higher recruitment threshold motor units, and inhibit activation of relatively lower recruitment threshold motor units.

Fish Protein Ingestion Induces Neural, but Not Muscular Adaptations, Following Resistance Training in Young Adults

Purpose: Nutritional supplementation in conjunction with exercise is of interest for the prevention or improvement of declines in motor performances in older adults. An understanding of the effects on both young and older adults contributes to its effective application. We investigated the effect of fish protein ingestion with resistance training on neural and muscular adaptations in young adults using interventions and assessments that have already been tested in older adults.

Methods: Eighteen young adults underwent 8 weeks of isometric knee extension training. During the intervention, nine participants ingested 5 g of fish protein (n = 9, Alaska pollack protein, APP), and the other nine participants ingested casein as a control (n = 9, CAS) in addition to daily meals. Before, during, and after the intervention, the isometric knee extension force, lower extremity muscle mass, and motor unit firing pattern of knee extensor muscles were measured.

Results: Maximum voluntary contraction (MVC) was significantly increased in both APP and CAS groups from 0 weeks to 4, 6, and 8 weeks of intervention (p < 0.001), but there were no significant differences between the groups (p = 0.546–0.931). Muscle mass was not significantly changed during the intervention in either group (p = 0.250–0.698). Significant changes in motor unit firing rates (p = 0.02 and 0.029 for motor units recruited at 20–40% of MVC and at 40–60%) were observed following the intervention in the APP but not CAS (p = 0.120–0.751) group.

Conclusions: These results suggest that dietary fish protein ingestion changes motor unit adaptations following resistance training in young adults.

Modulation of Neural and Muscular Adaptation Processes During Resistance Training by Fish Protein Ingestions in Older Adults

Assessments of both neural and muscular adaptations during interventions would provide valuable information for developing countermeasures to age-related muscle dysfunctions. We investigated the effect of fish protein ingestion on training-induced neural and muscular adaptations in older adults. Twenty older adults participated 8 weeks of isometric knee extension training intervention. The participants were divided into two groups who took fish protein (n = 10, Alaska pollack protein, APP) or casein (n = 10, CAS). Maximal muscle strength during knee extension, lower extremity muscle mass (body impedance method), and motor unit firing pattern of knee extensor muscle (high-density surface electromyography) were measured before, during, and after the intervention. Muscle strength were significantly increased in both CAS (124.7 ± 5.8%) and APP (117.1 ± 4.4%) after intervention (p < .05), but no significant differences between the groups were observed (p > .05). Significant increases in lower extremity muscle mass from 0 to 8 weeks were demonstrated only for APP (102.0 ± 3.2, p < .05). Greater changes in motor unit firing pattern following intervention were represented in CAS more than in APP. These results suggest that nutritional supplementations could modulate neural and muscular adaptations following resistance training and fish protein ingestion preferentially induces muscular adaptation without the detectable neural adaptation in older adults.

The Effects of Spinal Manipulation on Motor Unit Behavior

Over recent years, a growing body of research has highlighted the neural plastic effects of spinal manipulation on the central nervous system. Recently, it has been shown that spinal manipulation improved outcomes, such as maximum voluntary force and limb joint position sense, reflecting improved sensorimotor integration and processing. This study aimed to further evaluate how spinal manipulation can alter neuromuscular activity. High density electromyography (HD sEMG) signals from the tibialis anterior were recorded and decomposed in order to study motor unit changes in 14 subjects following spinal manipulation or a passive movement control session in a crossover study design. Participants were asked to produce ankle dorsiflexion at two force levels, 5% and 10% of maximum voluntary contraction (MVC), following two different patterns of force production (“ramp” and “ramp and maintain”). A significant decrease in the conduction velocity (p = 0.01) was observed during the “ramp and maintain” condition at 5% MVC after spinal manipulation. A decrease in conduction velocity suggests that spinal manipulation alters motor unit recruitment patterns with an increased recruitment of lower threshold, lower twitch torque motor units.

Identification of the laterality of motor unit behavior in female patients with parkinson's disease using high-density surface electromyography

Patients with Parkinson's disease (PD) have greater laterality of muscle contraction properties than other people with parkinsonism diseases. However, few studies have reported the laterality of MU activation properties of the lower extremity muscles in patients with PD. The aim of the present study was to identify the laterality of MU behavior in PD patients using high-density surface electromyography (HD-SEMG). Eleven female patients with PD (age, 69.2 ± 6.2 years, disease duration, 2.7 ± 0.9 years, Unified Parkinson's disease Rating Scale score, 13 (9-16)), and 9 control female subjects (age, 66.8 ± 3.5 years) were enrolled in the present study. All subjects performed a sustained isometric knee extension in a 30% maximal voluntary contraction (MVC) task for 20 s. HD-SEMG signals were used to record and extract single MU firing behavior in the vastus lateralis muscle during submaximal isometric knee extensor contractions with 64 electrodes and decomposed with the convolution kernel compensation technique to extract individuals MUs. Compared to the control subjects, the patients with PD exhibited laterality of the MU firing rate and an absence of a relationship between the mean MU firing rate and MU threshold. Patients with PD exhibit laterality of MU behavior and experience MU behavioral abnormalities even with mild symptoms such as Hoehn & Yahr stage ≤ 3 and disease duration = 2.7 ± 0.9. These findings suggest the importance of considering the detection of abnormal muscle properties in PD patients beginning in the early phase of the disease.

High-density surface electromyography signals during isometric contractions of elbow muscles of healthy humans

This paper presents a dataset of high-density surface EMG signals (HD-sEMG) designed to study patterns of sEMG spatial distribution over upper limb muscles during voluntary isometric contractions. Twelve healthy subjects performed four different isometric tasks at different effort levels associated with movements of the forearm. Three 2-D electrode arrays were used for recording the myoelectric activity from five upper limb muscles: biceps brachii, triceps brachii, anconeus, brachioradialis, and pronator teres. Technical validation comprised a signals quality assessment from outlier detection algorithms based on supervised and non-supervised classification methods. About 6% of the total number of signals were identified as "bad" channels demonstrating the high quality of the recordings. In addition, spatial and intensity features of HD-sEMG maps for identification of effort type and level, have been formulated in the framework of this database, demonstrating better performance than the traditional time-domain features. The presented database can be used for pattern recognition and MUAP identification among other uses.

Does strict validation criteria for individual motor units alter population-based regression models of the motor unit pool?

The purpose of this study was to determine if the implementation of a strict validation procedure, designed to limit the inclusion of inaccuracies from the decomposition of surface electromyographic (sEMG) signals, affects population-based motor unit (MU) analyses. Four sEMG signals were obtained from the vastus lateralis of 59 participants during isometric contractions at different relative intensities [30%, 70%, and 100% of maximal voluntary contraction (MVC)], and its individual motor unit potential trains (MUPTs) were extracted. The MUPTs were then excluded (ISIval) based on the coefficient of variation and histogram of the interspike intervals (ISI), the absence of additional clusters that reveals missed or additional firings, and more. MU population-based regression models (i.e., modeling the entire motor unit pool) were performed between motor unit potential size (MUP_SIZE), mean firing rate (MFR), and recruitment threshold (RT%) separately for DSDC_Only (includes all MUPTs without the additional validation performed) and ISIval data at each contraction intensity. The only significant difference in regression coefficients between DSDC_Only and ISIval was for the intercepts of the MUP_SIZE/MFR at 100% MVC. The validation had no other significant effect on any of the other regression coefficients for each of the contraction intensities. Our findings suggest that even though the decomposition of surface signals leads to some inaccuracies, these errors have limited effects on the regression models used to estimate the behavior of the whole pool. Therefore, we propose that motor unit population-based regression models may be robust enough to overcome decomposition-induced errors at the individual MU level.

A Multiday Evaluation of Real-Time Intramuscular EMG Usability with ANN

Recent developments in implantable technology, such as high-density recordings, wireless transmission of signals to a prosthetic hand, may pave the way for intramuscular electromyography (iEMG)-based myoelectric control in the future. This study aimed to investigate the real-time control performance of iEMG over time. A novel protocol was developed to quantify the robustness of the real-time performance parameters. Intramuscular wires were used to record EMG signals, which were kept inside the muscles for five consecutive days. Tests were performed on multiple days using Fitts' law. Throughput, completion rate, path efficiency and overshoot were evaluated as performance metrics using three train/test strategies. Each train/test scheme was categorized on the basis of data quantity and the time difference between training and testing data. An artificial neural network (ANN) classifier was trained and tested on (i) data from the same day (WDT), (ii) data collected from the previous day and tested on present-day (BDT) and (iii) trained on all previous days including the present day and tested on present-day (CDT). It was found that the completion rate (91.6 ± 3.6%) of CDT was significantly better (p < 0.01) than BDT (74.02 ± 5.8%) and WDT (88.16 ± 3.6%). For BDT, on average, the first session of each day was significantly better (p < 0.01) than the second and third sessions for completion rate (77.9 ± 14.0%) and path efficiency (88.9 ± 16.9%). Subjects demonstrated the ability to achieve targets successfully with wire electrodes. Results also suggest that time variations in the iEMG signal can be catered by concatenating the data over several days. This scheme can be helpful in attaining stable and robust performance.

Effect of milk fat globule membrane supplementation on motor unit adaptation following resistance training in older adults

This study aimed to investigate the effect of milk fat globule membrane (MFGM) supplementation on motor unit adaptation following resistance training in older adults. Twenty-five older males and females took MFGM (n = 12) or a placebo (PLA; n = 12) while performing 8 weeks of isometric knee extension training. During the training, the motor unit firing pattern during submaximal contractions, muscle thickness, and maximal muscle strength of knee extensor muscles were measured every 2 weeks. None of the measurements showed significant differences in muscle thickness or maximal muscle strength (MVC) between the two groups (p > .05). Significant decreases in motor unit firing rate following the intervention were observed in PLA, that is, 14.1 ± 2.7 pps at 0 weeks to 13.0 ± 2.4 pps at 4 weeks (p = .003), but not in MFGM (14.4 ± 2.5 pps to 13.8 ± 1.9 pps). Motor unit firing rates in MFGM were significantly higher than those in PLA at 2, 4, 6, and 8 weeks of the intervention, that is, 15.1 ± 2.3 pps in MFGM and 14.5 ± 3.3 pps in PLA at 70% of MVC for motor units recruited at 40% of MVC at 6 weeks (p = .034). Significant differences in firing rates among motor units with different recruitment thresholds were newly observed following the resistance training intervention in MFGM, indicating that motor unit firing pattern is changed in this group. These results suggest that motor unit adaptation following resistance training is modulated by MFGM supplementation in older adults.

Decomposing single-channel intramuscular electromyography signal sampled at a low frequency into its motor unit action potential trains with a generative adversarial network

Conventional methods decompose single-channel intramuscular electromyography (iEMG) signals into their constituent motor unit action potential trains (MUAPTs) by detecting and clustering individual motor unit action potentials (MUAPs). However, these methods are not applicable for iEMG signals recorded by electrodes with a large sensing areas or iEMG signals sampled at a low frequency, in which detecting and clustering individual MUAPs are difficult due to superimpositions of the MUAPs and the loss of MUAP morphological characteristics. In this study, we propose an approach based on a generative adversarial network to decompose iEMG signals, which does not depend on detecting and clustering individual MUAPs from the iEMG signal. The proposed approach decomposes the iEMG signal into its MUAPTs based on Bayes' law and a Wasserstein generative adversarial network with gradient penalty (WGAN-GP). MUAPTs generated by the WGAN-GP were used to decompose the iEMG signal to maximize the posterior probability of the generated MUAPTs given the iEMG signal. The accuracy of the proposed approach is analysed directly by decomposing the simulated iEMG signal with seven gold-standard motor units. The results showed that the proposed approach achieved a 53% accuracy in capturing the firing regularities of the MUs, while the conventional method achieved a 37% accuracy on the same task.

Effect of Resistance Training and Fish Protein Intake on Motor Unit Firing Pattern and Motor Function of Elderly

We investigated the effect of resistance training and fish protein intake on the motor unit firing pattern and motor function in elderly. Fifty healthy elderly males and females (69.2 ± 4.7 years) underwent 6 weeks of intervention. We applied the leg-press exercise as resistance training and fish protein including Alaska pollack protein (APP) as nutritional supplementation. Subjects were divided into four groups: fish protein intake without resistance training (APP-CN, n = 13), placebo intake without resistance training (PLA-CN, n = 12), fish protein intake with resistance training (APP-RT, n = 12), and placebo intake with resistance training (PLA-RT, n = 13). Motor unit firing rates were calculated from multi-channel surface electromyography by the Convolution Kernel. For the chair-stand test, while significant increases were observed at 6 weeks compared with 0 week in all groups (p < 0.05), significant increases from 0 to 3 weeks and 6 weeks were observed in APP-RT (18.2 ± 1.9 at 0 week to 19.8 ± 2.2 at 3 weeks and 21.2 ± 1.9 at 6 weeks) (p < 0.05). Increase and/or decrease in the motor unit firing rate were mainly noted within motor units with a low-recruitment threshold in APP-RT and PLA-RT at 3 and 6 weeks (12.3 pps at 0 week to 13.6 pps at 3 weeks and 12.1 pps at 6 weeks for APP-RT and 12.9 pps at 0 week to 13.9 pps at 3 weeks and 14.1 pps at 6 weeks for PLA-RT at 50% of MVC) (p < 0.05), but not in APP-CN or PLA-CN (p > 0.05). Time courses of changes in the results of the chair-stand test and motor unit firing rate were different between APP-RT and PLA-RT. These findings suggest that, in the elderly, the effect of resistance training on the motor unit firing rate is observed in motor units with a low-recruitment threshold, and additional fish protein intake modifies these adaptations in motor unit firing patterns and the motor function following resistance training.

On the Impact of Muscle Shortening on Non-Negative Matrix Factorization of Dynamic Surface Electromyograms

We analyzed the sensitivity of Non-negative Matrix Factorization (NMF) of dynamic surface electromyograms (EMG) to muscle shortening. We first identified Motor unit action potentials (MUAPs) by decomposing experimentally recorded EMG signals during slow shortening of biceps brachii muscle in five young healthy males. We then used these MUAPs to generate different synthetic EMG signals with different muscle shortening and excitation profiles. Afterwards, we applied NMF to the synthetic EMG signals and calculated Pearson correlation coefficient (CC) between the extracted NMF components and a) muscle shortening and b) muscle excitation profiles. The results demonstrated good match between NMF components and muscle excitation profiles, but only when the muscle excitation level changed for at least 10 % during the muscle shortening. During constant muscle excitation, the resulting NMF components correlated significantly with the muscle shortening profiles. These results demonstrate that NMF components reflect not only the muscle excitation profiles but also muscle shortening profiles. Therefore, the results of NMF analysis of dynamic EMG signals need to be interpreted with caution.

Comparison of Convolutive Kernel Compensation and Non-Negative Matrix Factorization of Surface Electromyograms

We compared non-negative matrix factorization (NMF) and convolution kernel compensation techniques for high-density electromyogram decomposition. The experimental data were recorded from nine healthy persons during controlled single degree of freedom (DOF) wrist flexion-extension, supination-pronation, and ulnar-radial deviation movements. We assembled the identified motor units and NMF components into three groups. Those active mostly during the first and the second movement direction per DOF were placed in the G1 and G3 groups, respectively. The remaining components were nonspecific for movement direction and were placed in the G2 group. In ulnar and radial deviation, the relative energies of identified cumulative motor unit spike trains (CSTs) and NMF components were similarly distributed among the groups. In other two movement types, the energy of NMF components in the G2 group was significantly larger than the energy of CSTs. We further performed a coherence analysis between CSTs and sums of NMF components in each group. Both decompositions demonstrated a solid match, but only at frequencies <3 Hz. At higher frequencies, the coherence hardly exceeded the value of 0.5. Potential reasons for these discrepancies include the negative impact of motor unit action potential shapes and noise on NMF decomposition.

Variability in common synaptic input to motor neurons modulates both force steadiness and pegboard time in young and older adults

KEY POINTS

The fluctuations in force during a steady isometric contraction (force steadiness) are associated with oscillations in common synaptic input to the involved motor neurons. Decreases in force steadiness are associated with increases in pegboard times in older adults, although a mechanism for this link has not been established. We used a state-space model to estimate the variability in common synaptic input to motor neurons during steady, isometric contractions. The estimate of common synaptic input was derived from the discharge times of motor units as recorded with high-density surface electrodes. We found that the variability in common synaptic input to motor neurons modulates force steadiness for young and older adults, as well as pegboard time for older adults.

ABSTRACT

We investigated the associations between grooved pegboard times, force steadiness (coefficient of variation for force) and variability in an estimate of the common synaptic input to motor neurons innervating the wrist extensor muscles during steady contractions performed by young and older adults. The discharge times of motor units were derived from recordings obtained with high-density surface electrodes when participants performed steady isometric contractions at 10% and 20% of maximal voluntary contraction force. The steady contractions were performed with a pinch grip and wrist extension, both independently (single action) and concurrently (double action). The variance in common synaptic input to motor neurons was estimated with a state-space model of the latent common input dynamics. There was a statistically significant association between the coefficient of variation for force during the steady contractions and the estimated variance in common synaptic input in young (r2  = 0.31) and older (r2  = 0.39) adults, although not between either the mean or the coefficient of variation for interspike interval of single motor units with the coefficient of variation for force. Moreover, the estimated variance in common synaptic input during the double-action task with the wrist extensors at the 20% target was significantly associated with grooved pegboard time (r2  = 0.47) for older adults but not young adults. These findings indicate that longer pegboard times of older adults were associated with worse force steadiness and greater fluctuations in the estimated common synaptic input to motor neurons during steady contractions.

A latent low-dimensional common input drives a pool of motor neurons: a probabilistic latent state-space model

Motor neurons appear to be activated with a common input signal that modulates the discharge activity of all neurons in the motor nucleus. It has proven difficult for neurophysiologists to quantify the variability in a common input signal, but characterization of such a signal may improve our understanding of how the activation signal varies across motor tasks. Contemporary methods of quantifying the common input to motor neurons rely on compiling discrete action potentials into continuous time series, assuming the motor pool acts as a linear filter, and requiring signals to be of sufficient duration for frequency analysis. We introduce a space-state model in which the discharge activity of motor neurons is modeled as inhomogeneous Poisson processes and propose a method to quantify an abstract latent trajectory that represents the common input received by motor neurons. The approach also approximates the variation in synaptic noise in the common input signal. The model is validated with four data sets: a simulation of 120 motor units, a pair of integrate-and-fire neurons with a Renshaw cell providing inhibitory feedback, the discharge activity of 10 integrate-and-fire neurons, and the discharge times of concurrently active motor units during an isometric voluntary contraction. The simulations revealed that a latent state-space model is able to quantify the trajectory and variability of the common input signal across all four conditions. When compared with the cumulative spike train method of characterizing common input, the state-space approach was more sensitive to the details of the common input current and was less influenced by the duration of the signal. The state-space approach appears to be capable of detecting rather modest changes in common input signals across conditions.NEW & NOTEWORTHY We propose a state-space model that explicitly delineates a common input signal sent to motor neurons and the physiological noise inherent in synaptic signal transmission. This is the first application of a deterministic state-space model to represent the discharge characteristics of motor units during voluntary contractions.

Muscle Activity Map Reconstruction from High Density Surface EMG Signals With Missing Channels Using Image Inpainting and Surface Reconstruction Methods

OBJECTIVE

The aim of this study was to reconstruct low-quality High-density surface EMG (HDsEMG) signals, recorded with 2-D electrode arrays, using image inpainting and surface reconstruction methods.

METHODS

It is common that some fraction of the electrodes may provide low-quality signals. We used variety of image inpainting methods, based on partial differential equations (PDEs), and surface reconstruction methods to reconstruct the time-averaged or instantaneous muscle activity maps of those outlier channels. Two novel reconstruction algorithms were also proposed. HDsEMG signals were recorded from the biceps femoris and brachial biceps muscles during low-to-moderate-level isometric contractions, and some of the channels (5-25%) were randomly marked as outliers. The root-mean-square error (RMSE) between the original and reconstructed maps was then calculated.

RESULTS

Overall, the proposed Poisson and wave PDE outperformed the other methods (average RMSE 8.7 μV_rms ± 6.1 μV_rms and 7.5 μV_rms ± 5.9 μV_rms) for the time-averaged single-differential and monopolar map reconstruction, respectively. Biharmonic Spline, the discrete cosine transform, and the Poisson PDE outperformed the other methods for the instantaneous map reconstruction. The running time of the proposed Poisson and wave PDE methods, implemented using a Vectorization package, was 4.6 ± 5.7 ms and 0.6 ± 0.5 ms, respectively, for each signal epoch or time sample in each channel.

CONCLUSION

The proposed reconstruction algorithms could be promising new tools for reconstructing muscle activity maps in real-time applications.

SIGNIFICANCE

Proper reconstruction methods could recover the information of low-quality recorded channels in HDsEMG signals.

Comparison of methods for estimating motor unit firing rate time series from firing times

The central nervous system regulates recruitment and firing of motor units to modulate muscle tension. Estimation of the firing rate time series is typically performed by decomposing the electromyogram (EMG) into its constituent firing times, then lowpass filtering a constituent train of impulses. Little research has examined the performance of different estimation methods, particularly in the inevitable presence of decomposition errors. The study of electrocardiogram (ECG) and electroneurogram (ENG) firing rate time series presents a similar problem, and has applied novel simulation models and firing rate estimators. Herein, we adapted an ENG/ECG simulation model to generate realistic EMG firing times derived from known rates, and assessed various firing rate time series estimation methods. ENG/ECG-inspired rate estimation worked exceptionally well when EMG decomposition errors were absent, but degraded unacceptably with decomposition error rates of ⩾1%. Typical EMG decomposition error rates-even after expert manual review-are 3-5%. At realistic decomposition error rates, more traditional EMG smoothing approaches performed best, when optimal smoothing window durations were selected. This optimal window was often longer than the 400ms duration that is commonly used in the literature. The optimal duration decreased as the modulation frequency of firing rate increased, average firing rate increased and decomposition errors decreased. Examples of these rate estimation methods on physiologic data are also provided, demonstrating their influence on measures computed from the firing rate estimate.

Electromyography and Mechanomyography Signals During Swallowing in Healthy Adults and Head and Neck Cancer Survivors

Surface electromyography (sEMG) is used as an adjuvant to dysphagia therapy to demonstrate the activity of submental muscles during swallowing exercises. Mechanomyography (MMG) has been suggested as a potential superior alternative to sEMG; however, this advantage is not confirmed for signal acquired from submental muscles. This study compared the signal-to-noise ratio (SNR) obtained from sEMG and MMG sensors during swallowing tasks, in healthy participants and those with a history of head and neck cancer (HNC), a population with altered anatomy and a high incidence of dysphagia. Twenty-two healthy adults and 10 adults with a history of HNC participated in this study. sEMG and MMG signals were acquired during dry, thin liquid, effortful, and Mendelsohn maneuver swallows. SNR was compared between the two sensors using repeated measures ANOVAs and subsequent planned pairwise comparisons. Test-retest measures were collected on 20 % of participants. In healthy participants, MMG SNR was higher than that of sEMG for dry [t(21) = -3.02, p = 0.007] and thin liquid swallows [t(21) = -4.24, p < 0.001]. Although a significant difference for sensor was found in HNC participants F(1,9) = 5.54, p = 0.043, planned pairwise comparisons by task revealed no statistically significant difference between the two sensors. sEMG also showed much better test-retest reliability than MMG. Biofeedback provided as an adjuvant to dysphagia therapy in patients with HNC should employ sEMG technology, as this sensor type yielded better SNR and overall test-retest reliability. Poor MMG test-retest reliability was noted in both healthy and HNC participants and may have been related to differences in sensor application.

Progressive FastICA Peel-Off and Convolution Kernel Compensation Demonstrate High Agreement for High Density Surface EMG Decomposition

Decomposition of electromyograms (EMG) is a key approach to investigating motor unit plasticity. Various signal processing techniques have been developed for high density surface EMG decomposition, among which the convolution kernel compensation (CKC) has achieved high decomposition yield with extensive validation. Very recently, a progressive FastICA peel-off (PFP) framework has also been developed for high density surface EMG decomposition. In this study, the CKC and PFP methods were independently applied to decompose the same sets of high density surface EMG signals. Across 91 trials of 64-channel surface EMG signals recorded from the first dorsal interosseous (FDI) muscle of 9 neurologically intact subjects, there were a total of 1477 motor units identified from the two methods, including 969 common motor units. On average, 10.6 ± 4.3 common motor units were identified from each trial, which showed a very high matching rate of 97.85 ± 1.85% in their discharge instants. The high degree of agreement of common motor units from the CKC and the PFP processing provides supportive evidence of the decomposition accuracy for both methods. The different motor units obtained from each method also suggest that combination of the two methods may have the potential to further increase the decomposition yield.

Age-related changes in motor unit firing pattern of vastus lateralis muscle during low-moderate contraction

Age-related changes in motor unit activation properties remain unclear for locomotor muscles such as quadriceps muscles, although these muscles are preferentially atrophied with aging and play important roles in daily living movements. The present study investigated and compared detailed motor unit firing characteristics for the vastus lateralis muscle during isometric contraction at low to moderate force levels in the elderly and young. Fourteen healthy elderly men and 15 healthy young men performed isometric ramp-up contraction to 70 % of the maximal voluntary contractions (MVC) during knee extension. Multichannel surface electromyograms were recorded from the vastus lateralis muscle using a two-dimensional grid of 64 electrodes and decomposed with the convolution kernel compensation technique to extract individual motor units. Motor unit firing rates in the young were significantly higher (~+29.7 %) than in the elderly (p < 0.05). There were significant differences in firing rates among motor units with different recruitment thresholds at each force level in the young (p < 0.05) but not in the elderly (p > 0.05). Firing rates at 60 % of the MVC force level for the motor units recruited at <20 % of MVC were significantly correlated with MVC force in the elderly (r = 0.885, p < 0.0001) but not in the young (r = 0.127, p > 0.05). These results suggest that the motor unit firing rate in the vastus lateralis muscle is affected by aging and muscle strength in the elderly and/or age-related strength loss is related to motor unit firing/recruitment properties.

Preferential distribution of nociceptive input to motoneurons with muscle units in the cranial portion of the upper trapezius muscle

Pain is associated with changes in the neural drive to muscles. For the upper trapezius muscle, surface electromyography (EMG) recordings have indicated that acute noxious stimulation in either the cranial or the caudal region of the muscle leads to a relative decrease in muscle activity in the cranial region. It is, however, not known if this adaption reflects different recruitment thresholds of the upper trapezius motor units in the cranial and caudal region or a nonuniform nociceptive input to the motor units of both regions. This study investigated these potential mechanisms by direct motor unit identification. Motor unit activity was investigated with high-density surface EMG signals recorded from the upper trapezius muscle of 12 healthy volunteers during baseline, control (intramuscular injection of isotonic saline), and painful (hypertonic saline) conditions. The EMG was decomposed into individual motor unit spike trains. Motor unit discharge rates decreased significantly from control to pain conditions by 4.0 ± 3.6 pulses/s (pps) in the cranial region but not in the caudal region (1.4 ± 2.8 pps; not significant). These changes were compatible with variations in the synaptic input to the motoneurons of the two regions. These adjustments were observed, irrespective of the location of noxious stimulation. These results strongly indicate that the nociceptive synaptic input is distributed in a nonuniform way across regions of the upper trapezius muscle.

Motor Neuron Pools of Synergistic Thigh Muscles Share Most of Their Synaptic Input

Neural control of synergist muscles is not well understood. Presumably, each muscle in a synergistic group receives some unique neural drive and some drive that is also shared in common with other muscles in the group. In this investigation, we sought to characterize the strength, frequency spectrum, and force dependence of the neural drive to the human vastus lateralis and vastus medialis muscles during the production of isometric knee extension forces at 10 and 30% of maximum voluntary effort. High-density surface electromyography recordings were decomposed into motor unit action potentials to examine the neural drive to each muscle. Motor unit coherence analysis was used to characterize the total neural drive to each muscle and the drive shared between muscles. Using a novel approach based on partial coherence analysis, we were also able to study specifically the neural drive unique to each muscle (not shared). The results showed that the majority of neural drive to the vasti muscles was a cross-muscle drive characterized by a force-dependent strength and bandwidth. Muscle-specific neural drive was at low frequencies (<5 Hz) and relatively weak. Frequencies of neural drive associated with afferent feedback (6-12 Hz) and with descending cortical input (∼20 Hz) were almost entirely shared by the two muscles, whereas low-frequency (<5 Hz) drive comprised shared (primary) and muscle-specific (secondary) components. This study is the first to directly investigate the extent of shared versus independent control of synergist muscles at the motor neuron level.

SIGNIFICANCE STATEMENT

Precisely how the nervous system coordinates the activity of synergist muscles is not well understood. One possibility is that muscles of a synergy share a common neural drive. In this study, we directly compared the relative strength of shared versus independent neural drive to synergistically activated thigh muscles in humans. The results of this analysis support the notion that synergistically activated muscles share most of their neural drive. Scientifically, this study addressed an important gap in our current understanding of how neural drive is delivered to synergist muscles. We have also demonstrated the feasibility of a novel approach to the study of muscle synergies based on partial coherence analysis of motor unit activity.