Amplitude cancellation of motor-unit action potentials in the surface electromyogram can be estimated with spike-triggered averaging

Effect of experimentally induced muscle pain on neuromuscular control of force production

PURPOSE

Neural and peripheral effects of induced muscle pain on explosive force production were investigated.

METHODS

Nine participants performed two maximal, six explosive, and six electrical stimulations induced (twitches and octets) isometric knee extensions before and after (15 min of rest) receiving an intramuscular injection of hypertonic saline (pain inducer) or isotonic (placebo) infusions in two laboratory visits separated by 7 days.

RESULTS

It was observed a reduction of peak torque production in maximal voluntary contraction in both conditions (9.3 and 3.3% for pain and placebo, respectively) and in the rate of torque development in placebo (7%). There was an increase in the rate of torque development for twitch and octets (10.5 and 15.8%, respectively) in the pain condition and peak torque for twitch (12%) in both conditions (as did the total rate of torque development for octets).

CONCLUSION

Force production decreases and increases during voluntary and involuntary contractions, respectively, suggesting that acute pain impairs force production via central mechanisms.

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.

Combined effect of contraction type and intensity on corticomuscular coherence during isokinetic plantar flexions

During isometric contractions, corticomuscular coherence (CMC) may be modulated along with the contraction intensity. Furthermore, CMC may also vary between contraction types due to the contribution of spinal inhibitory mechanisms. However, the interaction between the effect of the contraction intensity and of the contraction type on CMC remains hitherto unknown. Therefore, CMC and spinal excitability modulations were compared during submaximal isometric, shortening and lengthening contractions of plantar flexor muscles at 25, 50, and 70% of the maximal soleus (SOL) EMG activity. CMC was computed in the time-frequency domain between the Cz EEG electrode signal and the SOL or medial gastrocnemius (MG) EMG signals. The results indicated that beta-band CMC was decreased in the SOL only between 25 and 50-70% contractions for both isometric and anisometric contractions, but remained similar for all contraction intensities in the MG. Spinal excitability was similar for all contraction intensities in both muscles. Meanwhile a divergence of the EEG and the EMG signals mean frequency was observed only in the SOL and only between 25 and 50-70% contractions, independently from the contraction type. Collectively, these findings confirm an effect of the contraction intensity on beta-band CMC, although it was only measured in the SOL, between low-level and high-level contraction intensities. Furthermore, the current findings provide new evidence that the observed modulations of beta-band CMC with the contraction intensity does not depend on the contraction type or on spinal excitability variations.

Mapping Individual Motor Unit Activity to Continuous Three-DoF Wrist Torques: Perspectives for Myoelectric Control

The surface electromyography (EMG) decomposition techniques provide access to motor neuron activities and have been applied to myoelectric control schemes. However, the current decomposition-based myoelectric control mainly focuses on discrete gestures or single-DoF continuous movements. In this study, we aimed to map the motor unit discharges, which were identified from high-density surface EMG, to the three degrees of freedom (DoFs) wrist movements. The 3-DoF wrist torques and high-density surface EMG signals were recorded concurrently from eight non-disabled subjects. The experimental protocol included single-DoF movements and their various combinations. We decoded the motor unit discharges from the EMG signals using a segment-wise decomposition algorithm. Then the neural features were extracted from motor unit discharges and projected to wrist torques with a multiple linear regression model. We compared the performance of two neural features (twitch model and spike counting) and two training schemes (single-DoF and multi-DoF training). On average, 145 ± 33 motor units were identified from each subject, with a pulse-to-noise ratio of 30.8 ± 4.2 dB. Both neural features exhibited high estimation accuracy of 3-DoF wrist torques, with an average [Formula: see text] of 0.76 ± 0.12 and normalized root mean square error of 11.4 ± 3.1%. These results demonstrated the efficiency of the proposed method in continuous estimation of 3-DoF wrist torques, which has the potential to advance dexterous myoelectric control based on neural information.

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

OBJECTIVE

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

METHODS

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

MAIN RESULTS

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

CONCLUSION AND SIGNIFICANCE

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

BioWolf16: a 16-channel, 24-bit, 4kSPS Ultra-Low Power Platform for Wearable Clinical-grade Bio-potential Parallel Processing and Streaming

Low-power wearable systems are essential for medical and industrial applications, but they face crucial implementation challenges when providing energy-efficient compact design while increasing the number of available channels, sampling rate and overall processing power. This work presents a small (39×41mm) wireless embedded low-power HMI device for ExG signals, offering up to 16 channels sampled at up to 4kSPS. By virtue of the high sampling rate and medical-grade signal quality (i.e. compliant with the IFCN standards), BioWolf16 is capable of accurate gesture recognition and enables the possibility to acquire data for neural spikes extraction. When employed over an EMG gesture recognition paradigm, the system achieves 90.24% classification accuracy over nine gestures (16 channels @4kSPS) while requiring only 16mW of power (57h of continuous operation) when deployed on Mr. Wolf MCU, part of the system architecture. The system can also provide up to 14h of real-time data streaming (4kSPS), which can further be extended to 23h when reducing the sampling rate to 1kSPS. Our results also demonstrate that this design outperforms many features of current state-of-the-art systems. Clinical Relevance - This work establishes that BioWolf16 is a wearable ultra-low power device enabling advanced multi-channel streaming and processing of medical-grade EMG signal, that can expand research opportunities and applications in healthcare and industrial scenarios.

Non-invasive analysis of motor unit activation during simultaneous and continuous wrist movements

Surface electromyography (EMG) signals have shown promising applications in human-machine interfacing (HMI) systems such as orthotics, prosthetics, and exoskeletons. Nevertheless, existing myoelectric control methods, generally based on time-domain or frequency-domain features, could not directly interpret neural commands. EMG decomposition techniques have become a prevailing solution to decode the motor neuron discharges from the spinal cord, whereas only single degree-of-freedom (DoF) movements are primarily involved in the current neural-based interfaces, resulting in limited intuitiveness and functionality. Here, we propose a non-invasive framework to analyze motor unit activities and estimate wrist torques during simultaneous contractions of multiple DoFs. Motor unit discharges were decoded from surface EMG signals and pooled into groups during sequential wrist movements. Then three neural features were extracted and linearly projected to the torques of multi-DoF tasks. On average, there were 4413 motor units identified for each motion with a PNR value of 25.82.9 dB. The neural features outperformed the classic EMG feature on the estimation accuracy with higher correlation coefficients and smoothness. These results demonstrate the feasibility and superiority of the proposed framework in kinetics estimation of simultaneous movements, extending the potential applications of surface EMG decomposition in human-machine interfaces.

Behavior of motor units during submaximal isometric contractions in chronically strength-trained individuals

Neural and morphological adaptations combine to underpin the enhanced muscle strength following prolonged exposure to strength training, although their relative importance remains unclear. We investigated the contribution of motor unit (MU) behavior and muscle size to submaximal force production in chronically strength-trained athletes (ST) versus untrained controls (UT). Sixteen ST (age: 22.9 ± 3.5 yr; training experience: 5.9 ± 3.5 yr) and 14 UT (age: 20.4 ± 2.3 yr) performed maximal voluntary isometric force (MViF) and ramp contractions (at 15%, 35%, 50%, and 70% MViF) with elbow flexors, whilst high-density surface electromyography (HDsEMG) was recorded from the biceps brachii (BB). Recruitment thresholds (RTs) and discharge rates (DRs) of MUs identified from the submaximal contractions were assessed. The neural drive-to-muscle gain was estimated from the relation between changes in force (ΔFORCE, i.e. muscle output) relative to changes in MU DR (ΔDR, i.e. neural input). BB maximum anatomical cross-sectional area (ACSA_MAX) was also assessed by MRI. MViF (+64.8% vs. UT, P < 0.001) and BB ACSA_MAX (+71.9%, P < 0.001) were higher in ST. Absolute MU RT was higher in ST (+62.6%, P < 0.001), but occurred at similar normalized forces. MU DR did not differ between groups at the same normalized forces. The absolute slope of the ΔFORCE - ΔDR relationship was higher in ST (+66.9%, P = 0.002), whereas it did not differ for normalized values. We observed similar MU behavior between ST athletes and UT controls. The greater absolute force-generating capacity of ST for the same neural input demonstrates that morphological, rather than neural, factors are the predominant mechanism for their enhanced force generation during submaximal efforts.NEW & NOTEWORTHY In this study, we observed that recruitment strategies and discharge characteristics of large populations of motor units identified from biceps brachii of strength-trained athletes were similar to those observed in untrained individuals during submaximal force tasks. We also found that for the same neural input, strength-trained athletes are able to produce greater absolute muscle forces (i.e., neural drive-to-muscle gain). This demonstrates that morphological factors are the predominant mechanism for the enhanced force generation during submaximal efforts.

Simultaneous and proportional control of wrist and hand movements by decoding motor unit discharges in real time

Objective.Surface electromyography (EMG) decomposition techniques can be used to establish human-machine interfacing (HMI), but most investigations are implemented offline due to the computational load of the approach. Here, we generalize the offline decomposition algorithm to identify the motor unit (MU) activities in real time, and we propose a MU-based approach for online simultaneous and proportional control of multiple motor tasks.Approach.High-density surface EMG signals recorded from forearm muscles were decomposed into motor unit spike trains (MUST) with the proposed decomposition method. The MUSTs were first pooled into clusters in the calibration phase and the cumulative discharges of active MUs in each group were extracted as the control signal for each motor task. Then the subjects were instructed to control a virtual cursor with multiple motor tasks involving grasp and wrist movements. Fifteen able-bodied subjects and two patients with limb deficiency participated in the experiments to validate the proposed control scheme.Main results.On average, over 20 MUSTs were identified in real time with an estimated decomposition accuracy > 85%. The cumulative discharge in each pool was highly correlated with the activation of the specific motion (R=0.93±0.05). Moreover, the proposed MU-based method had superior performance in online tests than conventional myo-control methods based on global EMG features.Significance.These results indicate the feasibility of real-time neural decoding in a non-invasive way. Moreover, the superior performance in online tests proves the potential of the MU-based approach for the simultaneous and proportional control, promoting the application of EMG decomposition for HMI systems.

Functional evaluation of triceps surae during heel rise test: from EMG frequency analysis to machine learning approach

Soleus muscle flap as coverage tissue is a possible surgical solution adopted to cover the wounds due to open fractures. Despite this procedure presents many clinical advantages, relatively poor information is available about the loss of functionality of triceps surae of the treated leg. In this study, a group of patients who underwent a soleus muscle flap surgical procedure has been analyzed through the heel rise test (HRT), in order to explore the triceps surae residual functionalities. A frequency band analysis was performed in order to assess whether the residual heads of triceps surae exhibit different characteristics with respect to both the non-treated lower limb and an age-matched control group. Then, an in-depth analysis based on a machine learning approach was proposed for discriminating between groups by generalizing across new unseen subjects. Experimental results showed the reliability of the proposed analyses for discriminating between-group at a specific time epoch and the high interpretability of the proposed machine learning algorithm allowed the temporal localization of the most discriminative frequency bands. Findings of this study highlighted that significant differences can be recognized in the myoelectric spectral characteristics between the treated and contralateral leg in patients who underwent soleus flap surgery. These experimental results may support the clinical decision-making for assessing triceps surae performance and for supporting the choice of treatment in plastic and reconstructive surgery. Graphical Abstract The Graphical abstract presents the scope of the proposed analysis of myoelectric signals of soleus and gastrocnemius muscles of patiens groups during Hell Rise Test, highlighting the applied methods and the obtained results.

Regional activation in the human longissimus thoracis pars lumborum muscle

KEY POINTS

•Longissimus activity in the lumbar region was measured using indwelling electromyography to characterize the territory of its motor units. •The distribution of motor units in the longissimus pars lumborum muscle was mainly grouped into two distinct regions. •Regional activation of the longissimus pars lumborum was also observed during functional tasks involving trunk movements. •The regional activation of the longissimus pars lumborum muscle may play a role in segmental stabilization of the lumbar spine.

ABSTRACT

The longissimus pars lumborum contributes to lumbar postural control and movement. While animal studies suggest a segmental control of this muscle, the territory of motor units constituting the human longissimus pars lumborum remains unknown. The aims of this study were to identify the localization of motor unit territories in the longissimus and assess the activation of this muscle during functional tasks. Eight healthy participants were recruited. During isometric back extension contractions, single motor-unit (at L1, L2, L3 and L4) and multi-unit indwelling recordings (at L1, L1-L2, L2, L2-L3, L3, L3-L4 and L4) were used to estimate motor unit territories in the longissimus pars lumborum based on the motor-unit spike-triggered averages from fine-wire electrodes. A series of functional tasks involving trunk and arm movements were also performed. A total of 73 distinct motor units were identified along the length of the longissimus: only two motor units spanned all recording sites. The majority of the recorded motor units had muscle fibres located in two main rostro-caudal territories (32 motor units spanned L1 to L3 and 30 spanned ∼L3 to L4) and 11 had muscle fibres outside these two main territories. We also observed distinct muscle activation between the rostral and caudal regions of the longissimus pars lumborum during a trunk rotation task. Our results show clear rostral and caudal motor unit territories in the longissimus pars lumborum muscle and suggest that the central nervous system can selectively activate regions of the superficial lumbar muscles to provide local stabilization of the spine.

Modelling the electrical activity of skeletal muscle tissue using a multi-domain approach

Electromyography (EMG) can be used to study the behaviour of the motor neurons and thus provides insights into the physiology of the central nervous system. However, due to the high complexity of neuromuscular control, EMG signals are challenging to interpret. While the exact knowledge of the excitation patterns of a specific muscle within an in vivo experimental setting remains elusive, simulations allow to systematically investigate EMG signals in a controlled environment. Within this context, simulations can provide virtual EMG data, which, for example, can be used to validate and optimise signal analysis methods that aim to estimate the relationship between EMG signals and the output of motor neuron pools. However, since existing methods, which are employed to compute EMG signals, exhibit deficiencies with respect to the physical model itself as well as with respect to numerical aspects, we propose a novel homogenised continuum model that closely resolves the electro-physiological behaviour of skeletal muscle tissue. The proposed model is based on an extension of the well-established bidomain model and includes a biophysically detailed description of the electrical activity within the tissue, which is due to the depolarisation of the muscle fibre membranes. In contrast to all other published EMG models, which assume that the electrical potential field for each muscle fibre can be calculated independently, the proposed model assumes that the electrical potential in the muscle fibres is coupled to the electrical potential in the extracellular space. We show that the newly proposed model is able to simulate realistic EMG signals and demonstrate the potential to employ the predicted virtual EMG signal in order to evaluate the goodness of automated decomposition algorithms.

Compound maximal motor unit response is modulated by contraction intensity, but not contraction type in tibialis anterior

Determining a single compound maximal motor response (MMAX ) or an average superimposed MMAX response (MSUP ) are commonly used reference values in experiments eliciting raw electromyographic, motor evoked potentials, H-reflexes, and V-waves. However, existing literature is limited in detailing the most appropriate method to normalize these electrophysiological measures. Due to the accessibility of assessment from a cortical and spinal perspective, the tibialis anterior is increasingly used in literature and hence investigated in this study. The aims of the present study were to examine the differences and level of agreement in MMAX /MSUP under different muscle actions and contraction intensities. Following a familiarization session, 22 males visited the laboratory on a single occasion. MMAX was recorded under 10% isometric and 25% and 100% shortening and lengthening maximal voluntary contractions (MVC) at an angular velocity of 15° sec-1 . MSUP was also recorded during 100% shortening and lengthening with an average of five responses recorded. There were no differences in MMAX or MSUP between contraction types. All variables showed large, positive correlations (P < 0.001, r2  ≥ 0.64). MMAX amplitude was larger (P < 0.001) at 100% shortening and lengthening intensity compared to MMAX amplitude at 10% isometric and 25% lengthening MVC. Bland-Altman plots revealed a bias toward higher MMAX at the higher contraction intensities. Despite MSUP being significantly smaller than MMAX (P < 0.001) at 100% MVC, MSUP showed a large positive correlation (P < 0.001, r2  ≥ 0.64) with all variables. It is our recommendation that MMAX should be recorded at specific contraction intensity but not necessarily a specific contraction type.

Higher muscle fiber conduction velocity and early rate of torque development in chronically strength-trained individuals

Strength-trained individuals (ST) develop greater levels of force compared with untrained subjects. These differences are partly of neural origin and can be explained by training-induced changes in the neural drive to the muscles. In the present study we hypothesize a greater rate of torque development (RTD) and faster recruitment of motor units with greater muscle fiber conduction velocity (MFCV) in ST compared with a control cohort. MFCV was assessed during maximal voluntary isometric explosive contractions of the elbow flexors in eight ST and eight control individuals. MFCV was estimated from high-density surface electromyogram recordings (128 electrodes) in intervals of 50 ms starting from the onset of the electromyogram. RTD and MFCV were computed and normalized to their maximal voluntary torque (MVT) values. The explosive torque of the ST was greater than in the control group in all time intervals analyzed ( P < 0.001). The absolute MFCV values were also greater for the ST than for controls at all time intervals ( P < 0.001). ST also achieved greater normalized RTD in the first 50 ms of contraction [887.6 (152) vs. 568.5 (148.66)%MVT/s, mean (SD), P < 0.001] and normalized MFCV before the rise in force compared with controls. We have shown for the first time that ST can recruit motor units with greater MFCV in a shorter amount of time compared with untrained subjects during maximal voluntary isometric explosive contractions.

NEW & NOTEWORTHY Strength-trained individuals show neuromuscular adaptations. These adaptations have been partly related to changes in the neural drive to the muscles. Here, we show for the first time that during the initial phase of a maximal isometric explosive contraction, strength-trained individuals achieve higher levels of force and recruit motor units with greater conduction velocities.

Neurophysiological Mechanisms Underpinning Stretch-Induced Force Loss

It is well known that prolonged passive muscle stretch reduces maximal muscle force production. There is a growing body of evidence suggesting that adaptations occurring within the nervous system play a major role in this stretch-induced force reduction. This article reviews the existing literature, and some new evidence, regarding acute neurophysiological changes in response to passive muscle stretching. We discuss the possible contribution of supra-spinal and spinal structures to the force reduction after passive muscle stretch. In summary, based on the recent evidence reviewed we propose a new hypothesis that a disfacilitation occurring at the motoneuronal level after passive muscle stretch is a major factor affecting the neural efferent drive to the muscle and, subsequently, its ability to produce maximal force.

Robust and accurate decoding of motoneuron behaviour and prediction of the resulting force output

KEY POINTS

The spinal alpha motoneuron is the only cell in the human CNS whose discharge can be routinely recorded in humans. We have reengineered motor unit collection and decomposition approaches, originally developed in humans, to measure the neural drive to muscle and estimate muscle force generation in the in vivo cat model. Experimental, computational, and predictive approaches are used to demonstrate the validity of this approach across a wide range of modes to activate the motor pool. The utility of this approach is shown through the ability to track individual motor units across trials, allowing for better predictions of muscle force than the electromyography signal, and providing insights in to the stereotypical discharge characteristics in response to synaptic activation of the motor pool. This approach now allows for a direct link between the intracellular data of single motoneurons, the discharge properties of motoneuron populations, and muscle force generation in the same preparation.

ABSTRACT

The discharge of a spinal alpha motoneuron and the resulting contraction of its muscle fibres represents the functional quantum of the motor system. Recent advances in the recording and decomposition of the electromyographic signal allow for the identification of several tens of concurrently active motor units. These detailed population data provide the potential to achieve deep insights into the synaptic organization of motor commands. Yet most of our understanding of the synaptic input to motoneurons is derived from intracellular recordings in animal preparations. Thus, it is necessary to extend the new electrode and decomposition methods to recording of motor unit populations in these same preparations. To achieve this goal, we use high-density electrode arrays and decomposition techniques, analogous to those developed for humans, to record and decompose the activity of tens of concurrently active motor units in a hindlimb muscle in the in vivo cat. Our results showed that the decomposition method in this animal preparation was highly accurate, with conventional two-source validation providing rates of agreement equal to or superior to those found in humans. Multidimensional reconstruction of the motor unit action potential provides the ability to accurately track the same motor unit across multiple contractions. Additionally, correlational analyses demonstrate that the composite spike train provides better estimates of whole muscle force than conventional estimates obtained from the electromyographic signal. Lastly, stark differences are observed between the modes of activation, in particular tendon vibration produced quantal interspike intervals at integer multiples of the vibration period.

Excitability and firing behavior of single slow motor axons transmitting natural repetitive firing of human motoneurons

Excitability of motor axons is critically important for realizing their main function, i.e., transmitting motoneuron firing to muscle fibers. The present study was designed to explore excitability recovery and firing behavior in single slow axons transmitting human motoneuron firing during voluntary muscle contractions. The abductor digiti minimi, flexor carpi ulnaris, and tibialis anterior were investigated during threshold stimulation of corresponding motor nerves. Motor unit (MU) firing index in response to testing volleys evoking M-responses was used as a physiological measure of axonal excitability and its changes throughout a target interspike interval (ISI) were explored. It was shown that axons displayed an early irresponsive period (within the first ~2-5 ms of a target ISI) that was followed by a responsive period (for the next 5-17 ms of the ISI), in which MUs fired axonal doublets, and a later irresponsive period. At the beginning of the responsive period, M-responses showed small latency delays. However, since at that ISI moment, MUs displayed excitability recovery with high firing index, slight latency changes may be considered as a functionally insignificant phenomenon. The duration of axonal doublet ISIs did not depend on motoneuron firing frequencies (range 4.3-14.6 imp/s). The question of whether or not traditionally described axonal recovery excitability cycle is realistic in natural motor control is discussed. In conclusion, the present approach, exploring, for the first time, excitability recovery in single slow axons during motoneuron natural activation, can provide further insight into axonal firing behavior in normal states and diseases.NEW & NOTEWORTHY Excitability of single slow axons was estimated by motor unit firing index in response to motor nerve stimulation, and its changes throughout a target interspike interval were explored during transmitting human motoneuron natural firing. It was found that axons exhibited early irresponsive, responsive, and later irresponsive periods. Findings question whether the traditionally described axonal excitability recovery cycle is realistic in natural motor control.

Associations between motor unit action potential parameters and surface EMG features

The surface interference EMG signal provides some information on the neural drive to muscles. However, the association between neural drive to muscle and muscle activation has long been debated with controversial indications due to the unavailability of motor unit population data. In this study, we clarify the potential and limitations of interference EMG analysis to infer motor unit recruitment strategies with an experimental investigation of several concurrently active motor units and of the associated features of the surface EMG. For this purpose, we recorded high-density surface EMG signals during linearly increasing force contractions of the tibialis anterior muscle, up to 70% of maximal force. The recruitment threshold (RT), conduction velocity (MUCV), median frequency (MDF_MU), and amplitude (RMS_MU) of action potentials of 587 motor units from 13 individuals were assessed and associated with features of the interference EMG. MUCV was positively associated with RT (R² = 0.64 ± 0.14), whereas MDF_MU and RMS_MU showed a weaker relation with RT (R² = 0.11 ± 0.11 and 0.39 ± 0.24, respectively). Moreover, the changes in average conduction velocity estimated from the interference EMG predicted well the changes in MUCV (R² = 0.71), with a strong association to ankle dorsiflexion force (R² = 0.81 ± 0.12). Conversely, both the average EMG MDF and RMS were poorly associated with motor unit recruitment. These results clarify the limitations of EMG spectral and amplitude analysis in inferring the neural strategies of muscle control and indicate that, conversely, the average conduction velocity could provide relevant information on these strategies.NEW & NOTEWORTHY The surface EMG provides information on the neural drive to muscles. However, the associations between EMG features and neural drive have been long debated due to unavailability of motor unit population data. Here, by using novel highly accurate decomposition of the EMG, we related motor unit population behavior to a wide range of voluntary forces. The results fully clarify the potential and limitation of the surface EMG to provide estimates of the neural drive to muscles.

Motor units in the human medial gastrocnemius muscle are not spatially localized or functionally grouped

KEY POINTS

Human medial gastrocnemius (MG) motor units (MUs) are thought to occupy small muscle territories or regions, with low-threshold units preferentially located distally. We used intramuscular recordings to measure the territory of muscle fibres from MG MUs and determine whether these MUs are grouped by recruitment threshold or joint action (ankle plantar flexion and knee flexion). The territory of MUs from the MG muscle varied from somewhat localized to highly distributed, with approximately half the MUs spanning at least half the length and width of the muscle. There was also no evidence of regional muscle activity based on MU recruitment thresholds or joint action. The CNS does not have the means to selectively activate regions of the MG muscle based on task requirements.

ABSTRACT

Human medial gastrocnemius (MG) motor units (MUs) are thought to occupy small muscle territories, with low-threshold units preferentially located distally. In this study, subjects (n = 8) performed ramped and sustained isometric contractions (ankle plantar flexion and knee flexion; range: ∼1-40% maximal voluntary contraction) and we measured MU territory size with spike-triggered averages from fine-wire electrodes inserted along the length (seven electrodes) or across the width (five electrodes) of the MG muscle. Of 69 MUs identified along the length of the muscle, 32 spanned at least half the muscle length (≥ 6.9 cm), 11 of which spanned all recording sites (13.6-17.9 cm). Distal fibres had smaller pennation angles (P < 0.05), which were accompanied by larger territories in MUs with fibres located distally (P < 0.05). There was no distal-to-proximal pattern of muscle activation in ramp contraction (P = 0.93). Of 36 MUs identified across the width of the muscle, 24 spanned at least half the muscle width (≥ 4.0 cm), 13 of which spanned all recording sites (8.0-10.8 cm). MUs were not localized (length or width) based on recruitment threshold or contraction type, nor was there a relationship between MU territory size and recruitment threshold (Spearman's rho = -0.20 and 0.13, P > 0.18). MUs in the human MG have larger territories than previously reported and are not localized based on recruitment threshold or joint action. This indicates that the CNS does not have the means to selectively activate regions of the MG muscle based on task requirements.

Limitations of Spectral Electromyogramic Analysis to Determine the Onset of Neuromuscular Fatigue Threshold during Incremental Ergometer Cycling

Recently, a new method has been proposed to detect the onset of neuromuscular fatigue during an incremental cycling test by assessing the changes in spectral electromyographic (sEMG) frequencies within individual exercise periods of the test. The method consists on determining the highest power output that can be sustained without a significant decrease in spectral frequencies. This study evaluated the validity of the new approach by assessing the changes in spectral indicators both throughout the whole test and within individual exercise periods of the test. Fourteen cyclists performed incremental cycle ergometer rides to exhaustion with bipolar surface EMG signals recorded from the vastus lateralis. The mean and median frequencies (Fmean and Fmedian, respectively) of the sEMG power spectrum were calculated. The main findings were: (1) Examination of spectral indicators within individual exercise periods of the test showed that neither Fmean nor Fmedian decreased significantly during the last (most fatiguing) exercise periods. (2) Examination of the whole incremental test showed that the behaviour of Fmean and Fmedian with increasing power output was highly inconsistent and varied greatly among subjects. (3) Over the whole incremental test, half of the participants exhibited a positive relation between spectral indicators and workload, whereas the other half demonstrated the opposite behavior. Collectively, these findings indicate that spectral sEMG indexes do not provide a reliable measure of the fatigue state of the muscle during an incremental cycling test. Moreover, it is concluded that it is not possible to determine the onset of neuromuscular fatigue during an incremental cycling test by examining spectral indicators within individual exercise periods of the test. Key pointsThe behaviour of spectral EMG indicators during the incremental test exhibited a high heterogeneity among individuals, with approximately half of the participants showing a positive relation between spectral indicators and workload and the other half showing the opposite behaviour.None of the spectral EMG indicators examined (Fmean nor Fmedian) decreased significantly between the ventilatory threshold and the highest power output.Examination of spectral indicators within individual exercise periods of the test showed that neither Fmean nor Fmedian decreased significantly during the last (most fatiguing) exercise periods.

The Magnitude of Peripheral Muscle Fatigue Induced by High and Low Intensity Single-Joint Exercise Does Not Lead to Central Motor Output Reductions in Resistance Trained Men

Purpose

To examine quadriceps muscle fatigue and central motor output during fatiguing single joint exercise at 40% and 80% maximal torque output in resistance trained men.

Method

Ten resistance trained men performed fatiguing isometric knee extensor exercise at 40% and 80% of maximal torque output. Maximal torque, rate of torque development, and measures of central motor output and peripheral muscle fatigue were recorded at two matched volumes of exercise, and after a final contraction performed to exhaustion. Central motor output was quantified from changes in voluntary activation, normalized surface electromyograms (EMG), and V-waves. Quadriceps muscle fatigue was assessed from changes in the size and shape of the resting potentiated twitch (Q._pot.tw). Central motor output during the exercise protocols was estimated from EMG and interpolated twitches applied during the task (VA_sub).

Results

Greater reductions in maximal torque and rate of torque development were observed during the 40% protocol (p<0.05). Maximal central motor output did not change for either protocol. For the 40% protocol reductions from pre-exercise in rate and amplitude variables calculated from the Q._pot.tw between 66.2 to 70.8% (p<0.001) exceeded those observed during the 80% protocol (p<0.01). V-waves only declined during the 80% protocol between 56.8 ± 35.8% to 53.6 ± 37.4% (p<0.05). At the end of the final 80% contraction VA_sub had increased from 91.2 ± 6.2% to 94.9 ± 4.7% (p = 0.005), but a greater increase was observed during the 40% contraction where VA_sub had increased from 67.1 ± 6.1% to 88.9 ± 9.6% (p<0.001).

Conclusion

Maximal central motor output in resistance trained men is well preserved despite varying levels of peripheral muscle fatigue. Upregulated central motor output during the 40% contraction protocol appeared to elicit greater peripheral fatigue. V-waves declines during the 80% protocol suggest intensity dependent modulation of the Ia afferent pathway.

Spatial variability in cortex-muscle coherence investigated with magnetoencephalography and high-density surface electromyography

Cortex-muscle coherence (CMC) reflects coupling between magnetoencephalography (MEG) and surface electromyography (sEMG), being strongest during isometric contraction but absent, for unknown reasons, in some individuals. We used a novel nonmagnetic high-density sEMG (HD-sEMG) electrode grid (36 mm × 12 mm; 60 electrodes separated by 3 mm) to study effects of sEMG recording site, electrode derivation, and rectification on the strength of CMC. Monopolar sEMG from right thenar and 306-channel whole-scalp MEG were recorded from 14 subjects during 4-min isometric thumb abduction. CMC was computed for 60 monopolar, 55 bipolar, and 32 Laplacian HD-sEMG derivations, and two derivations were computed to mimic "macroscopic" monopolar and bipolar sEMG (electrode diameter 9 mm; interelectrode distance 21 mm). With unrectified sEMG, 12 subjects showed statistically significant CMC in 91-95% of the HD-sEMG channels, with maximum coherence at ∼25 Hz. CMC was about a fifth stronger for monopolar than bipolar and Laplacian derivations. Monopolar derivations resulted in most uniform CMC distributions across the thenar and in tightest cortical source clusters in the left rolandic hand area. CMC was 19-27% stronger for HD-sEMG than for "macroscopic" monopolar or bipolar derivations. EMG rectification reduced the CMC peak by a quarter, resulted in a more uniformly distributed CMC across the thenar, and provided more tightly clustered cortical sources than unrectifed sEMGs. Moreover, it revealed CMC at ∼12 Hz. We conclude that HD-sEMG, especially with monopolar derivation, can facilitate detection of CMC and that individual muscle anatomy cannot explain the high interindividual CMC variability.

Power spectrum of the rectified EMG: when and why is rectification beneficial for identifying neural connectivity?

OBJECTIVE

The identification of common oscillatory inputs to motor neurons in the electromyographic (EMG) signal power spectrum is often preceded by EMG rectification for enhancing the low-frequency oscillatory components. However, rectification is a nonlinear operator and its influence on the EMG signal spectrum is not fully understood. In this study, we aim at determining when EMG rectification is beneficial in the study of oscillatory inputs to motor neurons.

APPROACH

We provide a full mathematical description of the power spectrum of the rectified EMG signal and the influence of the average shape of the motor unit action potentials on it. We also provide a validation of these theoretical results with both simulated and experimental EMG signals.

MAIN RESULTS

Simulations using an advanced computational model and experimental results demonstrated the accuracy of the theoretical derivations on the effect of rectification on the EMG spectrum. These derivations proved that rectification is beneficial when assessing the strength of low-frequency (delta and alpha bands) common synaptic inputs to the motor neurons, when the duration of the action potentials is short, and when the level of cancellation is relatively low. On the other hand, rectification may distort the estimation of common synaptic inputs when studying higher frequencies (beta and gamma), in a way dependent on the duration of the action potentials, and may introduce peaks in the coherence function that do not correspond to physiological shared inputs.

SIGNIFICANCE

This study clarifies the conditions when rectifying the surface EMG is appropriate for studying neural connectivity.

Neural adaptations in isometric contractions with EMG and force biofeedback

This study aimed to evaluate the quadriceps femoris neural adaptations during isometric contractions using force and electromyogram (EMG) signals as visual biofeedback. Forty-two participants were randomly assigned to three groups: EMG group, tested with EMG biofeedback; Force group, tested with force biofeedback; and Control group, tested without biofeedback. Evaluations were performed pre (baseline) and post-tests to determine the maximum force and EMG amplitude during maximal voluntary isometric contraction (MVIC). The tests consisted of series of MVICs in which the participants were encouraged to surpass the force or EMG thresholds determined at baseline. The vastus lateralis EMG amplitude and knee extensor force increased significantly in all groups when compared the baseline and post-test evaluations values (p < .05). EMG percentage gain was significantly different between Force and Control groups (p < .01), while force percentage gain was not different between groups. Force biofeedback was more effective in producing neural adaptations.

Power spectrum of the rectified EMG: influence of motor unit action potential shapes

The rectification of EMG signals is a preprocessing method widely used for inferring neural connectivity by coherence analysis. The assumption for the use of this non-linear operator is that it enhances the neural information in the signal, i.e. the motor unit spike trains. However, because of non-linearity, it is difficult to predict the effect of rectification on the EMG power spectrum. In this study, we analyze the influence of the motor unit action potential properties on spectral content of the rectified EMG. The results show that changes in the action potential waveforms have a strong influence on the rectified EMG power spectrum, with an effect on estimated coherence functions. Knowledge on the properties of action potentials may be necessary for properly comparing the rectified EMG power spectrum across conditions.

The extraction of neural strategies from the surface EMG: an update

A surface EMG signal represents the linear transformation of motor neuron discharge times by the compound action potentials of the innervated muscle fibers and is often used as a source of information about neural activation of muscle. However, retrieving the embedded neural code from a surface EMG signal is extremely challenging. Most studies use indirect approaches in which selected features of the signal are interpreted as indicating certain characteristics of the neural code. These indirect associations are constrained by limitations that have been detailed previously (Farina D, Merletti R, Enoka RM. J Appl Physiol 96: 1486-1495, 2004) and are generally difficult to overcome. In an update on these issues, the current review extends the discussion to EMG-based coherence methods for assessing neural connectivity. We focus first on EMG amplitude cancellation, which intrinsically limits the association between EMG amplitude and the intensity of the neural activation and then discuss the limitations of coherence methods (EEG-EMG, EMG-EMG) as a way to assess the strength of the transmission of synaptic inputs into trains of motor unit action potentials. The debated influence of rectification on EMG spectral analysis and coherence measures is also discussed. Alternatively, there have been a number of attempts to identify the neural information directly by decomposing surface EMG signals into the discharge times of motor unit action potentials. The application of this approach is extremely powerful, but validation remains a central issue.

Comparison of the power spectral changes of the voluntary surface electromyogram and M wave during intermittent maximal voluntary contractions

INTRODUCTION

To compare the power spectral changes of the voluntary surface electromyogram (sEMG) and of the compound action potential (M wave) in the vastus medialis and vastus lateralis muscles during fatiguing contractions.

METHODS

Interference sEMG and force were recorded during 48 intermittent 3-s isometric maximal voluntary contractions (MVC) from 13 young, healthy subjects. M waves and twitches were evoked using supramaximal femoral nerve stimulation between the successive MVCs. Mean frequency (F mean), and median frequency were calculated from the sEMG and M waves. Muscle fiber conduction velocity (MFCV) was computed by cross-correlation.

RESULTS

The power spectral shift to lower frequencies was significantly greater for the voluntary sEMG than for the M waves (P < 0.05). Over the fatiguing protocol, the overall average decrease in MFCV (~25%) was comparable to that of sEMG F mean (~22%), but significantly greater than that of M-wave F mean (~9%) (P < 0.001). The mean decline in MFCV was highly correlated with the mean decreases in both sEMG and M-wave F mean.

CONCLUSIONS

The present findings indicated that, as fatigue progressed, central mechanisms could enhance the relative weight of the low-frequency components of the voluntary sEMG power spectrum, and/or the end-of-fiber (non-propagating) components could reduce the sensitivity of the M-wave spectrum to changes in conduction velocity.

Motor unit

Movement is accomplished by the controlled activation of motor unit populations. Our understanding of motor unit physiology has been derived from experimental work on the properties of single motor units and from computational studies that have integrated the experimental observations into the function of motor unit populations. The article provides brief descriptions of motor unit anatomy and muscle unit properties, with more substantial reviews of motoneuron properties, motor unit recruitment and rate modulation when humans perform voluntary contractions, and the function of an entire motor unit pool. The article emphasizes the advances in knowledge on the cellular and molecular mechanisms underlying the neuromodulation of motoneuron activity and attempts to explain the discharge characteristics of human motor units in terms of these principles. A major finding from this work has been the critical role of descending pathways from the brainstem in modulating the properties and activity of spinal motoneurons. Progress has been substantial, but significant gaps in knowledge remain.

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

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

Recruitment of motor units in two fascicles of the semispinalis cervicis muscle

This study investigated the behavior of motor units in the semispinalis cervicis muscle. Intramuscular EMG recordings were obtained unilaterally at levels C2 and C5 in 15 healthy volunteers (8 men, 7 women) who performed isometric neck extensions at 5%, 10%, and 20% of the maximal force [maximum voluntary contraction (MVC)] for 2 min each and linearly increasing force contractions from 0 to 30% MVC over 3 s. Individual motor unit action potentials were identified. The discharge rate and interspike interval variability of the motor units in the two locations did not differ. However, the recruitment threshold of motor units detected at C2 (n = 16, mean ± SD: 10.3 ± 6.0% MVC) was greater than that of motor units detected at C5 (n = 92, 6.9 ± 4.3% MVC) (P < 0.01). A significant level of short-term synchronization was identified in 246 of 307 motor unit pairs when computed within one spinal level but only in 28 of 110 pairs of motor units between the two levels. The common input strength, which quantifies motor unit synchronization, was greater for pairs within one level (0.47 ± 0.32) compared with pairs between levels (0.09 ± 0.07) (P < 0.05). In a second experiment on eight healthy subjects, interference EMG was recorded from the same locations during a linearly increasing force contraction from 0 to 40% MVC and showed significantly greater EMG amplitude at C5 than at C2. In conclusion, synaptic input is distributed partly independently and nonuniformly to different fascicles of the semispinalis cervicis muscle.

Neuromuscular adjustments that constrain submaximal EMG amplitude at task failure of sustained isometric contractions

The amplitude of the surface EMG does not reach the level achieved during a maximal voluntary contraction force at the end of a sustained, submaximal contraction, despite near-maximal levels of voluntary effort. The depression of EMG amplitude may be explained by several neural and muscular adjustments during fatiguing contractions, including decreased net neural drive to the muscle, changes in the shape of the motor unit action potentials, and EMG amplitude cancellation. The changes in these parameters for the entire motor unit pool, however, cannot be measured experimentally. The present study used a computational model to simulate the adjustments during sustained isometric contractions and thereby determine the relative importance of these factors in explaining the submaximal levels of EMG amplitude at task failure. The simulation results indicated that the amount of amplitude cancellation in the simulated EMG (∼ 40%) exhibited a negligible change during the fatiguing contractions. Instead, the main determinant of the submaximal EMG amplitude at task failure was a decrease in muscle activation (number of muscle fiber action potentials), due to a reduction in the net synaptic input to motor neurons, with a lesser contribution from changes in the shape of the motor unit action potentials. Despite the association between the submaximal EMG amplitude and reduced muscle activation, the deficit in EMG amplitude at task failure was not consistently associated with the decrease in neural drive (number of motor unit action potentials) to the muscle. This indicates that the EMG amplitude cannot be used as an index of neural drive.

Fluctuations in isometric muscle force can be described by one linear projection of low-frequency components of motor unit discharge rates

The aim of the study was to investigate the relation between linear transformations of motor unit discharge rates and muscle force. Intramuscular (wire electrodes) and high-density surface EMG (13 x 5 electrode grid) were recorded from the abductor digiti minimi muscle of eight healthy men during 60 s contractions at 5%, 7.5% and 10% of the maximal force. Spike trains of a total of 222 motor units were identified from the EMG recordings with decomposition algorithms. Principal component analysis of the smoothed motor unit discharge rates indicated that one component (first common component, FCC) described 44.2 +/- 7.5% of the total variability of the smoothed discharge rates when computed over the entire contraction interval and 64.3 +/- 10.2% of the variability when computed over 5 s intervals. When the FCC was computed from four or more motor units per contraction, it correlated with the force produced by the muscle (62.7 +/- 10.1%) by a greater degree (P < 0.001) than the smoothed discharge rates of individual motor units (41.4 +/- 7.8%). The correlation between FCC and the force signal increased up to 71.8 +/- 13.1% when the duration and the shape of the smoothing window for discharge rates were similar to the average motor unit twitch force. Moreover, the coefficients of variation (CoV) for the force and for the FCC signal were correlated in all subjects (R(2) range = 0.14-0.56; P < 0.05) whereas the CoV for force was correlated to the interspike interval variability in only one subject (R(2) = 0.12; P < 0.05). Similar results were further obtained from measures on the tibialis anterior muscle of an additional eight subjects during contractions at forces up to 20% of the maximal force (e.g. FCC explained 59.8 +/- 11.0% of variability of the smoothed discharge rates). In conclusion, one signal captures most of the underlying variability of the low-frequency components of motor unit discharge rates and explains large part of the fluctuations in the motor output during isometric contractions.

Relationships between motor unit size and recruitment threshold in older adults: implications for size principle

As a part of the aging process, motor unit reorganization occurs in which small motoneurons reinnervate predominantly fast-twitch muscle fibers that have lost their innervation. We examined the relationship between motor unit size and the threshold force for recruitment in two muscles to determine whether older individuals might develop an alternative pattern of motor unit activation. Young and older adults performed isometric contractions ranging from 0 to 50% of maximal voluntary contraction in both the first dorsal interosseous (FDI) and tibialis anterior (TA) muscles. Muscle fiber action potentials were recorded with an intramuscular needle electrode and motor unit size was computed using spike-triggered averaging of the global EMG signal (macro EMG), which was also obtained from the intramuscular needle electrode. As expected, older individuals exhibited larger motor units than young subjects in both the FDI and the TA. However, moderately strong correlations were obtained for the macro EMG amplitude versus recruitment threshold relationship in both the young and older adults within both muscles, suggesting that the size principle of motor unit recruitment seems to be preserved in older adults.

Analysis of motor units with high-density surface electromyography

Although the behaviour of individual motor units is classically studied with intramuscular EMG, recently developed techniques allow its analysis also from EMG recorded in multiple locations over the skin surface (high-density surface EMG). The analysis of motor units from the surface EMG is useful when the insertion of needles is not desirable or not possible. Moreover, surface EMG allows the measure of motor unit properties which are difficult to assess with invasive technology (e.g., muscle fiber conduction velocity or location of innervation zones) and may increase the number of detectable motor units with respect to selective intramuscular recordings. Although some limitations remain, both the discharge pattern and muscle fiber properties of individual motor units can currently be analyzed non-invasively. This review presents the conditions and methodologies which allow the investigation of motor units with surface EMG.