Two-dimensional surface EMG: The effects of electrode size, interelectrode distance and image truncation

Body Surface Potential Mapping: A Perspective on High-Density Cutaneous Electrophysiology

The electrophysiological signals recorded by cutaneous electrodes, known as body surface potentials (BSPs), are widely employed biomarkers in medical diagnosis. Despite their widespread application and success in detecting various conditions, the poor spatial resolution of traditional BSP measurements poses a limit to their diagnostic potential. Advancements in the field of bioelectronics have facilitated the creation of compact, high-quality, high-density recording arrays for cutaneous electrophysiology, allowing detailed spatial information acquisition as BSP maps (BSPMs). Currently, the design of electrode arrays for BSP mapping lacks a standardized framework, leading to customizations for each clinical study, limiting comparability, reproducibility, and transferability. This perspective proposes preliminary design guidelines, drawn from existing literature, rooted solely in the physical properties of electrophysiological signals and mathematical principles of signal processing. These guidelines aim to simplify and generalize the optimization process for electrode array design, fostering more effective and applicable clinical research. Moreover, the increased spatial information obtained from BSPMs introduces interpretation challenges. To mitigate this, two strategies are outlined: observational transformations that reconstruct signal sources for intuitive comprehension, and machine learning-driven diagnostics. BSP mapping offers significant advantages in cutaneous electrophysiology with respect to classic electrophysiological recordings and is expected to expand into broader clinical domains in the future.

Tutorial. Frequency analysis of the surface EMG signal: Best practices

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.

Reduced variability of erector spinae activity in people with chronic low back pain when performing a functional 3D lifting task

BACKGROUND

Chronic low back pain (LBP) is a leading cause of disability, which is exacerbated in some by repeated lifting. Electromyography (EMG) assessments of isolated erector spinae (ES) regions during lifting identified conflicting results. Here, high-density EMG comprehensively assesses the lumbar and thoracolumbar ES activity in people with and without LBP performing a multiplanar lifting task.

METHODS

Four high-density EMG grids (two bilaterally) and reflective markers were affixed over the ES and trunk to record muscle activity and trunk kinematics respectively. The task involved cyclical lifting of a 5 kg box for ∼7 min from a central shelf to five peripheral shelves, returning to the first between movements, while monitoring perceived exertion.

RESULTS

Fourteen LBP (26.9 ± 11.1 years) and 15 control participants (32.1 ± 14.6 years) completed the study. LBP participants used a strategy characterised by less diffuse and more cranially-focussed ES activity (P < 0.05). LBP participants also exhibited less variation in ES activity distribution between sides during movements distal to the central shelf (P < 0.05). There were few consistent differences in kinematics, but LBP participants reported greater exertion (P < 0.05).

CONCLUSION

In the presence of mild LBP, participants used a less variable motor strategy, with less diffuse and more cranially-focussed ES activity; this motor strategy occurred concomitantly with increased exertion while completing this dynamic task.

High Density Body Surface Potential Mapping with Conducting Polymer-Eutectogel Electrode Arrays for ECG imaging

Electrocardiography imaging (ECGi) is a non-invasive inverse reconstruction procedure which employs body surface potential maps (BSPM) obtained from surface electrode array measurements to improve the spatial resolution and interpretability of conventional electrocardiography (ECG) for the diagnosis of cardiac dysfunction. ECGi currently lacks precision, which has prevented its adoption in clinical setups. The introduction of high-density electrode arrays could increase ECGi reconstruction accuracy but is not attempted before due to manufacturing and processing limitations. Advances in multiple fields have now enabled the implementation of such arrays which poses questions on optimal array design parameters for ECGi. In this work, a novel conducting polymer electrode manufacturing process on flexible substrates is proposed to achieve high-density, mm-sized, conformable, long-term, and easily attachable electrode arrays for BSPM with parameters optimally selected for ECGi applications. Temporal, spectral, and correlation analysis are performed on a prototype array demonstrating the validity of the chosen parameters and the feasibility of high-density BSPM, paving the way for ECGi devices fit for clinical application.

Formation of Anisotropic Conducting Interlayer for High-Resolution Epidermal Electromyography Using Mixed-Conducting Particulate Composite

Epidermal electrophysiology is a non-invasive method used in research and clinical practices to study the electrical activity of the brain, heart, nerves, and muscles. However, electrode/tissue interlayer materials such as ionically conducting pastes can negatively affect recordings by introducing lateral electrode-to-electrode ionic crosstalk and reducing spatial resolution. To overcome this issue, biocompatible, anisotropic-conducting interlayer composites (ACI) that establish an electrically anisotropic interface with the skin are developed, enabling the application of dense cutaneous sensor arrays. High-density, conformable electrodes are also microfabricated that adhere to the ACI and follow the curvilinear surface of the skin. The results show that ACI significantly enhances the spatial resolution of epidermal electromyography (EMG) recording compared to conductive paste, permitting the acquisition of single muscle action potentials with distinct spatial profiles. The high-density EMG in developing mice, non-human primates, and humans is validated. Overall, high spatial-resolution epidermal electrophysiology enabled by ACI has the potential to advance clinical diagnostics of motor system disorders and enhance data quality for human-computer interface applications.

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.

Comparison of Two Types of Electrodes for Measuring Submental Muscle Activity During Swallowing

PURPOSE

This study aimed to investigate the potential of a newly developed small electrode to accurately record muscle activity during swallowing.

MATERIAL AND METHODS

This study included 31 healthy participants. The participants underwent swallowing trials with three types of material. The recordings involved the following conditions: 1) swallowing saliva, 2) swallowing 3 mL water, and 3) swallowing 5 mL water. Two types of electrodes, a conventional electrode (CE) and a newly developed small electrode (NE), were symmetrically positioned on the skin over the suprahyoid muscle group, starting from the center. From the surface electromyography data, the swallowing duration (s), peak amplitude, and rising time (duration from swallowing onset to peak amplitude: s) were measured. Additionally, the equivalence of characteristics of the waveform of muscle activities was calculated by using the variance in both the upper and lower confidence limits in duration and rising time.

RESULTS

No significant differences in baseline, swallowing duration or rising time between the CE and NE were observed for any swallowing material. The peak amplitude was significantly higher for the NE than for the CE for all swallowing materials. The CE and NE displayed no significant difference in the equivalence of characteristics of the waveform of muscle activities for any swallowing material.

CONCLUSIONS

The gold-plated small electrodes utilized in this study indicated the ability to record the same characteristics of muscle activity as conventional electrodes. Moreover, it was able to capture the muscle activity of each muscle group with improved sensitivity in a narrow area, such as under the submandibular region, with more precision than that of conventional electrodes.

Tutorial. Surface electromyogram (sEMG) amplitude estimation: Best practices

This tutorial intends to provide insight, instructions and "best practices" for those who are novices-including clinicians, engineers and non-engineers-in extracting electromyogram (EMG) amplitude from the bipolar surface EMG (sEMG) signal of voluntary contractions. A brief discussion of sEMG amplitude extraction from high density sEMG (HDsEMG) arrays and feature extraction from electrically elicited contractions is also provided. This tutorial attempts to present its main concepts in a straightforward manner that is accessible to novices in the field not possessing a wide range of technical background (if any) in this area. Surface EMG amplitude, also referred to as the sEMG envelope [often implemented as root mean square (RMS) sEMG or average rectified value (ARV) sEMG], quantifies the voltage variation of the sEMG signal and is grossly related to the overall neural excitation of the muscle and to peripheral parameters. The tutorial briefly reviews the physiological origin of the voluntary sEMG signal and sEMG recording, including electrode configurations, sEMG signal transduction, electronic conditioning and conversion by an analog-to-digital converter. These topics have been covered in greater detail in prior tutorials in this series. In depth descriptions of state-of-the-art methods for computing sEMG amplitude are then provided, including guidance on signal pre-conditioning, absolute value vs. square-law detection, selection of appropriate sEMG amplitude smoothing filters and attenuation of measurement noise. The tutorial provides a detailed list of best practices for sEMG amplitude estimation.

Wearable bioelectronics fabricated in situ on skins

In recent years, wearable bioelectronics has rapidly expanded for diagnosing, monitoring, and treating various pathological conditions from the skin surface. Although the devices are typically prefabricated as soft patches for general usage, there is a growing need for devices that are customized in situ to provide accurate data and precise treatment. In this perspective, the state-of-the-art in situ fabricated wearable bioelectronics are summarized, focusing primarily on Drawn-on-Skin (DoS) bioelectronics and other in situ fabrication methods. The advantages and limitations of these technologies are evaluated and potential future directions are suggested for the widespread adoption of these technologies in everyday life.

Detection and Reconstruction of Poor-Quality Channels in High-Density EMG Array Measurements

High-density electromyography (HD-EMG) arrays allow for the study of muscle activity in both time and space by recording electrical potentials produced by muscle contractions. HD-EMG array measurements are susceptible to noise and artifacts and frequently contain some poor-quality channels. This paper proposes an interpolation-based method for the detection and reconstruction of poor-quality channels in HD-EMG arrays. The proposed detection method identified artificially contaminated channels of HD-EMG for signal-to-noise ratio (SNR) levels 0 dB and lower with ≥99.9% precision and ≥97.6% recall. The interpolation-based detection method had the best overall performance compared with two other rule-based methods that used the root mean square (RMS) and normalized mutual information (NMI) to detect poor-quality channels in HD-EMG data. Unlike other detection methods, the interpolation-based method evaluated channel quality in a localized context in the HD-EMG array. For a single poor-quality channel with an SNR of 0 dB, the F1 scores for the interpolation-based, RMS, and NMI methods were 99.1%, 39.7%, and 75.9%, respectively. The interpolation-based method was also the most effective detection method for identifying poor channels in samples of real HD-EMG data. F1 scores for the detection of poor-quality channels in real data for the interpolation-based, RMS, and NMI methods were 96.4%, 64.5%, and 50.0%, respectively. Following the detection of poor-quality channels, 2D spline interpolation was used to successfully reconstruct these channels. Reconstruction of known target channels had a percent residual difference (PRD) of 15.5 ± 12.1%. The proposed interpolation-based method is an effective approach for the detection and reconstruction of poor-quality channels in HD-EMG.

Customizable, reconfigurable, and anatomically coordinated large-area, high-density electromyography from drawn-on-skin electrode arrays

Accurate anatomical matching for patient-specific electromyographic (EMG) mapping is crucial yet technically challenging in various medical disciplines. The fixed electrode construction of multielectrode arrays (MEAs) makes it nearly impossible to match an individual's unique muscle anatomy. This mismatch between the MEAs and target muscles leads to missing relevant muscle activity, highly redundant data, complicated electrode placement optimization, and inaccuracies in classification algorithms. Here, we present customizable and reconfigurable drawn-on-skin (DoS) MEAs as the first demonstration of high-density EMG mapping from in situ-fabricated electrodes with tunable configurations adapted to subject-specific muscle anatomy. The DoS MEAs show uniform electrical properties and can map EMG activity with high fidelity under skin deformation-induced motion, which stems from the unique and robust skin-electrode interface. They can be used to localize innervation zones (IZs), detect motor unit propagation, and capture EMG signals with consistent quality during large muscle movements. Reconfiguring the electrode arrangement of DoS MEAs to match and extend the coverage of the forearm flexors enables localization of the muscle activity and prevents missed information such as IZs. In addition, DoS MEAs customized to the specific anatomy of subjects produce highly informative data, leading to accurate finger gesture detection and prosthetic control compared with conventional technology.

Biased instantaneous regional muscle activation maps: Embedded fuzzy topology and image feature analysis

The instantaneous spatial representation of electrical propagation produced by muscle contraction may introduce bias in surface electromyographical (sEMG) activation maps. Here, we described the effect of instantaneous spatial representation (sEMG segmentation) on embedded fuzzy topological polyhedrons and image features extracted from sEMG activation maps. We analyzed 73,008 topographic sEMG activation maps from seven healthy participants (age 21.4 ± 1.5 years and body mass 74.5 ± 8.5 kg) who performed submaximal isometric plantar flexions with 64 surface electrodes placed over the medial gastrocnemius muscle. Window lengths of 50, 100, 150, 250, 500, and 1,000 ms and overlap of 0, 25, 50, 75, and 90% to change sEMG map generation were tested in a factorial design (grid search). The Shannon entropy and volume of global embedded tri-dimensional geometries (polyhedron projections), and the Shannon entropy, location of the center (LoC), and image moments of maps were analyzed. The polyhedron volume increased when the overlap was <25% and >75%. Entropy decreased when the overlap was <25% and >75% and when the window length was <100 ms and >500 ms. The LoC in the x-axis, entropy, and the histogram moments of maps showed effects for overlap (p < 0.001), while the LoC in the y-axis and entropy showed effects for both overlap and window length (p < 0.001). In conclusion, the instantaneous sEMG maps are first affected by outer parameters of the overlap, followed by the length of the window. Thus, choosing the window length and overlap parameters can introduce bias in sEMG activation maps, resulting in distorted regional muscle activation.

Wearable super-resolution muscle-machine interfacing

Muscles are the actuators of all human actions, from daily work and life to communication and expression of emotions. Myography records the signals from muscle activities as an interface between machine hardware and human wetware, granting direct and natural control of our electronic peripherals. Regardless of the significant progression as of late, the conventional myographic sensors are still incapable of achieving the desired high-resolution and non-invasive recording. This paper presents a critical review of state-of-the-art wearable sensing technologies that measure deeper muscle activity with high spatial resolution, so-called super-resolution. This paper classifies these myographic sensors according to the different signal types (i.e., biomechanical, biochemical, and bioelectrical) they record during measuring muscle activity. By describing the characteristics and current developments with advantages and limitations of each myographic sensor, their capabilities are investigated as a super-resolution myography technique, including: (i) non-invasive and high-density designs of the sensing units and their vulnerability to interferences, (ii) limit-of-detection to register the activity of deep muscles. Finally, this paper concludes with new opportunities in this fast-growing super-resolution myography field and proposes promising future research directions. These advances will enable next-generation muscle-machine interfaces to meet the practical design needs in real-life for healthcare technologies, assistive/rehabilitation robotics, and human augmentation with extended reality.

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

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

Topological supramolecular network enabled high-conductivity, stretchable organic bioelectronics

Intrinsically stretchable bioelectronic devices based on soft and conducting organic materials have been regarded as the ideal interface for seamless and biocompatible integration with the human body. A remaining challenge is to combine high mechanical robustness with good electrical conduction, especially when patterned at small feature sizes. We develop a molecular engineering strategy based on a topological supramolecular network, which allows for the decoupling of competing effects from multiple molecular building blocks to meet complex requirements. We obtained simultaneously high conductivity and crack-onset strain in a physiological environment, with direct photopatternability down to the cellular scale. We further collected stable electromyography signals on soft and malleable octopus and performed localized neuromodulation down to single-nucleus precision for controlling organ-specific activities through the delicate brainstem.

A Novel Methodology for the Synchronous Collection and Multimodal Visualization of Continuous Neurocardiovascular and Neuromuscular Physiological Data in Adults with Long COVID

Background: Reports suggest that adults with post-COVID-19 syndrome or long COVID may be affected by orthostatic intolerance syndromes, with autonomic nervous system dysfunction as a possible causal factor of neurocardiovascular instability (NCVI). Long COVID can also manifest as prolonged fatigue, which may be linked to neuromuscular function impairment (NMFI). The current clinical assessment for NCVI monitors neurocardiovascular performance upon the application of orthostatic stressors such as an active (i.e., self-induced) stand or a passive (tilt table) standing test. Lower limb muscle contractions may be important in orthostatic recovery via the skeletal muscle pump. In this study, adults with long COVID were assessed with a protocol that, in addition to the standard NCVI tests, incorporated simultaneous lower limb muscle monitoring for NMFI assessment. Methods: To conduct such an investigation, a wide range of continuous non-invasive biomedical sensing technologies were employed, including digital artery photoplethysmography for the extraction of cardiovascular signals, near-infrared spectroscopy for the extraction of regional tissue oxygenation in brain and muscle, and electromyography for assessment of timed muscle contractions in the lower limbs. Results: With the proposed methodology described and exemplified in this paper, we were able to collect relevant physiological data for the assessment of neurocardiovascular and neuromuscular functioning. We were also able to integrate signals from a variety of instruments in a synchronized fashion and visualize the interactions between different physiological signals during the combined NCVI/NMFI assessment. Multiple counts of evidence were collected, which can capture the dynamics between skeletal muscle contractions and neurocardiovascular responses. Conclusions: The proposed methodology can offer an overview of the functioning of the neurocardiovascular and neuromuscular systems in a combined NCVI/NMFI setup and is capable of conducting comparative studies with signals from multiple participants at any given time in the assessment. This could help clinicians and researchers generate and test hypotheses based on the multimodal inspection of raw data in long COVID and other cohorts.

Muscle-Specific High-Density Electromyography Arrays for Hand Gesture Classification

OBJECTIVE

Dexterous hand motion is critical for object manipulation. Electrophysiological studies of the hand are key to understanding its underlying mechanisms. High-density electromyography (HD-EMG) provides spatio-temporal information about the underlying electrical activity of muscles, which can be used in neurophysiological research, rehabilitation and control applications. However, existing EMG electrodes platforms are not muscle-specific, which makes the assessment of intrinsic hand muscles difficult.

METHODS

Muscle-specific flexible HD-EMG electrode arrays were developed to capture intrinsic hand muscle myoelectric activity during manipulation tasks. The arrays consist of 60 individual electrodes targeting 10 intrinsic hand muscles. Myoelectric activity was displayed as spatio-temporal amplitude maps to visualize muscle activation. Time-domain and temporal-spatial HD-EMG features were extracted to train cubic support vector machine machine-learning classifiers to classify the intended user motion.

RESULTS

Experimental data was collected from 5 subjects performing a range of 10 common hand motions. Spatio-temporal EMG maps showed distinct activation areas correlated to the muscles recruited during each movement. The thenar muscle fiber conduction velocity (CV) was estimated to be at 4.70.3 m/s for all subjects. Hand motions were successfully classified and average accuracy for all subjects was directly related to spatial resolution based on the number of channels used as inputs; ranging from 744% when using only 5 channels and up to 922% when using 41 channels. Temporal-spatial features were shown to provide increased motion-specific accuracy when similar muscles were recruited for different gestures.

CONCLUSIONS

Muscle-specific electrodes were capable of accurately recording HD-EMG signals from intrinsic hand muscles and accurately predicting motion.

SIGNIFICANCE

The muscle-specific electrode arrays could improve electrophysiological research studies using EMG decomposition techniques to assess motor unit activity and in applications involving the analysis of dexterous hand motions.

Retentive capacity of power output and linear versus non-linear mapping of power loss in the isotonic muscular endurance test

The limit of dynamic endurance during repetitive contractions has been referred to as the point of muscle fatigue, which can be measured by mechanical and electrophysiological parameters combined with subjective estimates of load tolerance for revealing the human real-world capacity required to work continuously. In this study, an isotonic muscular endurance (IME) testing protocol under a psychophysiological fatigue criterion was developed for measuring the retentive capacity of the power output of lower limb muscles. Additionally, to guide the development of electrophysiological evaluation methods, linear and non-linear techniques for creating surface electromyography (sEMG) models were compared in terms of their ability to estimate muscle fatigue. Forty healthy college-aged males performed three trials of an isometric peak torque test and one trial of an IME test for the plantar flexors and knee and hip extensors. Meanwhile, sEMG activity was recorded from the medial gastrocnemius, lateral gastrocnemius, vastus medialis, rectus femoris, vastus lateralis, gluteus maximus, and biceps femoris of the right leg muscles. Linear techniques (amplitude-based parameters, spectral parameters, and instantaneous frequency parameters) and non-linear techniques (a multi-layer perception neural network) were used to predict the time-dependent power output during dynamic contractions. Two mechanical manifestations of muscle fatigue were observed in the IME tests, including power output reduction between the beginning and end of the test and time-dependent progressive power loss. Compared with linear mapping (linear regression) alone or a combination of sEMG variables, non-linear mapping of power loss during dynamic contractions showed significantly higher signal-to-noise ratios and correlation coefficients between the actual and estimated power output. Muscular endurance required in real-world activities can be measured by considering the amount of work produced or the activity duration via the recommended IME testing protocol under a psychophysiological termination criterion. Non-linear mapping techniques provide more powerful mapping of power loss compared with linear mapping in the IME testing protocol.

Electrode Size and Placement for Surface EMG Bipolar Detection from the Brachioradialis Muscle: A Scoping Review

The brachioradialis muscle (BRD) is one of the main elbow flexors and is often assessed by surface electromyography (sEMG) in physiology, clinical, sports, ergonomics, and bioengineering applications. The reliability of the sEMG measurement strongly relies on the characteristics of the detection system used, because of possible crosstalk from the surrounding forearm muscles. We conducted a scoping review of the main databases to explore available guidelines of electrode placement on BRD and to map the electrode configurations used and authors’ awareness on the issues of crosstalk. One hundred and thirty-four studies were included in the review. The crosstalk was mentioned in 29 studies, although two studies only were specifically designed to assess it. One hundred and six studies (79%) did not even address the issue by generically placing the sensors above BRD, usually choosing large disposable ECG electrodes. The analysis of the literature highlights a general lack of awareness on the issues of crosstalk and the need for adequate training in the sEMG field. Three guidelines were found, whose recommendations have been compared and summarized to promote reliability in further studies. In particular, it is crucial to use miniaturized electrodes placed on a specific area over the muscle, especially when BRD activity is recorded for clinical applications.

Analytical Modelling of Surface EMG Signals Generated by Curvilinear Fibers with Approximate Conductivity Tensor

OBJECTIVE

Mathematical modelling of surface electromyographic (EMG) signals has been proven a valuable tool to interpret experimental data and to validate signal processing techniques. Most analytical EMG models only consider muscle fibers with specific and fixed arrangements. However, the fiber orientation and curvature may change along the fiber paths and may differ from fiber to fiber. Here we propose a subject-specific EMG model that simulates the fiber trajectories in muscles of the upper arm and analytically derives the action potentials assuming an approximate conductivity tensor.

METHODS

Magnetic Resonance (MR) images were acquired to identify and generate muscle fiber paths and to determine the muscle locations in a cylindrical volume conductor. While the propagation of the action potentials followed the identified curvilinear fiber paths, the conductivity tensor was not adapted to the fiber direction but approximated along the longitudinal axis of the cylindrical volume conductor. Single fiber action potentials (SFAPs) were computed by simulating the generation, propagation, and extinction of membrane current sources. To validate the assumption of the approximate conductivity tensor, two numerical models were implemented for comparison with the analytical solution. The first numerical model reproduced the analytical model and therefore included an approximation for the conductivity tensor. The second numerical model included the exact conductivity tensor derived from the fiber curvatures.

RESULTS

The motor unit action potentials generated by the proposed analytical model and the two numerical models were highly similar (cross-correlation >0.98, normalized root mean square error, nRMSE 0.04, relative error in the median frequency of the simulated waveforms of approximately 3%). The proposed analytical model was also evaluated by comparing simulated and experimentally recorded compound muscle action potentials (CMAPs). The CMAPs simulated with the proposed model better matched the experimental data (cross-correlation >0.90 and nRMSE <0.25 for the majority of the channels) than a model with straight fibers. Finally, the proposed model was representatively used to test the accuracy of an EMG decomposition algorithm, providing a realistic benchmark.

CONCLUSIONS AND SIGNIFICANCE

The proposed analytical model generates action potentials that reflect the spatial distributions of muscle fibers with curvilinear paths. The simulated signals are more realistic than signals generated by analytical models with straight fibers and can therefore be applied for testing EMG processing algorithms with a trade-off between simulation accuracy and computational speed.

Performance Evaluation of a Wearable Tattoo Electrode Suitable for High-Resolution Surface Electromyogram Recording

OBJECTIVE

High-density surface electromyography (HD-sEMG) has been utilized extensively in neuromuscular research. Despite its potential advantages, limitations in electrode design have largely prevented widespread acceptance of the technology. Commercial electrodes have limited spatial fidelity, because of a lack of sharpness of the signal, and variable signal stability. We demonstrate here a novel tattoo electrode that addresses these issues. Our dry HD electrode grid exhibits remarkable deformability which ensures superior conformity with the skin surface, while faithfully recording signals during different levels of muscle contraction.

METHOD

We fabricated a 4 cm×3 cm tattoo HD electrode grid on a stretchable electronics membrane for sEMG applications. The grid was placed on the skin overlying the biceps brachii of healthy subjects, and was used to record signals for several hours while tracking different isometric contractions.

RESULTS

The sEMG signals were recorded successfully from all 64 electrodes across the grid. These electrodes were able to faithfully record sEMG signals during repeated contractions while maintaining a stable baseline at rest. During voluntary contractions, broad EMG frequency content was preserved, with accurate reproduction of the EMG spectrum across the full signal bandwidth.

CONCLUSION

The tattoo grid electrode can potentially be used for recording high-density sEMG from skin overlying major limb muscles. Layout programmability, good signal quality, excellent baseline stability, and easy wearability make this electrode a potentially valuable component of future HD electrode grid applications.

SIGNIFICANCE

The tattoo electrode can facilitate high fidelity recording in clinical applications such as tracking the evolution and time-course of challenging neuromuscular degenerative disorders.

Effects of detection system parameters on cross-correlations between MUAPs generated from parallel and inclined muscle fibres

The aim of this study was to investigate the effects of inter-electrode distance (IED), electrode radius (ER) and electrodes configurations on cross-correlation coefficient (CC) between motor unit action potentials (MUAPs) generated in a motor unit (MU) of parallel fibres and in a MU of inclined fibres with respect to the detection system. The fibres inclination angle (FIA) varied from 0° to 180° by a step of 5°. Six spatial filters (the longitudinal single differential (LSD), longitudinal double differential (LDD), bi-transversal double differential (BiTDD), normal double differential (NDD), an inverse binomial filter of order two (IB2) and maximum kurtosis filter (MKF)), three values of IED and three values of ER were considered.

A cylindrical multilayer volume conductor constituted by bone, muscle, fat and skin layers was used to simulate the MUAPs.

The cross-correlation coefficient analysis showed that with the increase of the FIA, the pairs of MUAPs detected by the IB2 system were more correlated than those detected by the five other systems. For each FIA, the findings also showed that the MUAPs pairs detected by BiTDD, NDD, IB2 and MKF systems were more correlated with smaller IEDs than with larger ones, while inverse results were found with the LSD and LDD systems. In addition, the pairs of MUAPs detected by the LDD, BiTDD, IB2 and MKF systems were more correlated with large ERs than with smaller ones. However, inverse results were found with the LSD and NDD systems.

Effect of electrode characteristics on electromyographic activity of the masseter muscle

OBJECTIVES

The study investigated effects of electrode material, inter-electrode distance (IED), and conductive gel on electromyographic (EMG) activity recorded from the masseter muscle.

MATERIALS AND METHODS

EMG was recorded unilaterally, as ten volunteers performed standardized oral tasks. Ag/AgCl and Ag coated with Au were the gel-based; Ag alloy coated with graphene, pure Ag coated with graphene and silver nanowire embedded electrodes were the gel-free materials tested. Ag/AgCl electrodes were tested at three different IEDs (i.e. 15 mm, 20 mm, 25 mm). An electrode relative performance index (ERPI) was defined and calculated for each of the standardized oral tasks that the volunteers performed. ERPI values obtained for the different oral tasks with different electrode materials and IEDs were compared using two-way repeated-measures ANOVA.

RESULTS

ERPI values were not significantly influenced by IED. However, for the electrode materials statistically significant differences were found in ERPI values for all oral tasks. Of the gel-free electrode materials tested, pure silver electrodes coated with graphene had the highest ERPI values followed by Ag alloy electrodes coated with graphene and silver nanowire embedded electrodes.

CONCLUSIONS

Within the limitations of the study, IED between 15 and 25 mm has a negligible effect on masseter muscle EMG. Graphene coated and silver nanowire embedded electrodes show promise as gel-free alternatives.

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

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

Age Related Changes in Motor Function (II). Decline in Motor Performance Outcomes

Age-related impairments in motor performance are caused by a deterioration in mechanical and neuromuscular functions, which have been investigated from the macro-level of muscle-tendon unit to the micro-level of the single muscle fiber. When compared to the healthy young skeletal muscle, aged skeletal muscle is: (1) weaker, slower and less powerful during the performance of voluntary contractions; (2) less steady during the performance of isometric contractions, particularly at low levels of force; and (3) less susceptible to fatigue during the performance of sustained isometric contractions, but more susceptible to fatigue during the performance of high-velocity dynamic contractions. These impairments have been discussed to be mainly the result of: a) loss of muscle mass and selective atrophy of type II muscle fibers; b) altered tendon mechanical properties (decreased tendon stiffness); c) reduced number and altered function of motor units; d) slower muscle fiber shortening velocity; e) increased oscillation in common synaptic input to motor neurons; and f) altered properties and activity of sarcoplasmic reticulum. In this second part of a two-part review we have detailed the age-related impairments in motor performance with a reference to the most important mechanical and neuromuscular contributing factors.

Dry Epidermal Electrodes Can Provide Long-Term High Fidelity Electromyography for Limited Dynamic Lower Limb Movements

Due to the limitations of standard wet Silver/Silver Chloride (Ag/AgCl) hydrogel electrodes and the growing demand for long-term high fidelity surface electromyography (EMG) recording, dry epidermal electrodes are of great interest. Evaluating the usability and signal fidelity of dry epidermal electrodes could help determine the extent of potential applications using EMG electrodes. We collected EMG signals over eight days from the right rectus femoris of seven subjects using single-use dry epidermal electrodes and traditional Ag/AgCl electrodes while covered and uncovered during dynamic movements (leg extension, sit-to-stand, and treadmill walking at 0.75 m/s and 1.30 m/s). We quantified signal fidelity using signal-to-noise ratio (SNR); signal-to-motion ratio (SMR); and a metric we previously developed, the Signal Quality Index, which considers that better EMG signal quality requires both good signal-to-noise ratio and good signal-to-motion ratio. Wear patterns over the eight days degraded EMG signal quality. Uncovered epidermal electrodes that remained intact and maintained good adhesion to the skin had signal-to-noise ratios, signal-to-motion ratios, and Signal Quality Index values that were above the acceptable thresholds for limited dynamic lower limb movements (leg extension and sit-to-stand). This indicated that dry epidermal electrodes could provide good signal quality across all subjects for five days for these movements. For walking, the signal-to-noise ratios of the uncovered epidermal electrodes were still above the acceptable threshold, but signal-to-motion ratios and the Signal Quality Index values were far below the acceptable thresholds. The signal quality of the epidermal electrodes that showed no visible wear was stable over five days. As expected, covering the epidermal electrodes improved signal quality, but only for limited dynamic lower limb movements. Overall, single-use dry epidermal electrodes were able to maintain high signal quality for long-term EMG recording during limited dynamic lower limb movements, but further improvement is needed to reduce motion artifacts for whole body dynamic movements such as walking.

Real-Time Forecasting of sEMG Features for Trunk Muscle Fatigue Using Machine Learning

OBJECTIVE

Several features of the surface electromyography (sEMG) signal are related to muscle activity and fatigue. However, the time-evolution of these features are non-stationary and vary between subjects. The aim of this study is to investigate the use of adaptive algorithms to forecast sEMG feature of the trunk muscles.

METHODS

Shallow models and a deep convolutional neural network (CNN) were used to simultaneously learn and forecast 5 common sEMG features in real-time to provide tailored predictions. This was investigated for: up to a 25 second horizon; for 14 different muscles in the trunk; across 13 healthy subjects; while they were performing various exercises.

RESULTS

The CNN was able to forecast 25 seconds ahead of time, with 6.88% mean absolute percentage error and 3.72% standard deviation of absolute percentage error, across all the features. Moreover, the CNN outperforms the best shallow model in terms of a figure of merit combining accuracy and precision by at least 30% for all the 5 features.

CONCLUSION

Even though the sEMG features are non-stationary and vary between subjects, adaptive learning and forecasting, especially using CNNs, can provide accurate and precise forecasts across a range of physical activities.

SIGNIFICANCE

The proposed models provide the groundwork for a wearable device which can forecast muscle fatigue in the trunk, so as to potentially prevent low back pain. Additionally, the explicit real-time forecasting of sEMG features provides a general model which can be applied to many applications of muscle activity monitoring, which helps practitioners and physiotherapists improve therapy.

A gel-free Ti3C2Tx-based electrode array for high-density, high-resolution surface electromyography

Wearable sensors for surface electromyography (EMG) are composed of single- to few-channel large-area contacts, which exhibit high interfacial impedance and require conductive gels or adhesives to record high-fidelity signals. These devices are also limited in their ability to record activation across large muscle groups due to poor spatial coverage. To address these challenges, we have developed a novel high-density EMG array based on titanium carbide (Ti3C2Tx) MXene encapsulated in parylene-C. Ti3C2Tx is a two-dimensional nanomaterial with excellent electrical, electrochemical, and mechanical properties, which forms colloidally stable aqueous dispersions, enabling safe, scalable solutions-processing. Leveraging the excellent combination of metallic conductivity, high pseudocapacitance, and ease of processability of Ti3C2Tx MXene, we demonstrate the fabrication of gel-free, high-density EMG arrays which are ~8 μm thick, feature 16 recording channels, and are highly skin-conformable. The impedance of Ti3C2Tx electrodes in contact with human skin is 100-1000x lower than the impedance of commercially-available electrodes which require conductive gels to be effective. Furthermore, our arrays can record high-fidelity, low-noise EMG, and can resolve muscle activation with improved spatiotemporal resolution and sensitivity compared to conventional gelled electrodes. Overall, our results establish Ti3C2Tx-based bioelectronic interfaces as a powerful platform technology for high-resolution, non-invasive wearable sensing technologies.

Impact of the EMG normalization method on muscle activation and the antagonist-agonist co-contraction index during active elbow extension: Practical implications for post-stroke subjects

Electromyographic (EMG) raw signals are sensitive to intrinsic and extrinsic factors. Consequently, EMG normalization is required to draw proper interpretations of standardized data. Specific recommendations are needed regarding a relevant EMG normalization method for participants who show atypical EMG patterns, such as post-stroke subjects. This study compared three EMG normalization methods ("isometric MVC", "isokinetic MVC", "isokinetic MVC kinematic-related") on muscle activations and the antagonist-agonist co-contraction index. Fifteen post-stroke subjects and fifteen healthy controls performed active elbow extensions, followed by isometric and isokinetic maximum voluntary contractions (MVC). Muscle activations were obtained by normalizing EMG envelopes during active movement using a reference value determined for each EMG normalization method. The results showed no significant difference between the three EMG normalization methods in post-stroke subjects on muscle activation and the antagonist-agonist co-contraction index. We highlighted that the antagonist-agonist co-contraction index could underestimate the antagonist co-contraction in the presence of atypical EMG patterns. Based on its practicality and feasibility, we recommend the use of isometric MVC as a relevant procedure for EMG normalization in post-stroke subjects. We suggest combined analysis of the antagonist-agonist co-contraction index and agonist and antagonist activations to properly investigate antagonist co-contraction in the presence of atypical EMG patterns during movement.

Muscle endurance time estimation during isometric training using electromyogram and supervised learning

Constant-force isometric muscle training is useful for increasing the maximal strength , rehabilitation and work-fatigue assessment. Earlier studies have shown that muscle fatigue characteristics can be used for evaluating muscle endurance limit.

STUDY OBJECTIVE

To predict muscle endurance time during isometric task using frequency spectrum characteristics of surface electromyography signals along with analysis of frequency spectrum shape and scale during fatigue accumulation.

METHOD

Thirteen subjects performed isometric lateral raise at 60% MVC of deltoid (lateral) till endurance limit. Time windowed sEMG frequency spectrum was modelled using 2-parameter distributions namely Gamma and Weibull for spectrum analysis and endurance prediction.

RESULTS

Gamma distribution provided better spectrum fitting (P < 0.001) than Weibull distribution. Spectrum Distribution demonstrated no change in shape but shifted towards lower frequency with increase of magnitude at characteristic mode frequency. Support Vector Regression based algorithm was developed for endurance time estimation using features derived from fitted frequency spectrum. Time taken till endurance limit for acquired dataset 38.53 ± 17.33 s (Mean ± Standard Deviation) was predicted with error of 0.029 ± 4.19 s . R-square: 0.956, training and test sets RMSE was calculated as 3.96 and 4.29 s respectively. The application of the algorithm suggested that model required 70% of sEMG signal from maximum time of endurance for high prediction accuracy.

CONCLUSION

Endurance Limit prediction algorithm was developed for quantification of endurance time for optimizing isometric training and rehabilitation. Our method could help personalize and change conventional training method of same weight and duration for all subjects with optimized training parameters, based upon individual sEMG activity.

Tutorial. Surface EMG detection in space and time: Best practices

This tutorial is aimed to non-engineers using, or planning to use, surface electromyography (sEMG) as an assessment tool in the prevention, monitoring and rehabilitation fields. Its first purpose is to address the issues related to the origin and nature of the signal and to its detection (electrode size, distance, location) by one-dimensional (bipolar and linear arrays) and two-dimensional (grids) electrode systems while avoiding advanced mathematical, physical or physiological issues. Its second purpose is to outline best practices and provide general guidelines for proper signal detection. Issues related to the electrode-skin interface, signal conditioning and interpretation will be discussed in subsequent tutorials.

Consensus for experimental design in electromyography (CEDE) project: Electrode selection matrix

The Consensus for Experimental Design in Electromyography (CEDE) project is an international initiative which aims to guide decision-making in recording, analysis, and interpretation of electromyographic (EMG) data. The quality of the EMG recording, and validity of its interpretation depend on many characteristics of the recording set-up and analysis procedures. Different electrode types (i.e., surface and intramuscular) will influence the recorded signal and its interpretation. This report presents a matrix to consider the best electrode type selection for recording EMG, and the process undertaken to achieve consensus. Four electrode types were considered: (1) conventional surface electrode, (2) surface matrix or array electrode, (3) fine-wire electrode, and (4) needle electrode. General features, pros, and cons of each electrode type are presented first. This information is followed by recommendations for specific types of muscles, the information that can be estimated, the typical representativeness of the recording and the types of contractions for which the electrode is best suited. This matrix is intended to help researchers when selecting and reporting the electrode type in EMG studies.

A Study of Movement Classification of the Lower Limb Based on up to 4-EMG Channels

The number and position of sEMG electrodes have been studied extensively due to the need to improve the accuracy of the classification they carry out of the intention of movement. Nevertheless, increasing the number of channels used for this classification often increases their processing time as well. This research work contributes with a comparison of the classification accuracy based on the different number of sEMG signal channels (one to four) placed in the right lower limb of healthy subjects. The analysis is performed using Mean Absolute Values, Zero Crossings, Waveform Length, and Slope Sign Changes; these characteristics comprise the feature vector. The algorithm used for the classification is the Support Vector Machine after applying a Principal Component Analysis to the features. The results show that it is possible to reach more than 90% of classification accuracy by using 4 or 3 channels. Moreover, the difference obtained with 500 and 1000 samples, with 2, 3 and 4 channels, is not higher than 5%, which means that increasing the number of channels does not guarantee 100% precision in the classification.