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This tutorial is aimed primarily to non-engineers (clinical researchers, clinicians, neurophysiology technicians, ergonomists, movement and sport scientists, physical therapists) or beginners using, or planning to use, surface electromyography (sEMG) as a monitoring and assessment tool for muscle and neuromuscular evaluations in the prevention and rehabilitation fields. Its first purpose is to explain, with minimal mathematics, basic concepts related to: (a) time and frequency domain description of a signal, (b) Fourier transform, (c) amplitude, phase, and power spectrum of a signal, (d) sampling of a signal, (e) filtering of sEMG signals, (f) cross-spectrum and coherence between two signals, (g) signal stationarity and criteria for epoch selection, (h) myoelectric manifestations of muscle fatigue and (i) fatigue indices. These concepts are consolidated knowledge and are addressed and discussed with examples taken from the literature., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2024 The Authors. Published by Elsevier Ltd.. All rights reserved.)

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.

Surgical nerve transfers are used to efficiently treat peripheral nerve injuries, neuromas, phantom limb pain, or improve bionic prosthetic control. Commonly, one donor nerve is transferred to one target muscle. However, the transfer of multiple nerves onto a single target muscle may increase the number of muscle signals for myoelectric prosthetic control and facilitate the treatment of multiple neuromas. Currently, no experimental models are available. This study describes a novel experimental model to investigate the neurophysiological effects of peripheral double nerve transfers to a common target muscle. In 62 male Sprague-Dawley rats, the ulnar nerve of the antebrachium alone (n=30) or together with the anterior interosseus nerve (n=32) was transferred to reinnervate the long head of the biceps brachii. Before neurotization, the motor branch to the biceps' long head was transected at the motor entry point. Twelve weeks after surgery, muscle response to neurotomy, behavioral testing, retrograde labeling, and structural analyses were performed to assess reinnervation. These analyses indicated that all nerves successfully reinnervated the target muscle. No aberrant reinnervation was observed by the originally innervating nerve. Our observations suggest a minimal burden for the animal with no signs of functional deficit in daily activities or auto-mutilation in both procedures. Furthermore, standard neurophysiological analyses for nerve and muscle regeneration were applicable. This newly developed nerve transfer model allows for the reliable and standardized investigation of neural and functional changes following the transfer of multiple donor nerves to one target muscle., Competing Interests: ML, JK, SM, JI, VT, CF, GL, OP, UM, DF, OA, KB No competing interests declared, (© 2021, Luft et al.)

Our current understanding of synergistic muscle control is based on the analysis of muscle activities. Modules (synergies) in muscle coordination are extracted from electromyographic (EMG) signal envelopes. Each envelope indirectly reflects the neural drive received by a muscle; therefore, it carries information on the overall activity of the innervating motor neurons. However, it is not known whether the output of spinal motor neurons, whose number is orders of magnitude greater than the muscles they innervate, is organized in a low-dimensional fashion when performing complex tasks. Here, we hypothesized that motor neuron activities exhibit a synergistic organization in complex tasks and therefore that the common input to motor neurons results in a large dimensionality reduction in motor neuron outputs. To test this hypothesis, we factorized the output spike trains of motor neurons innervating 14 intrinsic and extrinsic hand muscles and analyzed the dimensionality of control when healthy individuals exerted isometric forces using seven grip types. We identified four motor neuron synergies, accounting for >70% of the variance of the activity of 54.1 ± 12.9 motor neurons, and we identified four functionally similar muscle synergies. However, motor neuron synergies better discriminated individual finger forces than muscle synergies and were more consistent with the expected role of muscles actuating each finger. Moreover, in a few cases, motor neurons innervating the same muscle were active in separate synergies. Our findings suggest a highly divergent net neural inputs to spinal motor neurons from spinal and supraspinal structures, contributing to the dimensionality reduction captured by muscle synergies. SIGNIFICANCE STATEMENT We addressed whether the output of spinal motor neurons innervating multiple hand muscles could be accounted for by a modular organization, i.e., synergies, previously described to account for the coordination of multiple muscles. We found that motor neuron synergies presented similar dimensionality (implying a >10-fold reduction in dimensionality) and structure as muscle synergies. Nonetheless, the synergistic behavior of subsets of motor neurons within a muscle was also observed. These results advance our understanding of how neuromuscular control arises from mapping descending inputs to muscle activation signals. We provide, for the first time, insights into the organization of neural inputs to spinal motor neurons which, to date, has been inferred through analysis of muscle synergies., (Copyright © 2021 the authors.)

Pathological tremor is an oscillation of body parts at 3-10 Hz, determined by the output of spinal motor neurons (MNs), which receive synaptic inputs from supraspinal centers and muscle afferents. The behavior of spinal MNs during tremor is not well understood, especially in relation to the activation of the multiple muscles involved. Recent studies on patients with essential tremor have shown that antagonist MN pools receive shared input at the tremor frequency. In this study, we investigated the synaptic inputs related to tremor and voluntary movement, and their coordination across antagonist muscles. We analyzed the spike trains of motor units (MUs) identified from high-density surface electromyography from the forearm extensor and flexor muscles in 15 patients with essential tremor during postural tremor. The shared synaptic input was quantified by coherence and phase difference analysis of the spike trains. All pairs of spike trains in each muscle showed coherence peaks at the voluntary drive frequency (1-3 Hz, 0.2 ± 0.2, mean ± SD) and tremor frequency (3-10 Hz, 0.6 ± 0.3) and were synchronized with small phase differences (3.3 ± 25.2° and 3.9 ± 22.0° for the voluntary drive and tremor frequencies, respectively). The coherence between MN spike trains of antagonist muscle groups at the tremor frequency was significantly smaller than intramuscular coherence. We predominantly observed in-phase activation of MUs between agonist/antagonist muscles at the voluntary frequency band (0.6 ± 48.8°) and out-of-phase activation at the tremor frequency band (126.9 ± 75.6°). Thus MNs innervating agonist/antagonist muscles concurrently receive synaptic inputs with different phase shifts in the voluntary and tremor frequency bands. NEW & NOTEWORTHY Although the mechanical characteristics of tremor have been widely studied, the activation of the affected muscles is still poorly understood. We analyzed the behavior of motor units of pairs of antagonistic wrist muscle groups in patients with essential tremor and studied their activity at voluntary movement- and tremor-related frequencies. We found that the phase relation between inputs to antagonistic muscles is different at the voluntary and tremor frequency bands.

It has been shown that Ia afferents inhibit muscle activity of the ipsilateral antagonist, a mechanism known as reciprocal inhibition. Stimulation of these afferents may be explored for the therapeutic reduction of pathological tremor (Essential Tremor or due Parkinson's Disease, for example). However, only a few studies have investigated reciprocal inhibition of wrist flexor / extensor motor control. The main goal of this study was to characterize reciprocal inhibition of wrist flexors / extensors by applying surface electrical stimulation to the radial and median nerves, respectively. Firstly, the direct (M) and monosynaptic (H) reflex responses to increasing median and radial nerve stimulation were recorded to characterize the recruitment curve of the flexor carpi radialis (FCR) and extensor carpi radialis (ECR) muscles, respectively. Based on the recruitment curve data, we then stimulated the median and radial nerves below (<; MT) and above (> MT) motor threshold (MT) during a submaximal isometric task to assess the amount of inhibition on ECR and FCR antagonist muscles, respectively. The stimulation of both nerves produced a long-duration inhibition of the antagonist motoneuron pool activity. On average, maximum peak of inhibition was 27 ± 6% for ECR and 32 ± 9% for FCR with stimulation <; MT; maximum peak of inhibition was 45 ± 7% for ECR and 44 ± 13% for FCR when using stimulation > MT. These results validate this neurophysiological technique that demonstrates a mechanism similar to classical reciprocal Ia inhibition reported for other limb joints and that can be used to benchmark strategies to suppress pathological tremor.

Objective: We propose, design and test a novel thin-film multichannel electrode that can be used for both recording from and stimulating a muscle in acute implants., Approach: The system is built on a substrate of polyimide and contains 12 recording and three stimulation sites made of platinum. The structure is 420 µm wide, 20 µm thick and embeds the recording and stimulation contacts on the two sides of the polyimide over an approximate length of 2 cm. We show representative applications in healthy individuals as well as tremor patients. The designed system was tested by a psychometric characterization of the stimulation contacts in six tremor patients and three healthy individuals determining the perception threshold and current limit as well as the success rate in discriminating elicited sensations (electrotactile feedback). Also, we investigated the possibility of using the intramuscular electrode for reducing tremor in one patient by electrical stimulation delivered with timing based on the electromyographic activity recorded with the same electrode., Main Results: In the tremor patients, the current corresponding to the perception threshold and the current limit were 0.7  ±  0.2 and 1.4  ±  0.7 mA for the wrist flexor muscles and 0.4  ±  0.2 and 1.5  ±  0.7 mA for the extensors. In one patient, closed-loop stimulation resulted in a decrease of the tremor power  >50%. In healthy individuals the perception threshold and current limits were 0.9  ±  0.6 and 2.1  ±  0.6 mA for the extensor carpi radialis muscle. The subjects could distinguish four or six stimulation patterns (two or three stimulation sites  ×  two stimulation current amplitudes) with true positive rate  >80% (two subjects) and  >60% (one subject), respectively., Significance: The proposed electrode provides a compact multichannel interface for recording electromyogram and delivering electrical stimulation in applications such as neuroprostheses for tremor suppression and closed-loop myoelectric prostheses.

Objective: Surface electromyography (EMG) is currently used as a control signal for active prostheses in amputees who underwent targeted muscle reinnervation (TMR) surgery. Recent research has shown that it is possible to access the spiking activity of spinal motor neurons from multi-channel surface EMG. In this study, we propose the use of multi-channel epimysial EMG electrodes as an interface for decoding motor neurons activity following TMR., Approach: We tested multi-channel epimysial electrodes (48 detection sites) built with thin-film technology in an animal model of TMR. Eight animals were tested 12 weeks after reinnervation of the biceps brachii lateral head by the ulnar nerve. We identified the position of the innervation zone and the muscle fiber conduction velocity of motor units decoded from the multi-channel epimysial recordings. Moreover, we characterized the pick-up volume by the distribution of the motor unit action potential amplitude over the epimysium surface., Main Results: The electrodes provided high quality signals with average signal-to-noise ratio  >30 dB across 95 identified motor units. The motor unit action potential amplitude decreased with increasing distance of the electrode from the muscle fibers (P [Formula: see text] 0.001). The decrease was more pronounced for bipolar compared to monopolar derivations. The average muscle fiber conduction velocity was 2.46  ±  0.83 m s -1 . Most of the neuromuscular junctions were close to the region where the nerve was neurotized, as observed from the EMG recordings and imaging data., Significance: These results show that epimysial electrodes can be used for selective recordings of motor unit activities with a pick-up volume that included the entire muscle in the rat hindlimb. Epimysial electrodes can thus be used for detecting motor unit activity in muscles with specific fascicular territories associated to different functions following TMR surgery.

The relatively large pick-up volume of surface electrodes has for long motivated the concern that muscles other than that of interest may contribute to surface electromyograms (EMGs). Recent findings suggest however the pick-up volume of surface electrodes may be smaller than previously appreciated, possibly leading to the detection of surface EMGs insensitive to muscle activity. Here we combined surface and intramuscular recordings to investigate how comparably action potentials from gastrocnemius and soleus are represented in surface EMGs detected with different inter-electrode distances. We computed the firing instants of motor units identified from intramuscular EMGs detected from gastrocnemius and soleus while five participants stood upright. We used these instants to trigger and average surface EMGs detected from multiple skin regions along gastrocnemius. Results from 66 motor units (whereof 31 from gastrocnemius) revealed the surface-recorded amplitude of soleus action potentials was 6% of that of gastrocnemius and did not decrease for inter-electrode distances smaller than 4 cm. Gastrocnemius action potentials were more likely detected for greater inter-electrode distances and their amplitude increased steeply up to 5 cm inter-electrode distance. These results suggest that reducing inter-electrode distance excessively may result in the detection of surface EMGs insensitive to gastrocnemius activity without substantial attenuation of soleus crosstalk.

The neural command from motor neurons to muscles - sometimes referred to as the neural drive to muscle - can be identified by decomposition of electromyographic (EMG) signals. This approach can be used for inferring the voluntary commands in neural interfaces in patients with limb amputations. This paper proposes for the first time an innovative method for fully automatic and real-time intramuscular EMG (iEMG) decomposition. The method is based on online single-pass density-based clustering and adaptive classification of bivariate features, using the concept of potential measure. No attempt was made to resolve superimposed motor unit action potentials. The proposed algorithm was validated on sets of simulated and experimental iEMG signals. Signals were recorded from the biceps femoris long-head, vastus medialis and lateralis and tibialis anterior muscles during low-to-moderate isometric constant-force and linearly-varying force contractions. The average number of missed, duplicated and erroneous clusters for the examined signals was [Formula: see text], [Formula: see text], and [Formula: see text], respectively. The average decomposition accuracy (defined similar to signal detection theory but without using True Negatives in the denominator) and coefficient of determination (variance accounted for) for the cumulative discharge rate estimation were [Formula: see text], and [Formula: see text], respectively. The time cost for processing each 200[Formula: see text]ms iEMG interval was [Formula: see text] (21-97)[Formula: see text]ms. However, computational time generally increases over time as a function of frames/signal epochs. Meanwhile, the incremental accuracy defined as the accuracy of real-time analysis of each signal epoch, was [Formula: see text]% for epochs recorded after initial one second. The proposed algorithm is thus a promising new tool for neural decoding in the next-generation of prosthetic control.

Objective: The study of motor unit behavior has been classically performed by selective recording systems of muscle electrical activity (EMG signals) and decomposition algorithms able to discriminate between individual motor unit action potentials from multi-unit signals. In this study, we provide a general framework for the decomposition of multi-channel intramuscular and surface EMG signals and we extensively validate this approach with experimental recordings., Approach: First, we describe the conditions under which the assumptions of the convolutive blind separation model are satisfied. Second, we propose an approach of convolutive sphering of the observations followed by an iterative extraction of the sources. This approach is then validated using intramuscular signals recorded by novel multi-channel thin-film electrodes on the Abductor Digiti Minimi of the hand and Tibilias Anterior muscles, as well as on high-density surface EMG signals recorded by electrode grids on the First Dorsal Interosseous muscle. The validation was based on the comparison with the gold standard of manual decomposition (for intramuscular recordings) and on the two-source method (for comparison of intramuscular and surface EMG recordings) for the three human muscles and contraction forces of up to 90% MVC., Main Results: The average number of common sources identified for the validation was 14 ± 7 (averaged across all trials and subjects and all comparisons), with a rate of agreement in their discharge timings of 92.8 ± 3.2%. The average Decomposability Index, calculated on the automatic decomposed signals, was 16.0 ± 2.2 (7.3-44.1). For comparison, the same index calculated on the manual decomposed signals was 15.0 ± 3.0 (6.3-76.6)., Significance: These results show that the method provides a solid framework for the decomposition of multi-channel invasive and non-invasive EMG signals that allows the study of the behavior of a large number of concurrently active motor units.

Muscle pain induces a complex reorganization of the motor strategy which cannot be fully explained by current theories. We tested the hypothesis that the neural control of muscles during reaching in the presence of nociceptive input is determined by a reorganization of muscle synergies with respect to control conditions. Muscle pain was induced by injection of hypertonic saline into the anterior deltoid muscle of eight men. Electromyographic (EMG) signals were recorded from 12 upper limb muscles as subjects performed a reaching task before (baseline) and after the injection of hypertonic (pain) saline, and after the pain sensation vanished. The EMG envelopes were factorized in muscle synergies, and activation signals extracted for each condition. Nociceptive stimulation resulted in a complex muscle reorganization without changes in the kinematic output. The anterior deltoid muscle activity decreased in all subjects while the changes in other muscles were subject specific. Three synergies sufficed to describe the EMG patterns in each condition, suggesting that reaching movements remain modular in the presence of experimental pain. Muscle reorganization in all subjects was accompanied by a change in the activation signals compatible with a change in the central drive to muscles. One, two or three synergies were shared between the baseline and painful conditions, depending on the subject. These results indicate that nociceptive stimulation may induce a reorganization of modular control in reaching. We speculate that such reorganization may be due to the recruitment of synergies specific to the painful condition.

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

This paper presents a density-based method to automatically decompose single-channel intramuscular electromyogram (EMG) signals into their component motor unit action potential (MUAP) trains. In contrast to most previous decomposition methods, which require pre-setting and (or) tuning of multiple parameters, the proposed method takes advantage of the data-dependent strategies in the pattern recognition procedures. In this method, outliers (superpositions) are excluded prior to classification and MUAP templates are identified by an adaptive density-based clustering procedure. MUAP trains are then identified by a novel density-based classifier that incorporates MUAP shape and discharge time information. MUAP trains are merged by a fuzzy system that incorporates expert human knowledge. Finally, superimpositions are resolved to fill the gaps in the MUAP trains. The proposed decomposition algorithm has been experimentally tested on signals from low-force (≤30% maximal) isometric contractions of the vastus medialis obliquus, vastus lateralis, biceps femoris long-head and tibialis anterior muscles. Comparison with expert manual decomposition that had been verified using a rigorous statistical analysis showed that the algorithm identified 80% of the total 229 motor unit trains with an accuracy greater than 90%. The algorithm is robust and accurate, and therefore it is a promising new tool for decomposing single-channel multi-unit signals.

This study compares neck force steadiness in women with neck pain and controls and the way this is influenced by short term vibration of the neck. In the first experiment, 9 women with chronic neck pain and 9 controls performed 10-s isometric cervical flexion at 15N. Intramuscular EMG was recorded from the sternocleidomastoid muscle. In the second experiment, 10 women with neck pain and 10 controls performed 10-s isometric cervical flexion at 25% of their maximal force before and after vibration to the neck (bursts of 50Hz with duration 20, 40, 60 and 120s). Surface EMG was acquired from the sternocleidomastoid and splenius capitis. In both experiments, force steadiness was characterized by the coefficient of variation (CoV) and the relative power in three frequency subbands (low: 0-3Hz; middle: 4-6Hz; high: 8-12Hz) of the force signal. Women with neck pain exhibited decreased force steadiness (Exp 1: patients 3.9±1.3%, controls 2.7±0.9%, P<0.05; Exp 2: patients 3.4±1.2%, controls 1.7±0.6%, P<0.01) which was associated with higher power in the low-frequency band (patients 71.2±9.6%, controls 56.7±9.2%, P<0.01). Following vibration, CoV (2.6±1.1%, P<0.05) and the power in the low-frequency band of the force signal decreased (63.1±13.9%, P<0.05) in the patient group. These effects were not present in controls. Motor unit behavior and surface EMG amplitude were similar between groups. In conclusion, women with neck pain have reduced force steadiness, likely due to alterations in Ia afferent input. Vibration, which modulates Ia afferent input, increases force steadiness in patients with neck pain., (Copyright © 2010 Elsevier Ltd. All rights reserved.)

In cat medial gastrocnemius (MG), fibres supplied by individual motoneurones (muscle units) distribute extensively along the muscle longitudinal axis. In the human MG, the size of motor unit territory is unknown. It is uncertain if the absolute size of muscle unit territory or the size relative to the whole muscle is most comparable with the cat. By comparing intramuscular and surface electromyograms we tested whether muscle units extend narrowly or widely along the human MG muscle. Due to the pennation of the MG, if individual motoneurones supply fibres scattered along the muscle, then action potentials of single motor units are expected to appear sparsely on the surface of the skin. In nine healthy subjects, pairs of wire electrodes were inserted in three locations along the MG muscle (MG60%, MG75% and MG90%). A longitudinal array of 16 surface electrodes was positioned alongside the intramuscular electrodes. While subjects stood quietly, 55 motor units were identified, of which, significantly more units were detected in the most distal sites. The surface action potentials had maximum amplitude at 4.40 ±1.67 (mean±S.D.), 8.02±2.16 and 11.63±2.09 cm (P <0.001) from the most proximal surface electrode, for motor units in the MG60%, MG75% and MG90% locations, respectively. Single motor unit potentials were recorded by five consecutive surface electrodes, at most, indicating that muscle units extend shortly along the MG longitudinal axis. It is concluded that relative to the whole muscle, and compared with the cat, muscle units in human MG are localised. The localisation of muscle units might have implications for the regional control of muscle activity.

Muscle synergies have been proposed as a simplifying principle of generation of movements based on a low-dimensional control by the CNS. This principle may be useful for movement restoration by, e.g., functional electrical stimulation (FES), if a limited set of synergies can describe several functional tasks. This study investigates the possibility of describing a multijoint reaching task of the upper limb by a linear combination of one set of muscle synergies common to multiple directions. Surface electromyographic (EMG) signals were recorded from 12 muscles of the dominant upper limb of eight healthy men during single-joint movements and a multijoint reaching task in 12 directions in the horizontal plane. The movement kinematics was recorded by a motion analysis system. Muscle synergies were extracted with nonnegative matrix factorization of the EMG envelopes. Synergies were computed either from the single-joint movements to describe the two degrees of freedom independently or from the multijoint movements. On average, the multijoint reaching task could be accurately described in all the directions (coefficient of determination >0.85) by a linear combination of either four synergies extracted from the individual degrees of freedom or three synergies extracted from multijoint movements in at least three reaching directions. These results indicate that a large set of multijoint movements can be generated by a synergy matrix of limited dimensionality and common to all directions if the synergies are extracted from a representative number of directions. The linear combination of synergies may thus be used in strategies for restoring functions, such as FES.