High-yield decomposition of surface EMG signals

The effects of resistance training to near volitional failure on motor unit recruitment during neuromuscular fatigue

Background

It is unclear whether chronically training close to volitional failure influences motor unit recruitment strategies during fatigue.

Purpose

We compared resistance training to near volitional failure vs. non-failure on individual motor unit action potential amplitude (MUAP) and surface electromyographic excitation (sEMG) during fatiguing contractions.

Methods

Nineteen resistance-trained adults (11 males, 8 females) underwent 5 weeks (3×/week) of either low repetitions-in-reserve (RIR; 0-1 RIR) or high RIR training (4-6 RIR). Before and after the intervention, participants performed isometric contractions of the knee extensors at 30% of maximal peak torque until exhaustion while vastus lateralis sEMG signals were recorded and later decomposed. MUAP and sEMG excitation for the vastus lateralis were quantified at the beginning, middle, and end of the fatigue assessment.

Results

Both training groups improved time-to-task failure (mean change = 43.3 s, 24.0%), with no significant differences between low and high RIR training groups (low RIR = 28.7%, high RIR = 19.4%). Our fatigue assessment revealed reduced isometric torque steadiness and increased MUAP amplitude and sEMG excitation during the fatiguing task, but these changes were consistent between groups.

Conclusion

Both low and high RIR training improved time-to-task failure, but resulted in comparable motor unit recruitment during fatiguing contractions. Our findings indicate that both low and high RIR training can be used to enhance fatiguability among previously resistance-trained adults.

Motor unit firing rates increase in prepubescent youth following linear periodization resistance exercise training

PURPOSE

The purpose was to examine the effects of 8-weeks (3 days/week) of linear periodization resistance exercise training (RET) on neuromuscular function in prepubescent youth.

METHODS

Twenty-five healthy prepubescent youth (11 males, 14 females, age = 9.1 ± 0.8 years) completed the RET (n = 17) or served as controls (CON, n = 8). Isometric maximal voluntary contractions (MVCs) and trapezoidal submaximal contractions at 35 and 60% MVC of the right leg extensors were performed with surface electromyography (EMG) recorded from the leg extensors [vastus lateralis (VL), rectus femoris, and vastus medialis] and flexors (biceps femoris and semitendinosus). EMG amplitude of the leg extensors and flexors were calculated during the MVCs. Motor unit (MU) action potential trains were decomposed from the surface EMG of the VL for the 35 and 60% MVCs. MU firing rates and action potential amplitudes were regressed against recruitment threshold with the y-intercepts and slopes calculated for each contraction. Total leg extensor muscle cross-sectional area (CSA) was collected using ultrasound images. ANOVA models were used to examine potential differences.

RESULTS

Isometric strength increased post-RET (P = 0.006) with no changes in leg extensor and flexor EMG amplitude. Furthermore, there were no changes in total CSA or the MU action potential amplitude vs. recruitment threshold relationships. However, there were increases in the firing rates of the higher-threshold MUs post-RET as indicated with greater y-intercepts (P = 0.003) from the 60% MVC and less negative slope (P = 0.004) of the firing rates vs. recruitment threshold relationships at 35% MVC.

CONCLUSIONS

MU adaptations contribute to strength increases following RET in prepubescent youth.

Three Levels of Neural Control Contributing to Performance-stabilizing Synergies in Multi-finger Tasks

We tested a hypothesis on force-stabilizing synergies during four-finger accurate force production at three levels: (1) The level of the reciprocal and coactivation commands, estimated as the referent coordinate and apparent stiffness of all four fingers combined; (2) The level of individual finger forces; and (3) The level of firing of individual motor units (MU). Young, healthy participants performed accurate four-finger force production at a comfortable, non-fatiguing level under visual feedback on the total force magnitude. Mechanical reflections of the reciprocal and coactivation commands were estimated using small, smooth finger perturbations applied by the "inverse piano" device. Firing frequencies of motor units in the flexor digitorum superficialis (FDS) and extensor digitorum communis (EDC) were estimated using surface recording. Principal component analysis was used to identify robust MU groups (MU-modes) with parallel changes in the firing frequency. The framework of the uncontrolled manifold hypothesis was used to compute synergy indices in the spaces of referent coordinate and apparent stiffness, finger forces, and MU-mode magnitudes. Force-stabilizing synergies were seen at all three levels. They were present in the MU-mode spaces defined for MUs in FDS, in EDC, and pooled over both muscles. No effects of hand dominance were seen. The synergy indices defined at different levels of analysis showed no correlations across the participants. The findings are interpreted within the theory of control with spatial referent coordinates for the effectors. We conclude that force stabilization gets contributions from three levels of neural control, likely associated with cortical, subcortical, and spinal circuitry.

Differential training benefits and motor unit remodeling in wrist force precision tasks following high and low load blood flow restriction exercises under volume-matched conditions

BACKGROUND

Blood flow restriction (BFR) resistance training has demonstrated efficacy in promoting strength gains beneficial for rehabilitation. Yet, the distinct functional advantages of BFR strength training using high-load and low-load protocols remain unclear. This study explored the behavioral and neurophysiological mechanisms that explain the differing effects after volume-matched high-load and low-load BFR training.

METHODS

Twenty-eight healthy participants were randomly assigned to the high-load blood flow restriction (BFR-HL, n = 14) and low-load blood flow restriction (BFR-LL, n = 14) groups. They underwent 3 weeks of BFR training for isometric wrist extension at intensities of 25% or 75% of maximal voluntary contraction (MVC) with matched training volume. Pre- and post-tests included MVC and trapezoidal force-tracking tests (0-75%-0% MVC) with multi-channel surface electromyography (EMG) from the extensor digitorum.

RESULTS

The BFR-HL group exhibited a greater strength gain than that of the BFR-LL group after training (BFR_HL: 26.96 ± 16.33% vs. BFR_LL: 11.16 ± 15.34%)(p = 0.020). However, only the BFR-LL group showed improvement in force steadiness for tracking performance in the post-test (p = 0.004), indicated by a smaller normalized change in force fluctuations compared to the BFR-HL group (p = 0.048). After training, the BFR-HL group activated motor units (MUs) with higher recruitment thresholds (p < 0.001) and longer inter-spike intervals (p = 0.002), contrary to the BFR-LL group, who activated MUs with lower recruitment thresholds (p < 0.001) and shorter inter-spike intervals (p < 0.001) during force-tracking. The discharge variability (p < 0.003) and common drive index (p < 0.002) of MUs were consistently reduced with training for the two groups.

CONCLUSIONS

BFR-HL training led to greater strength gains, while BFR-LL training better improved force precision control due to activation of MUs with lower recruitment thresholds and higher discharge rates.

The Decomposition Method of Surface Electromyographic Signals: A Novel Approach for Motor Unit Activity and Recruitment Description

This review aims to describe a novel method in the field of electromyography (EMG), established and improved upon in the last three decades that is able to observe specific parameters of muscle units (MUs). This concept is called the decomposition method, based on its ability to decompose a surface EMG signal to describe muscle activity on the level of individual muscle units in contrast to the level of the whole muscle, as is customary for regular surface electromyography. We provide a brief overview of its history, constituent parts regarding both hardware and software and possible applications. We also acknowledge the state of the research, regarding the background of the decomposition algorithm, the main software component responsible for identifying individual motor units and their parameters. As a result of the ability to describe the behavior of individual motor units during muscle contractions, key concepts in neuromuscular physiology have been put forward, pertaining to the hierarchy of MUs during their recruitment. Together with the recent application for cyclic contractions and gait, the decomposition method is beginning to open up wider possibilities of enquiry.

Influence of Blood Flow Restriction on Neuromuscular Function and Fatigue During Forearm Flexion in Men

ABSTRACT

Montgomery, TR Jr, Olmos, A, Sears, KN, Succi, PJ, Hammer, SM, Bergstrom, HC, Hill, EC, Trevino, MA, and Dinyer-McNeely, TK. Influence of blood flow restriction on neuromuscular function and fatigue during forearm flexion in men. J Strength Cond Res 38(7): e349-e358, 2024-To determine the effects of blood flow restriction (BFR) on the mean firing rate (MFR) and motor unit action potential amplitude (MUAPAMP) vs. recruitment threshold (RT) relationships during fatiguing isometric elbow flexions. Ten men (24.5 ± 4.0 years) performed isometric trapezoidal contractions at 50% maximum voluntary contraction to task failure with or without BFR, on 2 separate days. For BFR, a cuff was inflated to 60% of the pressure required for full brachial artery occlusion at rest. During both visits, surface electromyography was recorded from the biceps brachii of the dominant limb and the signal was decomposed. A paired-samples t test was used to determine the number of repetitions completed between BFR and CON. ANOVAs (repetition [first, last] × condition [BFR, CON]) were used to determine differences in MFR vs. RT and MUAPAMP vs. RT relationships. Subjects completed more repetitions during CON (12 ± 4) than BFR (9 ± 2; p = 0.012). There was no significant interaction (p > 0.05) between the slopes and y-intercepts during the repetition × condition interaction for MUAPAMP vs. MFR. However, there was a main effect of repetition for the slopes of the MUAPAMP vs. RT (p = 0.041) but not the y-intercept (p = 0.964). Post hoc analysis (collapsed across condition) indicated that the slopes of the MUAPAMP vs. RT during the first repetition was less than the last repetition (first: 0.022 ± 0.003 mv/%MVC; last: 0.028 ± 0.004 mv/%MVC; p = 0.041). Blood flow restriction resulted in the same amount of higher threshold MU recruitment in approximately 75% of the repetitions. Furthermore, there was no change in MFR for either condition, even when taken to task failure. Thus, BFR training may create similar MU responses with less total work completed than training without BFR.

NeuroMechanics: Electrophysiological and computational methods to accurately estimate the neural drive to muscles in humans in vivo

The ultimate neural signal for muscle control is the neural drive sent from the spinal cord to muscles. This neural signal comprises the ensemble of action potentials discharged by the active spinal motoneurons, which is transmitted to the innervated muscle fibres to generate forces. Accurately estimating the neural drive to muscles in humans in vivo is challenging since it requires the identification of the activity of a sample of motor units (MUs) that is representative of the active MU population. Current electrophysiological recordings usually fail in this task by identifying small MU samples with over-representation of higher-threshold with respect to lower-threshold MUs. Here, we describe recent advances in electrophysiological methods that allow the identification of more representative samples of greater numbers of MUs than previously possible. This is obtained with large and very dense arrays of electromyographic electrodes. Moreover, recently developed computational methods of data augmentation further extend experimental MU samples to infer the activity of the full MU pool. In conclusion, the combination of new electrode technologies and computational modelling allows for an accurate estimate of the neural drive to muscles and opens new perspectives in the study of the neural control of movement and in neural interfacing.

Decomposition strategy for surface EMG with few channels: a simulation study

Objective.In the specific use of electromyogram (EMG) driven prosthetics, the user's disability reduces the space available for the electrode array. We propose a framework for EMG decomposition adapted to the condition of a few channels (less than 30 observations), which can elevate the potential of prosthetics in terms of cost and applicability.Approach.The new framework contains a peel-off approach, a refining strategy for motor unit (MU) spike train and MU action potential and a re-subtracting strategy to adapt the framework to few channels environments. Simulated EMG signals were generated to test the framework. In addition, we quantify and analyze the effect of strategies used in the framework.Main results.The results show that the new algorithm has an average improvement of 19.97% in the number of MUs identified compared to the control algorithm. Quantitative analysis of the usage strategies shows that the re-subtracting and refining strategies can effectively improve the performance of the framework under the condition of few channels.Significance.These prove that the new framework can be applied to few channel conditions, providing a optimization space for neural interface design in cost and user adaptation.

Prediction of Dexterous Finger Forces With Forearm Rotation Using Motoneuron Discharges

Motor unit (MU) discharge information obtained via electromyogram (EMG) decomposition can be used to decode dexterous multi-finger movement intention for neural-machine interfaces (NMI). However, the variation of the motor unit action potential (MUAP) shape resulted from forearm rotation leads to the decreased performance of EMG decomposition, especially under the real-time condition and then the degradation of motion decoding accuracy. The object of this study was to develop a method to realize the accurate extraction of MU discharge information across forearm pronated/supinated positions in the real-time condition for dexterous multi-finger force prediction. The FastICA-based EMG decomposition technique was used and the proposed method obtained multiple separation vectors for each MU at different forearm positions in the initialization phase. Under the real-time condition, the MU discharge information was extracted adaptively using the separation vector extracted at the nearest forearm position. As comparison, the previous method that utilized a single constant separation vector to extract MU discharges across forearm positions and the conventional method that utilized the EMG amplitude information were also performed. The results showed that the proposed method obtained a significantly better performance compared with the other two methods, manifested in a larger coefficient of determination ( [Formula: see text] and a smaller root mean squared error (RMSE) between the predicted and recorded force. Our results demonstrated the feasibility and the effectiveness of the proposed method to extract MU discharge information during forearm rotation for dexterous force prediction under the real-time conditions. Further development of the proposed method could potentially promote the application of the EMG decomposition technique for continuous dexterous motion decoding in a realistic NMI application scenario.

Intrinsic motoneuron properties in typical human development

Motoneuron properties and their firing patterns undergo significant changes throughout development and in response to neuromodulators such as serotonin. Here, we examined the age-related development of self-sustained firing and general excitability of tibialis anterior motoneurons in a young development (7-17 years), young adult (18-28 years) and adult (32-53 years) group, as well as in a separate group of participants taking selective serotonin reuptake inhibitors (SSRIs, aged 11-28 years). Self-sustained firing, as measured by ΔF, was larger in the young development (∼5.8 Hz, n = 20) compared to the young adult (∼4.9 Hz, n = 13) and adult (∼4.8 Hz, n = 8) groups, consistent with a developmental decrease in self-sustained firing mediated by persistent inward currents (PIC). ΔF was also larger in participants taking SSRIs (∼6.5 Hz, n = 9) compared to their age-matched controls (∼5.3 Hz, n = 26), consistent with increased levels of spinal serotonin facilitating the motoneuron PIC. Participants in the young development and SSRI groups also had higher firing rates and a steeper acceleration in initial firing rates (secondary ranges), consistent with the PIC producing a steeper acceleration in membrane depolarization at the onset of motoneuron firing. In summary, both the young development and SSRI groups exhibited increased intrinsic motoneuron excitability compared to the adults, which, in the young development group, was also associated with a larger unsteadiness in the dorsiflexion torque profiles. We propose several intrinsic and extrinsic factors that affect both motoneuron PICs and cell discharge which vary during development, with a time course similar to the changes in motoneuron firing behaviour observed in the present study. KEY POINTS: Neurons in the spinal cord that activate muscles in the limbs (motoneurons) undergo increases in excitability shortly after birth to help animals stand and walk. We examined whether the excitability of human ankle flexor motoneurons also continues to change from child to adulthood by recording the activity of the muscle fibres they innervate. Motoneurons in children and adolescents aged 7-17 years (young development group) had higher signatures of excitability that included faster firing rates and more self-sustained activity compared to adults aged ≥18 years. Participants aged 11-28 years of age taking serotonin reuptake inhibitors had the highest measures of motoneuron excitability compared to their age-matched controls. The young development group also had more unstable contractions, which might partly be related to the high excitability of the motoneurons.

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

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

Effect of Warm-Up Exercise on Functional Regulation of Motor Unit Activation during Isometric Torque Production

In this study, we tested several hypotheses related to changes in motor unit activation patterns after warm-up exercise. Fifteen healthy young men participated in the experiment and the main task was to produce voluntary torque through the elbow joint under the isometric condition. The experimental conditions consisted of two directions of torque, including flexion and extension, at two joint angles, 10° and 90°. Participants were asked to increase the joint torque to the maximal level at a rate of 10% of the maximum voluntary torque. The warm-up protocol followed the ACSM guidelines, which increased body temperature by approximately 1.5°C. Decomposition electromyography electrodes, capable of extracting multiple motor unit action potentials from surface signals, were placed on the biceps and triceps brachii muscles, and joint torque was measured on the dynamometer. The mean firing rate and the recruitment threshold of the decomposed motor units were quantified. In addition, a single motor unit activity from the spike train was quantified for each of five selected motor units. The magnitude of joint torque increased with the warm-up exercise for all the experimental conditions. The results of the motor unit analyses showed a positive and beneficial effect of the warm-up exercise, with an increase in both the mean firing rate and the recruitment threshold by about 56% and 33%, respectively, particularly in the agonist muscle. Power spectral density in the gamma band, which is thought to be the dominant voluntary activity, was also increased by the warm-up exercise only in the high threshold motor units.

Neuromuscular behaviour in the first dorsal interosseus following mental fatigue

We examined sex-specific changes to neuromuscular function in response to mental fatigue. Twenty-five young, healthy adults (13 F, 12 M) performed a mentally fatiguing task and control condition for 30 min on two separate days. Neuromuscular function was assessed in the first dorsal interosseous before and after each condition. Reaction time decreased after the mentally fatiguing task (P < 0.001, η2  = 0.47). Males and females reported higher levels of subjective fatigue after the mentally fatiguing task (P < 0.02, η2  = 0.07). Motor unit firing rate increased over time at 10% maximal voluntary contraction (MVC; P < 0.04, η2  = 0.16), and decreased over time at 50% MVC (P < 0.01, η2  = 0.14); however, this was not unique to either sex. During a variable force contraction, error decreased in females over time and increased in males (P < 0.05, η2  = 0.13), although changes were not unique to mental fatigue. Physiological function of the neuromuscular system was not specifically affected by mental fatigue in males or females.

Enhanced Dynamic Surface EMG Decomposition Using the Non-Negative Matrix Factorization and Three-Dimensional Motor Unit Localization

OBJECTIVE

Surface electromyography (sEMG) signal decomposition is of great importance in examining neuromuscular diseases and neuromuscular research, especially dynamic sEMG decomposition is even more technically challenging.

METHODS

A novel two-step sEMG decomposition approach was developed. The linear minimum mean square error estimation was first employed to extract estimated firing trains (EFTs) from the eigenvector matrices constructed using the non-negative matrix factorization (NMF). The firing instants of each EFT were then classified into motor units (MUs) according to their specific three-dimensional (3D) space position. The performance of the proposed approach was evaluated using simulated and experimentally recorded sEMG.

RESULTS

The simulation results demonstrated that the proposed approach can reconstruct MUAPTs with true positive rates of 89.12 ± 2.71%, 94.34 ± 1.85% and 95.45 ± 2.11% at signal-to-noise ratios of 10, 20, and 30 dB, respectively. The experimental results also demonstrated a high decomposition accuracy of 90.13 ± 1.31% in the two-source evaluation, and a high accuracy of 91.86 ± 1.14% in decompose-synthesize-decompose- compare evaluation.

CONCLUSIONS

The adoption of NMF reduces the dimension of random pattern under the restriction of non-negativity, as well as keeps the information unchanged as much as possible. The 3D space information of MUs enhances the classification accuracy by tackling the issue of relative movements between MUs and electrodes during dynamic contractions. The accuracy achieved in this study demonstrates the good performance and reliability of the proposed decomposition algorithm in dynamic surface EMG decomposition.

SIGNIFICANCE

The spatiotemporal information is applied to the dynamic surface EMG decomposition.

Tutorial: Analysis of central and peripheral motor unit properties from decomposed High-Density surface EMG signals with openhdemg

High-Density surface Electromyography (HD-sEMG) is the most established technique for the non-invasive analysis of single motor unit (MU) activity in humans. It provides the possibility to study the central properties (e.g., discharge rate) of large populations of MUs by analysis of their firing pattern. Additionally, by spike-triggered averaging, peripheral properties such as MUs conduction velocity can be estimated over adjacent regions of the muscles and single MUs can be tracked across different recording sessions. In this tutorial, we guide the reader through the investigation of MUs properties from decomposed HD-sEMG recordings by providing both the theoretical knowledge and practical tools necessary to perform the analyses. The practical application of this tutorial is based on openhdemg, a free and open-source community-based framework for the automated analysis of MUs properties built on Python 3 and composed of different modules for HD-sEMG data handling, visualisation, editing, and analysis. openhdemg is interfaceable with most of the available recording software, equipment or decomposition techniques, and all the built-in functions are easily adaptable to different experimental needs. The framework also includes a graphical user interface which enables users with limited coding skills to perform a robust and reliable analysis of MUs properties without coding.

Motor unit activity and synaptic inputs to motoneurons in the caudal part of the injured spinal cord

Spinal cord injury (SCI) disrupts neuronal function below the lesion epicenter, causing disuse muscle atrophy. We investigated motor unit (MU) activity and synaptic inputs to motoneurons in the caudal region of the injured spinal cord. Participants with C4-C7 cervical injuries were studied. The extensor digitorum communis (EDC) muscle, which is mainly innervated by C8, was assessed for disuse muscle atrophy. Using advanced electromyography and signal-processing techniques, we examined the concurrent activation of a substantial population of MUs during force-tracking tasks. We found that in participants with SCI (n = 9), both MU discharge rates and the amplitudes of MU action potentials were significantly lower than in controls (n = 9). After SCI, MUs were recruited in a limited force range as the strength of muscle contractions increased, implying a disruption in the orderly MU recruitment pattern. Coherence analysis revealed reduced synaptic inputs to motoneurons in the delta band (0.5-5 Hz) for participants with SCI, suggesting diminished common synaptic inputs to the EDC muscle. In addition, participants with SCI exhibited greater muscle force variability. Using principal component analysis on low-frequency MU discharge rates, we found that the first common component (FCC) captured the most discharge variability in participants with SCI. The coefficients of variation (CV) of the FCC correlated with force signal CVs, suggesting force variability mainly results from common synaptic inputs to the EDC muscle after SCI. These results advance our understanding of the neurophysiology of disuse muscle atrophy in human SCI, paving the way for therapeutic interventions to restore muscle function.NEW & NOTEWORTHY This study analyzed motor unit (MU) function below the lesion epicenter in patients with spinal cord injury (SCI). We found reduced MU discharge rates and action potential amplitudes in participants with SCI compared with controls. The strength of common synaptic inputs to motoneurons was reduced in patients with SCI, with increased force variability primarily due to low-frequency oscillations of common inputs. This study enhances understanding of neurophysiological and behavioral changes in disuse muscle atrophy post-SCI.

Two classes of action-stabilizing synergies reflecting spinal and supraspinal circuitry

We explored force-stabilizing synergies during accurate four-finger constant force production tasks in spaces of finger modes (commands to fingers computed to account for the finger interdependence) and of motor unit (MU) firing frequencies. The main specific hypothesis was that the multifinger synergies would disappear during unintentional force drifts without visual feedback on the force magnitude, whereas MU-based synergies would be robust to such drifts. Healthy participants performed four-finger accurate cyclical force production trials followed by trials of constant force production. Individual MUs were identified in the flexor digitorum superficialis (FDS) and extensor digitorum communis (EDC). Principal component analysis was applied to motor unit frequencies to identify robust MU groups (MU-modes) with parallel scaling of the firing frequencies in FDS, in EDC, and the combined MUs of FDS + EDC. The framework of the uncontrolled manifold hypothesis was used to quantify force-stabilizing synergies when visual feedback on the force magnitude was available and 15 s after turning the visual feedback off. Removing visual feedback led to a force drift toward lower magnitudes, accompanied by the disappearance of multifinger synergies. In contrast, MU-mode synergies were minimally affected by removing visual feedback off and continued to be robust for the FDS and for the EDC, while being absent for the (FDS + EDC) analysis. We interpret the findings within the theory of hierarchical control of action with spatial referent coordinates. The qualitatively different behavior of the multifinger and MU-mode-based synergies likely reflects the difference in the involved neural circuitry, supraspinal for the former and spinal for the latter.NEW & NOTEWORTHY Two types of synergies, in the space of commands to individual fingers and in the space of motor unit groups, show qualitatively different behaviors during accurate multifinger force-production tasks. After removing visual feedback, finger force synergies disappear, whereas motor unit-based synergies persist. These results point at different neural circuitry involved in these two basic classes of synergies: supraspinal for multieffector synergies, and spinal for motor unit-based synergies.

Modified motor unit properties in residual muscle following transtibial amputation

Objective.Neural signals in residual muscles of amputated limbs are frequently decoded to control powered prostheses. Yet myoelectric controllers assume muscle activities of residual muscles are similar to that of intact muscles. This study sought to understand potential changes to motor unit (MU) properties after limb amputation.Approach.Six people with unilateral transtibial amputation were recruited. Surface electromyogram (EMG) of residual and intacttibialis anterior(TA) andgastrocnemius(GA) muscles were recorded while subjects traced profiles targeting up to 20% and 35% of maximum activation for each muscle (isometric for intact limbs). EMG was decomposed into groups of MU spike trains. MU recruitment thresholds, action potential amplitudes (MU size), and firing rates were correlated to model Henneman's size principle, the onion-skin phenomenon, and rate-size associations. Organization (correlation) and modulation (rates of change) of relations were compared between intact and residual muscles.Main results.The residual TA exhibited significantly lower correlation and flatter slopes in the size principle and onion-skin, and each outcome covaried between the MU relations. The residual GA was unaffected for most subjects. Subjects trained prior with myoelectric prostheses had minimally affected slopes in the TA. Rate-size association correlations were preserved, but both residual muscles exhibited flatter decay rates.Significance.We showed peripheral neuromuscular damage also leads to spinal-level functional reorganizations. Our findings suggest models of MU recruitment and discharge patterns for residual muscle EMG generation need reparameterization to account for disturbances observed. In the future, tracking MU pool adaptations may also provide a biomarker of neuromuscular control to aid training with myoelectric prostheses.

Neuromuscular responses to combined neuromuscular electrical stimulation and motor control exercises in a patient with recurrent low back pain: A single subject research report

BACKGROUND

Previous studies have demonstrated changes in lumbar multifidus muscle (LM) contractility after motor control exercises (MCE), and it has been hypothesized that adding neuromuscular electrical stimulation (NMES) may help to re-activate motor units.

OBJECTIVE

To present the effects of combined NMES and MCE on LM contractility, spatial and temporal motor unit recruitment, and movement control in a patient with recurrent low back pain (rLBP).

METHODS

Motion tracking system was used to measure quality of movement (smoothness) during an active forward bend, while ultrasound imaging and decomposition electromyography were used to measure the LM contractility and motor unit recruitment during the Sorensen test. These data were collected pre and post intervention. Perceived improvement was also recorded.

RESULTS

Improved movement smoothness post intervention was found, with increases in LM contractility from 68.1% to 97.7%, and from 74.2% to 86.7% on the right and left sides, respectively. Number of motor unit increased from 14 to 18 units, while mean firing rate decreased from 10.9 to 7.1 pulses/second post intervention. The patient also reported a perceived improvement of +2 on the Global Rating of Change (GROC). However, this change was not greater than +3 to be considered as minimal clinically important difference.

CONCLUSION

These findings indicate improvements in movement control, LM contractility, and changes in spatial and temporal motor unit recruitment in the study patient, suggesting the potential clinical utility and the need for further research on combined NMES and MCE in the treatment of patients with rLBP.

Ankle Torque Estimation With Motor Unit Discharges in Residual Muscles Following Lower-Limb Amputation

There has been increased interest in using residual muscle activity for neural control of powered lower-limb prostheses. However, only surface electromyography (EMG)-based decoders have been investigated. This study aims to investigate the potential of using motor unit (MU)-based decoding methods as an alternative to EMG-based intent recognition for ankle torque estimation. Eight people without amputation (NON) and seven people with amputation (AMP) participated in the experiments. Subjects conducted isometric dorsi- and plantarflexion with their intact limb by tracing desired muscle activity of the tibialis anterior (TA) and gastrocnemius (GA) while ankle torque was recorded. To match phantom limb and intact limb activity, AMP mirrored muscle activation with their residual TA and GA. We compared neuromuscular decoders (linear regression) for ankle joint torque estimation based on 1) EMG amplitude (aEMG), 2) MU firing frequencies representing neural drive (ND), and 3) MU firings convolved with modeled twitch forces (MUDrive). In addition, sensitivity analysis and dimensionality reduction of optimization were performed on the MUDrive method to further improve its practical value. Our results suggest MUDrive significantly outperforms (lower root-mean-square error) EMG and ND methods in muscles of NON, as well as both intact and residual muscles of AMP. Reducing the number of optimized MUDrive parameters degraded performance. Even so, optimization computational time was reduced and MUDrive still outperformed aEMG. Our outcomes indicate integrating MU discharges with modeled biomechanical outputs may provide a more accurate torque control signal than direct EMG control of assistive, lower-limb devices, such as exoskeletons and powered prostheses.

Differential impact on motor unit characteristics across severities of adult spinal muscular atrophy

OBJECTIVE

To test the hypotheses that decomposition electromyography (dEMG) motor unit action potential (MUAP) amplitude and firing rate are altered in SMA; dEMG parameters are associated with strength and function; dEMG parameters are correlated with traditional electrophysiological assessments.

METHODS

Ambulatory and non-ambulatory adults with SMA on nusinersen and healthy controls were enrolled. MUAPs were decomposed from multielectrode surface recordings during 30-s maximum contraction of the abductor digiti minimi (ADM). Isometric strength, upper limb function, patient-reported function, and standard electrophysiologic measures of the ADM (compound muscle action potential [CMAP], single motor unit potential [SMUP], motor unit number estimation [MUNE]) were collected.

RESULTS

dEMG MUAP amplitudes were higher in ambulatory versus control and non-ambulatory groups and were higher in controls versus non-ambulatory SMA. In contrast, dEMG firing rates were higher in ambulatory versus non-ambulatory and control groups but similar between non-ambulatory and control. dEMG parameters showed moderate to strong positive correlation with strength and function whereas CMAP and MUNE better correlated with function than strength. SMUP did not correlate with strength, function, or dEMG MUAP amplitude. dEMG parameters show overall good test-retest reliability.

INTERPRETATION

dEMG provided reliable, noninvasive measure of MUAP amplitude size and firing rate and revealed divergent patterns across disease severity in adults with SMA. Firing rate enhancement, as seen in milder SMA, may provide a therapeutic avenue for improving function in more severe SMA, where firing rates appear preserved. MUAP amplitude size and firing rate, quantified with dEMG, may be promising monitoring biomarker candidates for noninvasive assessment of SMA.

Cumulative Spike Train Estimation for Muscle Excitation Assessment From Surface EMG Using Spatial Spike Detection

Estimating cumulative spike train (CST) of motor units (MUs) from surface electromyography (sEMG) is essential for the effective control of neural interfaces. However, the limited accuracy of existing estimation methods greatly hinders the further development of neural interface. This paper proposes a simple but effective approach for identifying CST based on spatial spike detection from high-density sEMG. Specifically, we use a spatial sliding window to detect spikes according to the spatial propagation characteristics of the motor unit action potential, focusing on the spikes of activated MUs in a local area rather than those of a specific MU. We validated the effectiveness of our proposed method through an experiment involving wrist flexion/extension and pronation/supination, comparing it with a recognized CST estimation method and an MU decomposition based method. The results demonstrated that the proposed method obtained higher accuracy on multi-DoF wrist torque estimation leveraging the estimated CST compared to the other three methods. On average, the correlation coefficient (R) and the normalized root mean square error (nRMSE) between the estimation results and recorded force were 0.96 ± 0.03 and 10.1% ± 3.7%, respectively. Moreover, there was an extremely high interpretive extent between the CSTs of proposed method and the MU decomposition method. The outcomes reveal the superiority of the proposed method in identifying CSTs and can provide promising driven signals for neural interface.

Effects of fatigue on intramuscle force-stabilizing synergies

We applied the recently introduced concept of intramuscle synergies in spaces of motor units (MUs) to quantify indexes of such synergies in the tibialis anterior during ankle dorsiflexion force production tasks and their changes with fatigue. We hypothesized that MUs would be organized into robust groups (MU modes), which would covary across trials to stabilize force magnitude, and the indexes of such synergies would drop under fatigue. Healthy, young subjects (n = 15; 8 females) produced cyclical, isometric dorsiflexion forces while surface electromyography was used to identify action potentials of individual MUs. Principal component analysis was used to define MU modes. The framework of the uncontrolled manifold (UCM) was used to analyze intercycle variance and compute the synergy index, ΔVZ. Cyclical force production tasks were repeated after a nonfatiguing exercise (control) and a fatiguing exercise. Across subjects, fatigue led, on average, to a 43% drop in maximal force and fewer identified MUs per subject (29.6 ± 2.1 vs. 32.4 ± 2.1). The first two MU modes accounted for 81.2 ± 0.08% of variance across conditions. Force-stabilizing synergies were present across all conditions and were diminished after fatiguing exercise (1.49 ± 0.40) but not control exercise (1.76 ± 0.75). Decreased stability after fatigue was caused by an increase in the amount of variance orthogonal to the UCM. These findings contrast with earlier studies of multieffector synergies demonstrating increased synergy index under fatigue. We interpret the results as reflections of a drop in the gain of spinal reflex loops under fatigue. The findings corroborate an earlier hypothesis on the spinal nature of intramuscle synergies.NEW & NOTEWORTHY Across multielement force production tasks, fatigue of an element leads to increased indexes of force stability (synergy indexes). Here, however, we show that groups of motor units in the tibialis anterior show decreased indexes of force-stabilizing synergies after fatiguing exercise. These findings align intramuscle synergies with spinal mechanisms, in contrast to the supraspinal control of multimuscle synergies.

Ingersoll C, E. Norte G. Neural drive and motor unit characteristics after anterior cruciate ligament reconstruction: implications for quadriceps weakness

Purpose

The purpose of this investigation was to compare the quality of neural drive and recruited quadriceps motor units' (MU) action potential amplitude (MUAPAMP) and discharge rate (mean firing rate (MFR)) relative to recruitment threshold (RT) between individuals with anterior cruciate ligament reconstruction (ACLR) and controls.

Methods

Fourteen individuals with ACLR and 13 matched controls performed trapezoidal knee extensor contractions at 30%, 50%, 70%, and 100% of their maximal voluntary isometric contraction (MVIC). Decomposition electromyography (dEMG) and torque were recorded concurrently. The Hoffmann reflex (H-reflex) and central activation ratio (CAR) were acquired bilaterally to detail the proportion of MU pool available and volitionally activated. We examined MUAPAMP-RT and MFR-RT relationships with linear regression and extracted the regression line slope, y-intercept, and RT range for each contraction. Linear mixed effect modelling used to analyze the effect of group and limb on regression line slope and RT range.

Results

Individuals with ACLR demonstrated lower MVIC torque in the involved limb compared to uninvolved limb. There were no differences in H-reflex or CAR between groups or limbs. The ACLR involved limb demonstrated smaller mass-normalized RT range and slower MU firing rates at high contraction intensities (70% and 100% MVIC) compared to uninvolved and control limbs. The ACLR involved limb also demonstrated larger MU action potentials in the VM compared to the contralateral limb. These differences were largely attenuated with relative RT normalization.

Conclusions

These results suggest that persistent strength deficits following ACLR may be attributable to a diminished quadriceps motor neuron pool and inability to upregulate the firing rate of recruited MUs.

A comparison of techniques for verifying the accuracy of precision decomposition-derived relationships between motor unit firing rates and recruitment thresholds from surface EMG signals

Approaches for validating motor unit firing times following surface electromyographic (EMG) signal decomposition with the precision decomposition III (PDIII) algorithm have not been agreed upon. Two approaches have been common: (1) "reconstruct-and-test" and (2) spike-triggered averaging (STA). We sought to compare motor unit results following the application of these approaches. Surface EMG signals were recorded from the vastus lateralis of 13 young males performing trapezoidal, isometric knee extensions at 50% and 80% of maximum voluntary contraction (MVC) force. The PDIII algorithm was used to quantify motor unit firing rates. Motor units were excluded using eight combinations of the reconstruct-and-test approach with accuracy thresholds of 0, 90, 91, and 92% with and without STA. The mean firing rate versus recruitment threshold relationship was minimally affected by STA. At 80% MVC, slopes acquired at the 0% accuracy threshold were significantly greater (i.e., less negative) than when 91% (p = .010) and 92% (p = .030) accuracy thresholds were applied. The application of STA has minimal influence on surface EMG signal decomposition results. Stringent reconstruct-and-test accuracy thresholds influence motor unit-derived relationships at high forces, perhaps explained through the increased presence of large motor unit action potentials. Investigators using the PDIII algorithm can expect negligible changes in motor unit-derived linear regression relationships with the application of secondary validation procedures.

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.

Enhanced skeletal muscle contractile function and corticospinal excitability precede strength and architectural adaptations during lower-limb resistance training

PURPOSE

Evolving investigative techniques are providing greater understanding about the early neuromuscular responses to resistance training among novice exercisers. The aim of this study was to investigate the time-course of changes in muscle contractile mechanics, architecture, neuromuscular, and strength adaptation during the first 6-weeks of lower-limb resistance training.

METHODS

Forty participants: 22 intervention (10 males/12 females; 173.48 ± 5.20 cm; 74.01 ± 13.13 kg) completed 6-week resistance training, and 18 control (10 males/8 females; 175.52 ± 7.64 cm; 70.92 ± 12.73 kg) performed no resistance training and maintained their habitual activity. Radial muscle displacement (Dm) assessed via tensiomyography, knee extension maximal voluntary contraction (MVC), voluntary activation (VA), corticospinal excitability and inhibition via transcranial magnetic stimulation, motor unit (MU) firing rate, and muscle thickness and pennation angle via ultrasonography were assessed before and after 2, 4, and 6-weeks of dynamic lower-limb resistance training or control.

RESULTS

After 2-weeks training, Dm reduced by 19-25% in the intervention group; this was before any changes in neural or morphological measures. After 4-weeks training, MVC increased by 15% along with corticospinal excitability by 16%; however, there was no change in VA, corticospinal inhibition, or MU firing rate. After 6-weeks training there was further MVC increase by 6% along with muscle thickness by 13-16% and pennation angle by 13-14%.

CONCLUSION

Enhanced contractile properties and corticospinal excitability occurred before any muscle architecture, neural, and strength adaptation. Later increases in muscular strength can be accounted for by architectural adaptation.

Sex-related differences in motor unit behavior are influenced by myosin heavy chain during high- but not moderate-intensity contractions

AIMS

Motor unit recruitment and firing rate patterns of the vastus lateralis (VL) have not been compared between sexes during moderate- and high-intensity contraction intensities. Additionally, the influence of fiber composition on potential sex-related differences remains unquantified.

METHODS

Eleven males and 11 females performed 40% and 70% maximal voluntary contractions (MVCs). Surface electromyographic (EMG) signals recorded from the VL were decomposed. Recruitment thresholds (RTs), MU action potential amplitudes (MUAPAMP ), initial firing rates (IFRs), mean firing rates (MFRs), and normalized EMG amplitude (N-EMGRMS ) at steady torque were analyzed. Y-intercepts and slopes were calculated for MUAPAMP , IFR, and MFR versus RT relationships. Type I myosin heavy chain isoform (MHC) was determined with muscle biopsies.

RESULTS

There were no sex-related differences in MU characteristics at 40% MVC. At 70% MVC, males exhibited greater slopes (p = 0.002) for the MUAPAMP , whereas females displayed greater slopes (p = 0.001-0.007) for the IFR and MFR versus RT relationships. N-EMGRMS at 70% MVC was greater for females (p < 0.001). Type I %MHC was greater for females (p = 0.006), and was correlated (p = 0.018-0.031) with the slopes for the MUAPAMP , IFR, and MFR versus RT relationships at 70% MVC (r = -0.599-0.585).

CONCLUSION

Both sexes exhibited an inverse relationship between MU firing rates and recruitment thresholds. However, the sex-related differences in MU recruitment and firing rate patterns and N-EMGRMS at 70% MVC were likely due to greater type I% MHC and smaller twitch forces of the higher threshold MUs for the females. Evidence is provided that muscle fiber composition may explain divergent MU behavior between sexes.

A scoping review of current and emerging techniques for evaluation of peripheral nerve health, degeneration, and regeneration: part 1, neurophysiology

Peripheral neuroregeneration research and therapeutic options are expanding exponentially. With this expansion comes an increasing need to reliably evaluate and quantify nerve health. Valid and responsive measures that can serve as biomarkers of the nerve status are essential for both clinical and research purposes for diagnosis, longitudinal follow-up, and monitoring the impact of any intervention. Furthermore, such biomarkers can elucidate regeneration mechanisms and open new avenues for research. Without these measures, clinical decision-making falls short, and research becomes more costly, time-consuming, and sometimes infeasible. As a companion to Part 2, which is focused on non-invasive imaging, Part 1 of this two-part scoping review systematically identifies and critically examines many current and emerging neurophysiological techniques that have the potential to evaluate peripheral nerve health, particularly from the perspective of regenerative therapies and research.

Differences in psychological readiness for return to sport after anterior cruciate ligament injury is evident in thigh musculature motor unit characteristics

Background

Following anterior cruciate ligament (ACL) injury, many athletes that undergo surgery and 6-9 months of rehabilitation struggle to return to sport. Evidence suggests that psychological factors contribute to this failure to return-to-sport.

Objective

Determine the motor control relationship between thigh musculature motor unit characteristics and psychological readiness to return to sport between ACL-injured and healthy controls.

Study design

A longitudinal cohort study.

Methods

Athletes longitudinally completed the ACL Return to Sport after Injury (ACL-RSI) survey and isometric strength measures with a measurement of electromyography (EMG) of the vastus lateralis, vastus medialis, biceps femoris, and semitendinosus. A score cut-off of 61 on the ACL-RSI was used to divide ACL-injured groups. EMG was decomposed to provide each identified motor unit's characteristics (amplitude, average firing rate, etc).

Results

Data demonstrated increased average firing rate for hamstrings (p<0.001), decreased average firing rate for vastus lateralis (p<0.001) and decreased motor unit size for both the quadriceps and hamstrings at return-to-sport post-ACL reconstruction compared with sex-matched and age-matched healthy controls (p<0.001). Furthermore, there were marked differences in disparate ACL-RSI scores between ACL-injured athletes.

Conclusions

At return to sport, ACL-injured athletes have major alterations of thigh musculature motor control, with smaller motor units used by those with low ACL-RSI scores. This study uniquely demonstrates objective thigh muscle motor unit characteristics that coincide with subjective reports of psychological readiness. This information will be important to address psychomotor complexes of injury for future rehabilitation protocols.

Low-Level Laser Therapy Facilitates Postcontraction Recovery with Ischemic Preconditioning

PURPOSE

Despite early development of muscle fatigue, ischemic preconditioning is gaining popularity for strength training combined with low-load resistance exercise. This study investigated the effect of low-level laser (LLL) on postcontraction recovery with ischemic preconditioning.

METHODS

Forty healthy adults (22.9 ± 3.5 yr) were allocated into sham (11 men, 9 women) and LLL (11 men, 9 women) groups. With ischemic preconditioning, they were trained with three bouts of intermittent wrist extension of 40% maximal voluntary contraction (MVC). During the recovery period, the LLL group received LLL (wavelength of 808 nm, 60 J) on the working muscle, whereas the sham group received no sham therapy. MVC, force fluctuations, and discharge variables of motor units (MU) for a trapezoidal contraction were compared between groups at baseline (T0), postcontraction (T1), and after-recovery (T2).

RESULTS

At T2, the LLL group exhibited a higher normalized MVC (T2/T0; 86.22% ± 12.59%) than that of the sham group (71.70% ± 13.56%; P = 0.001). The LLL group had smaller normalized force fluctuations (LLL, 94.76% ± 21.95%; sham, 121.37% ± 29.02%; P = 0.002) with greater normalized electromyography amplitude (LLL, 94.33% ± 14.69%; sham, 73.57% ± 14.94%; P < 0.001) during trapezoidal contraction. In the LLL group, the smaller force fluctuations were associated with lower coefficients of variation of interspike intervals of MUs (LLL, 0.202 ± 0.053; sham, 0.208 ± 0.048; P = 0.004) with higher recruitment thresholds (LLL, 11.61 ± 12.68 %MVC; sham, 10.27 ± 12.73 %MVC; P = 0.003).

CONCLUSIONS

LLL expedites postcontraction recovery with ischemic preconditioning, manifesting as superior force generation capacity and force precision control for activation of MU with a higher recruitment threshold and lower discharge variability.

Robust Independent Component Analysis based EMG decomposition - a comparison study

High density surface Electromyography (HD-sEMG) provides a high fidelity measurement of the myoelectric activity that can be leveraged by EMG decomposition methods to estimate the motor neuron discharges. Independent Component Analysis (ICA) methods are used as basis for many EMG decomposition algorithms, for the estimation of motor unit action potential signals. Accurate source separation is a non-trivial task in EMG decomposition. While FastICA is widely used for this purpose, other methods with attractive characteristics, such as RobustICA, remain relatively unexplored. The purpose of the current work is to compare three different ICA-based EMG decomposition methods (FastICA, RobustICA and RobustICALCH) in terms of decomposition accuracy and computation time. The evaluation was performed on simulated data using a decomposition algorithm inspired by previous studies. Our results demonstrate that RobustICA outperforms the other methods in terms of number of correctly identified motor units, high decomposition accuracy, and low computation time, across different muscle contraction levels.

An exploration of the motor unit behaviour during the concentric and eccentric phases of a squat task performed at different speeds

Despite squatting being important in strength training and rehabilitation, few studies have investigated motor unit (MU) behaviour. This study explored the MU behaviour of vastus medialis (VM) and vastus lateralis (VL) during the concentric and eccentric phases of a squat exercise performed at two speeds. Twenty-two participants had surface dEMG sensors attached over VM and VL, and IMUs recorded thigh and shank angular velocities. Participants performed squats at 15 and 25 repetitions per minute in a randomised order, and EMG signals were decomposed into their MU action potential trains. A four factor (muscle × speed × contraction phase × sexes) mixed methods ANOVA revealed significant main effects for MU firing rates between speeds, between muscles and between sexes, but not contraction phases. Post hoc analysis showed significantly greater MU firing rates and amplitudes in VM. A significant interaction was seen between speed and the contraction phases. Further analysis revealed significantly greater firing rates during the concentric compared to the eccentric phases, and between speeds during the eccentric phase only. VM and VL respond differently during squatting depending on speed and contraction phase. These new insights in VM and VL MU behvaviour may be useful when designing training and rehabilitation protocols.

Arthrogenic muscle inhibition manifests in thigh musculature motor unit characteristics after anterior cruciate ligament injury

Joint trauma induces a presynaptic reflex inhibition termed arthrogenic muscle inhibition (AMI) that prevents complete activation of muscles. Reduced motor unit (MU) output is a hypothesised mechanism for persistent strength deficits. The objective of this study was to determine MU characteristics of thigh musculature and determine how they change with anterior cruciate ligament (ACL) injury compared to healthy controls. A randomised protocol of knee flexion/extension isometric contractions (10-50% maximal voluntary isometric contraction) was performed for each leg with surface EMG 5-pin array electrodes placed on the vastus medialis, vastus lateralis, semitendinosus and biceps femoris. Longitudinal assessments for average rate coding, recruitment thresholds and MU action potentials were acquired at 6-month intervals. With exception of the vastus medialis, all thigh musculature of ACL-injured demonstrated smaller MU action potential peak-to-peak amplitude. For average rate coding, ACL-injured demonstrated lower coding rates than Controls for the quadriceps (p < .05) and higher rates than Controls for the hamstrings (p < .05). These MU characteristics were different from Controls after ACL reconstruction up to 12 months post-surgery, yet maximal strength increased during this time frame. As thigh MU characteristics are known across phases of ACL rehabilitation, future studies can assess these patterns of motor control and their potential to determine risk of re-injury. Further, future rehabilitation can target specific intervention programmes to restore motor control.HighlightsMotor unit strategies of arthrogenic muscle inhibition are characterised for the first time via decomposed EMG.Motor unit deficits of thigh musculature persist throughout all phases of ACL rehabilitation, even after return-to-sport.After ACL injury, motor unit sizes at similar recruitment thresholds were smaller than those of healthy controls.

The effects of resistance training to near failure on strength, hypertrophy, and motor unit adaptations in previously trained adults

Limited research exists examining how resistance training to failure affects applied outcomes and single motor unit characteristics in previously trained individuals. Herein, resistance-trained adults (24 ± 3 years old, self-reported resistance training experience was 6 ± 4 years, 11 men and 8 women) were randomly assigned to either a low-repetitions-in-reserve (RIR; i.e., training near failure, n = 10) or high-RIR (i.e., not training near failure, n = 9) group. All participants implemented progressive overload during 5 weeks where low-RIR performed squat, bench press, and deadlift twice weekly and were instructed to end each training set with 0-1 RIR. high-RIR performed identical training except for being instructed to maintain 4-6 RIR after each set. During week 6, participants performed a reduced volume-load. The following were assessed prior to and following the intervention: (i) vastus lateralis (VL) muscle cross-sectional area (mCSA) at multiple sites; (ii) squat, bench press, and deadlift one-repetition maximums (1RMs); and (iii) maximal isometric knee extensor torque and VL motor unit firing rates during an 80% maximal voluntary contraction. Although RIR was lower in the low- versus high-RIR group during the intervention (p < 0.001), total training volume did not significantly differ between groups (p = 0.222). There were main effects of time for squat, bench press, and deadlift 1RMs (all p-values < 0.05), but no significant condition × time interactions existed for these or proximal/middle/distal VL mCSA data. There were significant interactions for the slope and y-intercept of the motor unit mean firing rate versus recruitment threshold relationship. Post hoc analyses indicated low-RIR group slope values decreased and y-intercept values increased after training suggesting low-RIR training increased lower-threshold motor unit firing rates. This study provides insight into how resistance training in proximity to failure affects strength, hypertrophy, and single motor unit characteristics, and may inform those who aim to program for resistance-trained individuals.

Motor unit-based synergies in a non-compartmentalized muscle

The concept of synergies has been used to address the grouping of motor elements contributing to a task with the covariation of these elements reflecting task stability. This concept has recently been extended to groups of motor units with parallel scaling of the firing frequencies with possible contributions of intermittent recruitment (MU-modes) in compartmentalized flexor and extensor muscles of the forearm stabilizing force magnitude in finger pressing tasks. Here, we directly test for the presence and behavior of MU-modes in the tibialis anterior, a non-compartmentalized muscle. Ten participants performed an isometric cyclical dorsiflexion force production task at 1 Hz between 20 and 40% of maximal voluntary contraction and electromyographic (EMG) data were collected from two high-density wireless sensors placed on the skin over the right tibialis anterior. EMG data were decomposed into individual motor unit frequencies and resolved into sets of MU-modes. Inter-cycle analysis of MU-mode magnitudes within the framework of the uncontrolled manifold (UCM) hypothesis was used to quantify force-stabilizing synergies. Two or three MU-modes were identified in all participants and trials accounting, on average, for 69% of variance and were robust to cross-validation measurements. Strong dorsiflexion force-stabilizing synergies in the space of MU-modes were present in all participants and for both electrode locations as reflected in variance within the UCM (median 954, IQR 511-1924) exceeding variance orthogonal to the UCM (median 5.82, IQR 2.9-17.4) by two orders of magnitude. In contrast, MU-mode-stabilizing synergies in the space of motor unit frequencies were not present. This study offers strong evidence for the existence of synergic control mechanisms at the level of motor units independent of muscle compartmentalization, likely organized within spinal cord circuitry.

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.

Consensus for experimental design in electromyography (CEDE) project: Single motor unit matrix

The analysis of single motor unit (SMU) activity provides the foundation from which information about the neural strategies underlying the control of muscle force can be identified, due to the one-to-one association between the action potentials generated by an alpha motor neuron and those received by the innervated muscle fibers. Such a powerful assessment has been conventionally performed with invasive electrodes (i.e., intramuscular electromyography (EMG)), however, recent advances in signal processing techniques have enabled the identification of single motor unit (SMU) activity in high-density surface electromyography (HDsEMG) recordings. This matrix, developed by the Consensus for Experimental Design in Electromyography (CEDE) project, provides recommendations for the recording and analysis of SMU activity with both invasive (needle and fine-wire EMG) and non-invasive (HDsEMG) SMU identification methods, summarizing their advantages and disadvantages when used during different testing conditions. Recommendations for the analysis and reporting of discharge rate and peripheral (i.e., muscle fiber conduction velocity) SMU properties are also provided. The results of the Delphi process to reach consensus are contained in an appendix. This matrix is intended to help researchers to collect, report, and interpret SMU data in the context of both research and clinical applications.

Evaluation method of motor unit number index based on optimal muscle strength combination

Repeatability is an important attribute of motor unit number index (MUNIX) technology. This paper proposes an optimal contraction force combination for MUNIX calculation in an effort to improve the repeatability of this technology. In this study, the surface electromyography (EMG) signals of the biceps brachii muscle of eight healthy subjects were initially recorded with high-density surface electrodes, and the contraction strength was the maximum voluntary contraction force of nine progressive levels. Then, by traversing and comparing the repeatability of MUNIX under various combinations of contraction force, the optimal combination of muscle strength is determined. Finally, calculate MUNIX using the high-density optimal muscle strength weighted average method. The correlation coefficient and the coefficient of variation are utilized to assess repeatability. The results show that when the muscle strength combination is 10, 20, 50 and 70% of the maximum voluntary contraction force, the repeatability of MUNIX is greatest, and the correlation between MUNIX calculated using this combination of muscle strength and conventional methods is high (PCC > 0.99), the repeatability of the MUNIX method improved by 11.5-23.8%. The results indicate that the repeatability of MUNIX differs for various combinations of muscle strength and that MUNIX, which is measured with a smaller number and lower-level contractility, has greater repeatability.

Arthrogenic muscle inhibition after anterior cruciate ligament injury: Injured and uninjured limb recovery over time

Introduction

It is well documented that marked weakness of the quadriceps is present after knee joint injury. This joint trauma induces a presynaptic reflex inhibition of musculature surrounding the joint, termed arthrogenic muscle inhibition (AMI). The extent to which anterior cruciate ligament (ACL) injury affects thigh musculature motor unit activity, which may affect restoration of thigh muscle strength after injury, is undetermined.

Methods

A randomized protocol of knee flexion and extension isometric contractions (10%-50% maximal voluntary isometric contraction) were performed for each leg on 54 subjects with electromyography array electrodes placed on the vastus medialis, vastus lateralis, semitendinosus, and biceps femoris. Longitudinal assessments for motor unit recruitment and average firing rate were acquired at 6-month intervals for 1 year post ACL injury.

Results

The ACL-injured population demonstrated smaller quadriceps and hamstrings motor unit size (assessed via motor unit action potential peak-to-peak amplitude) and altered firing rate activity in both injured and uninjured limbs compared to healthy controls. Motor unit activity remained altered compared to healthy controls at 12 months post ACL reconstruction (ACLR).

Discussion

Motor unit activity was altered after ACLR up to 12 months post-surgery. Further research is warranted to optimize rehabilitation interventions that adequately address altered motor unit activity and improve safety and success with return to sport after ACLR. In the interim, evidence based clinical reasoning with a focus on development of muscular strength and power capacity should be the impetus behind rehabilitation programming to address motor control deficits.

Compressed spike-triggered averaging in iterative decomposition of surface EMG

BACKGROUND AND OBJECTIVE

Analysis of motor unit activity is important for assessing and treating diseases or injuries affecting natural movement. State-of-the-art decomposition translates high-density surface electromyography (HDsEMG) into motor unit activity. However, current decomposition methods offer far from complete separation of all motor units.

METHODS

This paper proposes a peel-off approach to automatic decomposition of HDsEMG into motor unit action potential (MUAP) trains, based on the Fast Independent Component Analysis algorithm (FastICA). The novel steps include utilizing compression by means of Principal Component Analysis and spike-triggered averaging, to estimate surface MUAP distributions with less noise, which are iteratively subtracted from the HDsEMG dataset. Furthermore, motor unit spike trains are estimated by high-dimensional density-based clustering of peaks in the FastICA source output. And finally, a new reliability measure is used to discard poor motor unit estimates by comparing the variance of the FastICA source output before and after the peel-off step. The method was validated using reconstructed synthetic data at three different signal-to-noise levels and was compared to an established deflationary FastICA approach.

RESULTS

Both algorithms had very high recall and precision, over 90%, for spikes from matching motor units, referred to as matched performance. However, the peel-off algorithm correctly identified more motor units for all noise levels. When accounting for unidentified motor units, total recall was up to 33 percentage points higher; and when accounting for duplicate estimates, total precision was up to 24 percentage points higher, compared to the state-of-the-art reference. In addition, a comparison was done using experimental data where the proposed algorithm had a matched recall of 97% and precision of 85% with respect to the reference algorithm.

CONCLUSION

These results show a substantial performance increase for decomposition of simulated HDsEMG data and serve to validate the proposed approach. This performance increase is an important step towards complete decomposition and extraction of information of motor unit activity.

Failure to improve task performance after visuomotor training with error reduction feedback for young adults

Visual feedback that reinforces accurate movements may motivate skill acquisition by promoting self-confidence. This study investigated neuromuscular adaptations to visuomotor training with visual feedback with virtual error reduction. Twenty-eight young adults (24.6 ± 1.6 years) were assigned to error reduction (ER) (n = 14) and control (n = 14) groups to train on a bi-rhythmic force task. The ER group received visual feedback and the displayed errors were 50% of the real errors in size. The control group was trained with visual feedback with no reduction in errors. Training-related differences in task accuracy, force behaviors, and motor unit discharge were contrasted between the two groups. The tracking error of the control group progressively declined, whereas the tracking error of the ER group was not evidently reduced in the practice sessions. In the post-test, only the control group exhibited significant task improvements with smaller error size (p = .015) and force enhancement at the target frequencies (p = .001). The motor unit discharge of the control group was training-modulated, as indicated by a reduction of the mean inter-spike interval (p = .018) and smaller low-frequency discharge fluctuations (p = .017) with enhanced firing at the target frequencies of the force task (p = .002). In contrast, the ER group showed no training-related modulation of motor unit behaviors. In conclusion, for young adults, ER feedback does not induce neuromuscular adaptations to the trained visuomotor task, which is conceptually attributable to intrinsic error dead-zones.

Altered neuromuscular control in the vastus medialis following anterior cruciate ligament injury: A recurrence quantification analysis of electromyogram recruitment

BACKGROUND

Neuromuscular deficits exist following anterior cruciate ligament (ACL) injury. To observe these deficits, we examined nonlinear characteristics of vastus medialis electromyography (EMG) signals during submaximal isometric knee extensor contractions. Our purpose was to examine if determinism and entropy in EMG signals reflected neuromuscular control deficits in individuals with ACL-deficient limbs.

METHODS

24 participants (12 male, 12 female, mean age = 18.8 ± 3.1 years) with unilaterally injured ACLs and 25 age-similar healthy controls (11 male, 14 female, mean age = 18.8 ± 3.1 years) volunteered. Isometric knee extensions were tested at 10%, 25%, 35%, and 50% maximum voluntary contractions. Surface electrodes adhered over the vastus medialis captured EMG signals. EMG data were processed with recurrence quantification analyses. Specifically, determinism (an index of system predictability) and entropy (an index of system disorder) were calculated from recurrence plots.

FINDINGS

Determinism and entropy in EMG signals were lower in the injured than uninjured limb, and lower than that from healthy controls (P < .05).

INTERPRETATION

Vastus medialis EMG signals from the injured limb were less predictable and less complex than those from healthy limbs. The findings reflect impaired neuromuscular control in the injured limb's quadriceps and are consistent with a 'loss of complexity' hypothesis in physiologic signals emanating from pathologic states. Determinism and entropy in EMG signals may represent biomarkers of one's neuromuscular control system.

The Strategy of the Brain to Maintain the Force Production in Painful Contractions-A Motor Units Pool Reorganization

A common symptom in neuromuscular diseases is pain, which changes human movement in many ways. Using the decomposed electromyographic signal, we investigate the strategy of the brain in recruiting different pools of motor units (MUs) to produce torque during induced muscle pain in terms of firing rate (FR), recruitment threshold (RT) and action potential amplitude (MUAP_AMP). These properties were used to define two groups (G1/G2) based on a K-means clusterization method. A 2.0 mL intramuscular hypertonic (6%) or isotonic (0.9%) saline solution was injected to induce pain or act as a placebo during isometric and isokinetic knee extension contractions. While isometric torque decreases after pain induction with hypertonic solution, this does not occur in isokinetic torque. This occurs because the MUs re-organized after the injection of both solutions. This is supported by an increase in RT, in both G1 and G2 MUs. However, when inducing pain with the hypertonic solution, RT increase is exacerbated. In this condition, FR also decreases, while MUAP_AMP increases only for G1 MUs. Therefore, this study proposes that the strategy for maintaining force production during pain is to recruit MUs with higher RT and MUAP_AMP.

Neural inputs from spinal motor neurons to lateralis vastus muscle: Comparison between sprinters and nonathletes

The adaptation of neural contractile properties has been observed in previous work. However, the neural changes on the motor unit (MU) level remain largely unknown. Voluntary movements are controlled through the precise activation of MU populations. In this work, we estimate the neural inputs from the spinal motor neurons to the muscles during isometric contractions and characterize the neural adaptation during training by comparing the MU properties decomposed from sprinters and nonathletes. Twenty subjects were recruited and divided into two groups. The high-density surface electromyography (EMG) signals were recorded from the lateralis vastus muscle during the isometric contraction of knee extension and were then decomposed into MU spike trains. Each MU’s action potentials and discharge properties were extracted for comparison across subject groups and tasks. A total of 1097 MUs were identified from all subjects. Results showed that the discharge rates and amplitudes of MUAPs from athletes were significantly higher than those from nonathletes. These results demonstrate the neural adaptations in physical training at the MU population level and indicate the great potential of EMG decomposition in physiological investigations.

Differences in motor unit firing properties of the vastus lateralis muscle during postural and voluntary tasks

The firing properties of the motor units are usually affected by the motor task. However, it has not been clarified whether the firing properties of the motor units of a specific muscle are different between postural and voluntary tasks. Therefore, this study investigated whether the recruitment and rate coding of the motor units differ between these two motor tasks. Thirteen healthy volunteers performed trapezoidal muscle contraction with a target value of 15% maximum electromyography (EMG) activity by voluntary left knee extension in the sitting position (voluntary task) and postural maintenance in the semi-squatting position (postural task) with a knee flexion angle of 30°. We obtained four channels of surface EMG activity during each task from left vastus lateralis muscle. We extracted the firing properties of individual motor units using the EMG decomposition algorithm. The recruitment threshold and motor unit action potential amplitude were significantly lower in the postural task than in the voluntary task, and conversely, the mean firing rate was significantly higher. These results were explained by the preferential recruitment of motor units with higher recruitment threshold and amplitude in the voluntary task, while motor units with lower recruitment threshold and higher firing rate were preferentially recruited in the postural task. Preferential activation of fatigue-resistant motor units in the postural task is a reasonable strategy as it allows for sustained postural maintenance. We provide the first evidence that motor unit firing properties are clearly different between postural and voluntary tasks, even at the same muscle activity level.

Neural decoding from surface high-density EMG signals: influence of anatomy and synchronization on the number of identified motor units

OBJECTIVE

High-density surface electromyography (HD-sEMG) allows the reliable identification of individual motor unit (MU) action potentials. Despite the accuracy in decomposition, there is a large variability in the number of identified MUs across individuals and exerted forces. Here we present a systematic investigation of the anatomical and neural factors that determine this variability.

APPROACH

We investigated factors of influence on HD-sEMG decomposition, such as synchronization of MU discharges, distribution of MU territories, muscle-electrode distance (MED - subcutaneous adipose tissue thickness), maximum anatomical cross-sectional area (ACSA_max), and fiber CSA. For this purpose, we recorded HD-sEMG signals, ultrasound and, magnetic resonance images, and took a muscle biopsy from the biceps brachii muscle from 30 male participants drawn from two groups to ensure variability within the factors - untrained-controls (UT=14) and strength-trained individuals (ST=16). Participants performed isometric ramp contractions with elbow flexors (at 15, 35, 50 and 70% maximum voluntary torque - MVT). We assessed the correlation between the number of accurately detected MUs by HD-sEMG decomposition and each measured parameter, for each target force level. Multiple regression analysis was then applied.

MAIN RESULTS

ST subjects showed lower MED (UT=5.1±1.4 mm; ST=3.8±0.8 mm) and a greater number of identified motor units (UT:21.3±10.2 vs ST:29.2±11.8 MUs/subject across all force levels). The entire cohort showed a negative correlation between MED and the number of identified MUs at low forces (r= -0.6, p=0.002 at 15%MVT). Moreover, the number of identified MUs was positively correlated to the distribution of MU territories (r=0.56, p=0.01) and ACSA_max(r=0.48, p=0.03) at 15%MVT. By accounting for all anatomical parameters, we were able to partly predict the number of decomposed MUs at low but not at high forces.

SIGNIFICANCE

Our results confirmed the influence of subcutaneous tissue on the quality of HD-sEMG signals and demonstrated that MU spatial distribution and ACSA_maxare also relevant parameters of influence for current decomposition algorithms.