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

Development of a novel technique to insert intramuscular electromyography electrodes into the deep intrinsic foot muscles via the dorsum of the foot

This study aimed to develop an insertion technique for intramuscular EMG recording of the oblique head of adductor hallucis (AddH) and first dorsal interosseous (FDI) muscles in humans via the dorsum of the foot, and report feasibility of intramuscular EMG data acquisition during walking in shoes. In eight individuals without musculoskeletal pain or injury (5 males; 32 ± 8 years), intramuscular electrodes were inserted into AddH (oblique head) and FDI through the right foot's dorsum (between metatarsals I-II) with ultrasound guidance. The ultrasound transducer was positioned on the plantar surface. Intramuscular EMG was also recorded from abductor hallucis, tibialis posterior, flexor digitorum longus and peroneus longus. Participants performed six overground walking trials wearing modified shoes, and rated pain associated with the intramuscular electrodes during walking (numerical rating scale, 0-10). High-quality EMG recordings were obtained from intrinsic and extrinsic foot muscles. Analyses of power spectral densities indicated that movement artefacts commonly observed during gait were removed by filtering. Pain associated with AddH/FDI electrodes during walking was low (median[IQR] 1[2]; range 0-4) and similar to other sites. Findings demonstrate that intramuscular EMG recording from AddH (oblique head) and FDI using this insertion technique is feasible and associated with minimal pain when walking in shoes.

A novel procedure to automate the removal of PLI and motion artifacts using mode decomposition to enhance pattern recognition of sEMG signals for myoelectric control of prosthesis

Hand Movement Recognition (HMR) with sEMG is crucial for artificial hand prostheses. HMR performance mostly depends on the feature information that is fed to the classifiers. However, sEMG often captures noise like power line interference (PLI) and motion artifacts. This may extract redundant and insignificant feature information, which can degrade HMR performance and increase computational complexity. This study aims to address these issues by proposing a novel procedure for automatically removing PLI and motion artifacts from experimental sEMG signals. This will make it possible to extract better features from the signal and improve the categorization of various hand movements. Empirical mode decomposition and energy entropy thresholding are utilized to select relevant mode components for artifact removal. Time domain features are then used to train classifiers (kNN, LDA, SVM) for hand movement categorization, achieving average accuracies of 92.36%, 93.63%, and 98.12%, respectively, across subjects. Additionally, muscle contraction efforts are classified into low, medium, and high categories using this technique. Validation is performed on data from ten subjects performing eight hand movement classes and three muscle contraction efforts with three surface electrode channels. Results indicate that the proposed preprocessing improves average accuracy by 9.55% with the SVM classifier, significantly reducing computational time.

Reliability of Surface Electromyography From the Lower-limb Muscles During Maximal and Submaximal Voluntary Isometric Contractions in In-bed Healthy Individuals and Patients With Subacute Stroke

This study aims to develop maximal voluntary isometric contraction (MVIC) and submaximal voluntary isometric contraction (subMVIC) methods and to assess the reliability of the developed methods for in-bed healthy individuals and patients with subacute stroke. The electromyography (EMG) activities from the lower-limb muscles including the tensor fascia lata (TFL), rectus femoris (RF), tibialis anterior (TA), and gastrocnemius (GC) on both sides were recorded during MVIC and subMVIC using surface EMG sensors in 20 healthy individuals and 20 subacute stroke patients. In inter-trial reliability, both MVIC and subMVIC methods demonstrated excellent reliability for all the measured muscles at baseline and follow-up evaluations in both healthy individuals and stroke patients. In inter-day reliability, MVIC showed good reliability for the TFL and moderate reliability for the RF, TA, and GC, while subMVIC showed good reliability for the TFL, RF, and GC and poor reliability for the TA in healthy individuals. In conclusion, the MVIC and subMVIC methods of EMG activities were feasible in in-bed healthy individuals and patients with subacute stroke. The results can serve as a basis for the clinical evaluation of muscular activities using quantitative EMG signals on the lower-limb muscles in stroke patients with impaired mobility.

Effectiveness of the Copenhagen adduction modified position stage 1: EMG measurements and hand-held dynamometer analysis in young and healthy men

OBJECTIVES

To verify the effectiveness of the use of a modified position of the Copenhagen Adduction (CA) stage 1 compared to the original position.

DESIGN

Cross-sectional study.

SETTING

Laboratory.

PARTICIPANTS

31 healthy men aged 23.7 ± 1.9 years with no recent or chronic general pathology.

MAIN OUTCOME MEASURES

Differences between EMG amplitudes for the adductor longus (AL), rectus femoris (RF) and semi tendinous (ST) during dynamic contractions and adductor maximal isometric voluntary contraction (MIVC) force values between CA stage 1 standard and modified positions were assessed with either Wilcoxon or paired t-test.

RESULTS

No significant differences were observed for EMG amplitudes of the AL (p-value = 0.724) and for the RF muscle (p-value = 0.337) and for the adductor force (p-value = 0.361) between the two positions. A significant difference was obtained for the ST (p-value<0.001) mainly explained by the adapted position of the non-dominant leg which unlocked the hip joint and generated less muscle activity in the hamstrings.

CONCLUSIONS

Muscle activity of the AL muscle and adductor force being similar in both positions, the CA stage 1 modified position could be of interest for rehabilitation after adductor injury or strengthening of the adductors in elite athletes.

Design, Fabrication, and Evaluation of 3D Biopotential Electrodes and Intelligent Garment System for Sports Monitoring

This study presents the development and evaluation of an innovative intelligent garment system, incorporating 3D knitted silver biopotential electrodes, designed for long-term sports monitoring. By integrating advanced textile engineering with wearable monitoring technologies, we introduce a novel approach to real-time physiological signal acquisition, focusing on enhancing athletic performance analysis and fatigue detection. Utilizing low-resistance silver fibers, our electrodes demonstrate significantly reduced skin-to-electrode impedance, facilitating improved signal quality and reliability, especially during physical activities. The garment system, embedded with these electrodes, offers a non-invasive, comfortable solution for continuous ECG and EMG monitoring, addressing the limitations of traditional Ag/AgCl electrodes, such as skin irritation and signal degradation over time. Through various experimentation, including impedance measurements and biosignal acquisition during cycling activities, we validate the system's effectiveness in capturing high-quality physiological data. Our findings illustrate the electrodes' superior performance in both dry and wet conditions. This study not only advances the field of intelligent garments and biopotential monitoring, but also provides valuable insights for the application of intelligent sports wearables in the future.

Consensus for experimental design in electromyography (CEDE) project: Application of EMG to estimate muscle force

Skeletal muscles power movement. Deriving the forces produced by individual muscles has applications across various fields including biomechanics, robotics, and rehabilitation. Since direct in vivo measurement of muscle force in humans is invasive and challenging, its estimation through non-invasive methods such as electromyography (EMG) holds considerable appeal. This matrix, developed by the Consensus for Experimental Design in Electromyography (CEDE) project, summarizes recommendations on the use of EMG to estimate muscle force. The matrix encompasses the use of bipolar surface EMG, high density surface EMG, and intra-muscular EMG (1) to identify the onset of muscle force during isometric contractions, (2) to identify the offset of muscle force during isometric contractions, (3) to identify force fluctuations during isometric contractions, (4) to estimate force during dynamic contractions, and (5) in combination with musculoskeletal models to estimate force during dynamic contractions. For each application, recommendations on the appropriateness of using EMG to estimate force and justification for each recommendation are provided. The achieved consensus makes clear that there are limited scenarios in which EMG can be used to accurately estimate muscle forces. In most cases, it remains important to consider the activation as well as the muscle state and other biomechanical and physiological factors- such as in the context of a formal mechanical model. This matrix is intended to encourage interdisciplinary discussions regarding the integration of EMG with other experimental techniques and to promote advances in the application of EMG towards developing muscle models and musculoskeletal simulations that can accurately predict muscle forces in healthy and clinical populations.

Consensus for experimental design in electromyography (CEDE) project: Checklist for reporting and critically appraising studies using EMG (CEDE-Check)

The diversity in electromyography (EMG) techniques and their reporting present significant challenges across multiple disciplines in research and clinical practice, where EMG is commonly used. To address these challenges and augment the reproducibility and interpretation of studies using EMG, the Consensus for Experimental Design in Electromyography (CEDE) project has developed a checklist (CEDE-Check) to assist researchers to thoroughly report their EMG methodologies. Development involved a multi-stage Delphi process with seventeen EMG experts from various disciplines. After two rounds, consensus was achieved. The final CEDE-Check consists of forty items that address four critical areas that demand precise reporting when EMG is employed: the task investigated, electrode placement, recording electrode characteristics, and acquisition and pre-processing of EMG signals. This checklist aims to guide researchers to accurately report and critically appraise EMG studies, thereby promoting a standardised critical evaluation, and greater scientific rigor in research that uses EMG signals. This approach not only aims to facilitate interpretation of study results and comparisons between studies, but it is also expected to contribute to advancing research quality and facilitate clinical and other practical applications of knowledge generated through the use of EMG.

Towards standardisation of surface electromyography measurements in the horse: Bipolar electrode location

The use of surface electromyography in the field of animal locomotion has increased considerably over the past decade. However, no consensus exists on the methodology for data collection in horses. This study aimed to start the development of recommendations for bipolar electrode locations to collect surface electromyographic data from horses during dynamic tasks. Data were collected from 21 superficial muscles of three horses during trot on a treadmill using linear electrode arrays. The data were assessed both quantitatively (signal-to-noise ratio (SNR) and coefficient of variation (CoV)) and qualitatively (presence of crosstalk and activation patterns) to compare and select electrode locations for each muscle. For most muscles and horses, the highest SNR values were detected near or cranial/proximal to the central region of the muscle. Concerning the CoV, there were larger differences between muscles and horses than within muscles. Qualitatively, crosstalk was suspected to be present in the signals of twelve muscles but not in all locations in the arrays. With this study, a first attempt is made to develop recommendations for bipolar electrode locations for muscle activity measurements during dynamic contractions in horses. The results may help to improve the reliability and reproducibility of study results in equine biomechanics.

Older adults use fewer muscles to overcome perturbations during a seated locomotor task

Locomotor perturbations provide insights into humans' response to motor errors. We investigated the differences in motor adaptation and muscle cocontraction between young and older adults during perturbed-arm and -leg recumbent stepping. We hypothesized that besides prolonged adaptation due to use-dependent learning, older adults would exhibit greater muscle cocontraction than young adults in response to the perturbations. Perturbations were brief increases in resistance applied during each stride at the extension onset or midextension of the left or right leg. Seventeen young adults and eleven older adults completed four 10-min perturbed stepping tasks. Subjects were instructed to follow a visual pacing cue, step smoothly, and use all their limbs to drive the stepper. Results showed that young and older adults did not decrease their errors with more perturbation experience, and errors did not wash out after perturbations were removed. Interestingly, older adults consistently had smaller motor errors than young adults in response to the perturbations. Older adults used fewer muscles to drive the stepper and had greater cocontraction than young adults. The results suggest that, despite similar motor error responses, young and older adults use distinctive muscle recruitment patterns to perform the motor task. Age-related motor strategies help track motor changes across the human life span and are a baseline for rehabilitation and performance assessment.NEW & NOTEWORTHY Older adults often demonstrate greater cocontraction and motor errors than young adults in response to motor perturbations. We demonstrated that older adults reduced their motor errors more than young adults with brief perturbations during recumbent stepping while maintaining greater muscle cocontraction. In doing so, older adults largely used one muscle pair to drive the stepper, tibialis anterior and soleus, whereas young adults used all muscles. These two muscles are crucial for maintaining upright balance.

Current practices in clinical gait analysis in Europe: A comprehensive survey-based study from the European society for movement analysis in adults and children (ESMAC) standard initiative

BACKGROUND

Clinical gait analysis (CGA) is a systematic approach to comprehensively evaluate gait patterns, quantify impairments, plan targeted interventions, and evaluate the impact of interventions. However, international standards for CGA are currently lacking, resulting in various national initiatives. Standards are important to ensure safe and effective healthcare practices and to enable evidence-based clinical decision-making, facilitating interoperability, and reimbursement under national healthcare policies. Collaborative clinical and research work between European countries would benefit from common standards.

RESEARCH OBJECTIVE

This study aimed to review the current laboratory practices for CGA in Europe.

METHODS

A comprehensive survey was conducted by the European Society for Movement Analysis in Adults and Children (ESMAC), in close collaboration with the European national societies. The survey involved 97 gait laboratories across 16 countries. The survey assessed several aspects related to CGA, including equipment used, data collection, processing, and reporting methods.

RESULTS

There was a consensus between laboratories concerning the data collected during CGA. The Conventional Gait Model (CGM) was the most used biomechanical model for calculating kinematics and kinetics. Respondents also reported the use of video recording, 3D motion capture systems, force plates, and surface electromyography. While there was a consensus on the reporting of CGA data, variations were reported in training, documentation, data preprocessing and equipment maintenance practices.

SIGNIFICANCE

The findings of this study will serve as a foundation for the development of standardized guidelines for CGA in Europe.

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.

High-Density Electromyography Excitation in Front vs. Back Lat Pull-Down Prime Movers

The current study compared the spatial excitation of the primary muscles during the lat pull-down exercise with the bar passing in front (front-LPD) or behind the neck (back-LPD) using high-density electromyography. Fourteen resistance trained men performed a front-LPD or a back-LPD within a non-fatiguing set with 8-RM as the external load. The muscle excitation centroid of latissimus dorsi, middle trapezius, pectoralis major, biceps brachii, triceps brachii and posterior deltoid muscles were recorded during the ascending and the descending phase. During the descending phase, the front-LPD showed superior excitation of the latissimus dorsi (ES = 0.97) and the pectoralis major (ES = 1.17), while in the ascending phase, the back-LPD exhibited superior excitation of the latissimus dorsi (ES = 0.63), and the front-LPD showed superior excitation of the biceps brachii (ES = 0.41) and the posterior deltoid (ES = 1.77). During the descending phase, the front-LPD showed a more lateral centroid of the latissimus dorsi (ES = 0.60), the biceps brachii (ES = 0.63) and the triceps brachii (ES = 0.98), while the centroid was more medial for the middle trapezius (ES = 0.58). The centroid of the middle trapezius was also more medial in the front-LPD during the ascending phase (ES = 0.85). The pectoralis major centroid was more cranial in the front-LPD for both the descending (ES = 1.58) and the ascending phase (ES = 0.88). The front-LPD appears to provide overall greater excitation in the prime movers. However, distinct spatial excitation patterns were observed, making exercise suitable for the training routine.

Assessment of Self-report, Palpation, and Surface Electromyography Dataset During Isometric Muscle Contraction

Measuring muscle fatigue involves assessing various components within the motor system. While subjective and sensor-based measures have been proposed, a comprehensive comparison of these assessment measures is currently lacking. This study aims to bridge this gap by utilizing three commonly used measures: participant self-reported perceived muscle fatigue scores, a sports physiotherapist's manual palpation-based muscle tightness scores, and surface electromyography sensors. Compensatory muscle fatigue occurs when one muscle group becomes fatigued, leading to the involvement and subsequent fatigue of other muscles as they compensate for the workload. The evaluation of compensatory muscle fatigue focuses on nine different upper body muscles selected by the sports physiotherapist. With a cohort of 30 male subjects, this study provides a valuable dataset for researchers and healthcare practitioners in sports science, rehabilitation, and human performance. It enables the exploration and comparison of diverse methods for evaluating different muscles in isometric contraction.

Nonlinear spatio-temporal filter to reduce crosstalk in bipolar electromyogram

Objective.The wide detection volume of surface electromyogram (EMG) makes it prone to crosstalk, i.e. the signal from other muscles than the target one. Removing this perturbation from bipolar recordings is an important open problem for many applications.Approach.An innovative nonlinear spatio-temporal filter is developed to estimate the EMG generated by the target muscle by processing noisy signals from two bipolar channels, placed over the target and the crosstalk muscle, respectively. The filter is trained on some calibration data and then can be applied on new signals. Tests are provided in simulations (considering different thicknesses of the subcutaneous tissue, inter-electrode distances, locations of the EMG channels, force levels) and experiments (from pronator teres and flexor carpi radialis of 8 healthy subjects).Main results.The proposed filter allows to reduce the effect of crosstalk in all investigated conditions, with a statistically significant reduction of its root mean squared of about 20%, both in simulated and experimental data. Its performances are also superior to those of a blind source separation method applied to the same data.Significance.The proposed filter is simple to be applied and feasible in applications in which single bipolar channels are placed over the muscles of interest. It can be useful in many fields, such as in gait analysis, tests of myoelectric fatigue, rehabilitation with EMG biofeedback, clinical studies, prosthesis control.

Using force or EMG envelope as feedback signal for motor control system

PURPOSE

This work studied muscle neuro-mechanics during symmetrical up-going ramp (UGR) and down-going ramp (DGR).

AIM

to evaluate during the modulation of muscular action the outcome of force feedback (FF) or neural feedback (NF) on the behavior of the trailing signals - i.e. the EMG envelope (eEMG) for FF or force signal for NF.

METHOD

Subjects: 20. Investigated muscles: dorsal interosseous (FDI) and tibialis anterior (TA). Detected signals: force and EMG. Visual feedback: force (FF), eEMG (NF). Effort triangles: ramps duration 7.5 s, vertex at 50 and 100 % of the maximal voluntary action. Eventually, each subject performed FF50%, FF100%, NF50% and NF100% per each muscle. In each condition the areas beneath the force and eEMG signals were computed to calculate the ratios between the DGR and UGR values during the different tasks (force area DGR / force area UGR; eEMG area DGR / eEMG area UGR). Electro-mechanical coupling efficiency (EMCE) was estimated through the eEMG area / force area ratio for both UGR and DGR in each condition.

RESULTS

a) FF. FDI: eEMG area ratio was 0.84 ± 0.15 and 0.73 ± 0.17 for FF50% and FF100%, respectively. TA: eEMG area ratio was 0.88 ± 0.11 and 0.91 ± 0.17 for FF50% and FF100%, respectively. b) NF: FDI: force area ratio was 1.18 ± 0.13 and 1.17 ± 0.13 for NF50% and NF100%, respectively. TA: force area ratio was 1.17 ± 0.21 and 1.07 ± 0.19 for NF50% and NF100%, respectively. c) DGR EMCE was greater than UGR EMCE in all four tasks.

CONCLUSION

The influence of UGR on deployed EMCE in the following force decrement phase underpins the changes of trailing signals area during DGR. This underlines the necessity of a careful evaluation of the features of FF or NF for experimental studies or rehabilitation purposes involving the motor control system.

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

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

Effect of Exhaustive Exercise on Lumbopelvic-Hip Complex Stability, Muscle Activity, and Movement Patterns

This study aimed to evaluate the effect of exhaustive exercise on lumbopelvic-hip complex (LPHC) muscle activity, stability, and single-leg squat kinematics. Twenty-two healthy participants (12 females, 23.5 ± 3.1 years) were recruited. LPHC stability was measured by number of errors committed during a seated trunk control test (STCT). Surface electromyography recorded muscle activity of rectus abdominis (RA), external oblique, internal oblique (IO), erector spinae, and gluteus medius during the STCT and single-leg squat, and was normalized to peak activity during the task. Two-dimensional motion analysis quantified frontal and sagittal plane kinematics of the trunk, hip, and knee. Following exhaustive exercise, STCT performance worsened (number of errors: pre: 5.5 (interquartile range (IQR) = 1.4-9.0), post: 8.0 (IQR = 3.6-11.3), p = 0.026.), RA activity increased during the single-leg squat (pre: 42.1 (IQR = 33.6-48.5)%, post: 61.1 (IQR = 39.4-156.7 %, p =.004), and participants displayed less hip and knee flexion (hip: pre: 72.4 ± 22.1°; post: 66.2 ± 22.5°, p =.049; knee: pre: 72.4 ± 15.4°; post: 67.4 ± 18.2°, p =.005). Full-body exhaustive exercise negatively affected isolated LPHC stability and resulted in greater RA activity during the single-leg squat. Hip and knee flexion decreased during a single-leg squat after exhaustive exercise which could indicate decreased athletic performance, but changes in the quality of movement during other tasks should be further investigated.

Few sex-specific effects of fatigue on muscle synergies in a repetitive pointing task

Previous studies have identified some sex differences in how individual muscles change their activation during repetitive multi-joint arm motion-induced fatigue. However, little is known about how indicators of multi-muscle coordination change with fatigue in males and females. Fifty-six (29 females) asymptomatic young adults performed a repetitive, forward-backward pointing task until scoring 8/10 on a Borg CR10 scale while surface electromyographic activity of upper trapezius, anterior deltoid, biceps brachii, and triceps brachii was recorded. Activation coefficient, synergy structure, and relative weight of each muscle within synergies were calculated using the non-negative matrix factorization method. Two muscle synergies were extracted from the fatiguing task. The synergy structures were mostly preserved after fatigue, while the activation coefficients were altered. A significant Sex × Fatigue interaction effect showed more use of the anterior deltoid in males especially before fatigue in synergy 1 during shoulder stabilization (p = 0.04). As for synergy 2, it was characterized by variations in the relative weight of biceps, which was higher by 16 % in females compared to males (p = 0.04), and increased with fatigue (p = 0.03) during the elbow flexion acceleration phase and the deceleration phase of the backward pointing movement. Findings suggest that both sexes adapted to fatigue similarly, using fixed synergy structures, with alterations in synergy activation patterns and relative weights of individual muscles. Results support previous findings of an important role for the biceps and anterior deltoid in explaining sex differences in patterns of repetitive motion-induced upper limb fatigue.

Regional associations between inspiratory tongue dilatory movement and genioglossus activity during wakefulness in people with obstructive sleep apnoea

Inspiratory tongue dilatory movement is believed to be mediated via changes in neural drive to genioglossus. However, this has not been studied during quiet breathing in humans. Therefore, this study investigated this relationship and its potential role in obstructive sleep apnoea (OSA). During awake supine quiet nasal breathing, inspiratory tongue dilatory movement, quantified with tagged magnetic resonance imaging, and inspiratory phasic genioglossus EMG normalised to maximum EMG were measured in nine controls [apnoea-hypopnea index (AHI) ≤5 events/h] and 37 people with untreated OSA (AHI >5 events/h). Measurements were obtained for 156 neuromuscular compartments (85%). Analysis was adjusted for nadir epiglottic pressure during inspiration. Only for 106 compartments (68%) was a larger anterior (dilatory) movement associated with a higher phasic EMG [mixed linear regression, beta = 0.089, 95% CI [0.000, 0.178], t(99) = 1.995, P = 0.049, hereafter EMG↗/mvt↗]. For the remaining 50 (32%) compartments, a larger dilatory movement was associated with a lower phasic EMG [mixed linear regression, beta = -0.123, 95% CI [-0.224, -0.022], t(43) = -2.458, P = 0.018, hereafter EMG↘/mvt↗]. OSA participants had a higher odds of having at least one decoupled EMG↘/mvt↗ compartment (binary logistic regression, odds ratio [95% CI]: 7.53 [1.19, 47.47] (P = 0.032). Dilatory tongue movement was minimal (>1 mm) in nearly all participants with only EMG↗/mvt↗ compartments (86%, 18/21). These results demonstrate that upper airway dilatory mechanics cannot be predicted from genioglossus EMG, particularly in people with OSA. Tongue movement associated with minimal genioglossus activity suggests co-activation of other airway dilator muscles. KEY POINTS: Inspiratory tongue movement is thought to be mediated through changes in genioglossus activity. However, it is unknown if this relationship is altered by obstructive sleep apnoea (OSA). During awake supine quiet nasal breathing, inspiratory tongue movement, quantified with tagged magnetic resonance imaging (MRI), and inspiratory phasic genioglossus EMG normalised to maximum EMG were measured in four tongue compartments of people with and without OSA. Larger tongue anterior (dilatory) movement was associated with higher phasic genioglossus EMG for 68% of compartments. OSA participants had an ∼7-times higher odds of having at least one compartment for which a larger anterior tongue movement was not associated with a higher phasic EMG than controls. Therefore, higher genioglossus phasic EMG does not consistently translate into tongue dilatory movement, particularly in people with OSA. Large dilatory tongue movements can occur despite minimal genioglossus inspiratory activity, suggesting co-activation of other pharyngeal muscles.

Does cross-education minimize the loss of muscle force and power and sEMG amplitude during short-term detraining in older women who are recreationally engaged in resistance training?

This study aimed to investigate whether 4 weeks of unilateral resistance training (RT) could attenuate the decline in muscle function in the contralateral limb of older women recreationally engaged in RT compared to control group (CTL). Twenty-four participants completed a 10-week RT before the cross-education (CR-Edu) phase and subsequent detraining. Afterward, participants were randomized into two groups: CTL (n = 8 women, n = 16 legs) who underwent 4 weeks of detraining without any training, and CR-Edu (n = 16 women, n = 16 legs) who performed 4 weeks of unilateral RT. Muscle force, power, and surface electromyography were measured unilaterally before and after the 4-week period, using five repetitions conducted at 40% and 60% of the 1RM. The results showed a reduction in muscle force at both 40% and 60% of 1RM, as well as a decrease in power at 60% of 1RM (P-time < 0.05) without significant differences between the two groups (P interaction > 0.05). There was a decline in power at 60% of 1RM (P-time < 0.05) but no significant change at 40% of 1RM (P-time > 0.05), and again, no significant differences were observed between the groups (P-interaction > 0.05). The surface electromyography of vastus lateralis decreased only in the CTL group (P-interaction < 0.05). Older women recreationally engaged in RT who perform in unilateral leg extension compared to a brief period of detraining seem not to retain muscle force and power, and sEMG amplitude of their homologous and contralateral limb.

Automatic selection of IMFs to denoise the sEMG signals using EMD

Surface Electromyography (sEMG) signals are muscle activation signals, which has applications in muscle diagnosis, rehabilitation, prosthetics, and speech etc. However, they are known to be affected by noises such as Power Line Interference (PLI), motion artifacts etc. Currently, Empirical Mode Decomposition (EMD) and its modifications such as Ensemble EMD (EEMD), and Complementary EEMD (CEEMD) are used to decompose EMG into a series of Intrinsic Mode Functions (IMFs). The denoised EMG can be obtained from the selected IMFs. Statistical methods are used to select the signal dominant IMFs to reconstruct the denoised signal. In this work, a novel procedure is proposed to automatically separate noisy IMFs from the original sEMG signal. For this purpose, Permutation Entropy (PE) is employed in EEMD sifting process called Partly EEMD (PEEMD), to separate the noisy IMFs from the original sEMG signal according to the preset PE threshold. PEEMD decomposes the original signal into various modes according to a preset PE threshold and the denoised signal is reconstructed from resultant IMFs. The PEEMD denoising procedure is applied on the experimental sEMG data collected from eight subjects, that include six various upper limb movement classes. The proposed denoising procedure achieved an improved denoising performance in comparison with EMD, EEMD, and CEEMD. An alternate measure called Sample Entropy (SE) is also used in place of PE, for the automated sifting process as a comparison. Signal to Noise Ratio (SNR), Root Mean Square Error (RMSE), and Reconstruction Error (RE) parameters are used to evaluate the denoising performance. The results, averaged across eight subjects, demonstrate that the proposed denoising procedure outperforms the state-of-the-art EMD techniques in terms of these performance measures on the experimentally collected sEMG data samples.

Review of electromyography onset detection methods for real-time control of robotic exoskeletons

BACKGROUND

Electromyography (EMG) is a classical technique used to record electrical activity associated with muscle contraction and is widely applied in Biomechanics, Biomedical Engineering, Neuroscience and Rehabilitation Robotics. Determining muscle activation onset timing, which can be used to infer movement intention and trigger prostheses and robotic exoskeletons, is still a big challenge. The main goal of this paper was to perform a review of the state-of-the-art of EMG onset detection methods. Moreover, we compared the performance of the most commonly used methods on experimental EMG data.

METHODS

A total of 156 papers published until March 2022 were included in the review. The papers were analyzed in terms of application domain, pre-processing method and EMG onset detection method. The three most commonly used methods [Single (ST), Double (DT) and Adaptive Threshold (AT)] were applied offline on experimental intramuscular and surface EMG signals obtained during contractions of ankle and knee joint muscles.

RESULTS

Threshold-based methods are still the most commonly used to detect EMG onset. Compared to ST and AT, DT required more processing time and, therefore, increased onset timing detection, when applied on experimental data. The accuracy of these three methods was high (maximum error detection rate of 7.3%), demonstrating their ability to automatically detect the onset of muscle activity. Recently, other studies have tested different methods (especially Machine Learning based) to determine muscle activation onset offline, reporting promising results.

CONCLUSIONS

This study organized and classified the existing EMG onset detection methods to create consensus towards a possible standardized method for EMG onset detection, which would also allow more reproducibility across studies. The three most commonly used methods (ST, DT and AT) proved to be accurate, while ST and AT were faster in terms of EMG onset detection time, especially when applied on intramuscular EMG data. These are important features towards movement intention identification, especially in real-time applications. Machine Learning methods have received increased attention as an alternative to detect muscle activation onset. However, although several methods have shown their capability offline, more research is required to address their full potential towards real-time applications, namely to infer movement intention.

Lumbar muscle adaptations to external perturbations are modulated by trunk posture

PURPOSE

To investigate if the recruitment of different regions within the lumbar extensor muscles in response to unexpected perturbations depends on trunk posture.

METHODS

In a semi-seated posture, healthy adult participants experienced unexpected posterior-anterior trunk perturbations in three different postures: neutral, trunk flexion and left trunk rotation. High-density surface electromyography was used to identify the regional distribution of activation within the lumbar erector spinae muscles. The effect of posture and side (left vs right) on muscle activity and centroid coordinates was investigated at baseline and in response to perturbations.

RESULTS

Higher muscle activity was observed in trunk flexion compared to neutral and rotation postures at baseline (multiple p < 0.001) and in response to the perturbation (multiple p < 0.01). At baseline, the centroid of the electromyographic amplitude distribution was localized more medially in trunk flexion compared to trunk neutral posture (p = 0.003), while activation was localized more laterally in response to the perturbation (multiple p < 0.05). When the trunk was rotated, the electromyographic amplitude distribution was localized more cranially on the left than the right side, both at baseline (p = 0.001) and in response to the perturbation (p = 0.001). Finally, a more lateral location of the centroid on the left side in rotation compared to neutral posture was observed in response to the perturbation (multiple p < 0.001).

CONCLUSIONS

Regional differences in the distribution of electromyographic amplitude indicate that different muscle regions were recruited in different trunk postures and in response to perturbations, possibly based on regional mechanical advantage of the erector spinae muscle fibers.

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.

Continuous Motion Estimation of Knee Joint Based on a Parameter Self-Updating Mechanism Model

Estimation of continuous motion of human joints using surface electromyography (sEMG) signals has a critical part to play in intelligent rehabilitation. Traditional methods always use sEMG signals as inputs to build regression or biomechanical models to estimate continuous joint motion variables. However, it is challenging to accurately estimate continuous joint motion in new subjects due to the non-stationarity and individual differences in sEMG signals, which greatly limits the generalisability of the method. In this paper, a continuous motion estimation model for the human knee joint with a parameter self-updating mechanism based on the fusion of particle swarm optimization (PSO) and deep belief network (DBN) is proposed. According to the original sEMG signals of different subjects, the method adaptively optimized the parameters of the DBN model and completed the optimal reconstruction of signal feature structure in high-dimensional space to achieve the optimal estimation of continuous joint motion. Extensive experiments were conducted on knee joint motions. The results suggested that the average root mean square errors (RMSEs) of the proposed method were 9.42° and 7.36°, respectively, which was better than the results obtained by common neural networks. This finding lays a foundation for the human-robot interaction (HRI) of the exoskeleton robots based on the sEMG signals.

The Role of Back Muscle Dysfunctions in Chronic Low Back Pain: State-of-the-Art and Clinical Implications

Changes in back muscle function and structure are highly prevalent in patients with chronic low back pain (CLBP). Since large heterogeneity in clinical presentation and back muscle dysfunctions exists within this population, the potential role of back muscle dysfunctions in the persistence of low back pain differs between individuals. Consequently, interventions should be tailored to the individual patient and be based on a thorough clinical examination taking into account the multidimensional nature of CLBP. Considering the complexity of this process, we will provide a state-of-the-art update on back muscle dysfunctions in patients with CLBP and their implications for treatment. To this end, we will first give an overview of (1) dysfunctions in back muscle structure and function, (2) the potential of exercise therapy to address these dysfunctions, and (3) the relationship between changes in back muscle dysfunctions and clinical parameters. In a second part, we will describe a framework for an individualised approach for back muscle training in patients with CLBP.

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

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

Prolonged slumped sitting causes neck pain and increased axioscapular muscle activity during a computer task in healthy participants - A randomized crossover study

INTRODUCTION

Sitting posture may contribute to spinal pain. Effects of postures on pain, sensitivity and muscle activity during computer tasks were investigated.

METHODS

Twenty-five healthy participants, seated at a workstation without backrest, completed four, 15-min typing tasks: A)Upright with forearm-support; B)Upright without forearm-support; C)Slumped with forearm-support; D)Slumped without forearm-support. Participants rated pain every minute on a numerical rating scale (NRS). RMS-EMG was recorded from upper/lower trapezius (UT, LT), serratus anterior and anterior/middle deltoid. At baseline and after tasks, pressure pain thresholds (PPTs) were recorded bilaterally over the head, UT, and leg.

RESULTS

All tasks caused clinically relevant increased NRS (≥2/10) compared to baseline (P < 0.001). NRS was higher in Task-D (P < 0.003) and lower in Task-B (P < 0.005) than others. PPTs did not change from baseline. Task-D caused higher UT and LT RMS-EMG (P < 0.02) than other tasks.

CONCLUSION

A 15-min task caused pain irrespective of posture with some causing larger changes than others.

Muscle synergies in Parkinson's disease before and after the deep brain stimulation of the bilateral subthalamic nucleus

The aim of this study is to quantitatively assess motor control changes in Parkinson's disease (PD) patients after bilateral deep brain stimulation of the subthalamic nucleus (STN-DBS), based on a novel muscle synergy evaluation approach. A group of 20 PD patients evaluated at baseline (before surgery, T₀), at 3 months (T₁), and at 12 months (T₂) after STN-DBS surgery, as well as a group of 20 age-matched healthy control subjects, underwent an instrumented gait analysis, including surface electromyography recordings from 12 muscles. A smaller number of muscle synergies was found in PD patients (4 muscle synergies, at each time point) compared to control subjects (5 muscle synergies). The neuromuscular robustness of PD patients-that at T₀ was smaller with respect to controls (PD T₀: 69.3 ± 2.2% vs. Controls: 77.6 ± 1.8%, p = 0.004)-increased at T₁ (75.8 ± 1.8%), becoming not different from that of controls at T₂ (77.5 ± 1.9%). The muscle synergies analysis may offer clinicians new knowledge on the neuromuscular structure underlying PD motor types of behavior and how they can improve after electroceutical STN-DBS therapy.

Estimating and minimizing movement artifacts in surface electromyogram

While recording surface electromyography [sEMG], it is possible to record the electrical activities coming from the muscles and transients in the half-cell potential at the electrode-electrolyte interface due to micromovements of the electrode-skin interface. Separating the two sources of electrical activity usually fails due to the overlapping frequency characteristics of the signals. This paper aims to develop a method that detects movement artifacts and suggests a minimization technique. Towards that aim, we first estimated the frequency characteristics of movement artifacts under various static and dynamic experimental conditions. We found that the extent of the movement artifact depended on the nature of the movement and varied from person to person. Our study's highest movement artifact frequency for the stand position was 10 Hz, tiptoe 22, walk 32, run 23, jump from box 41, and jump up and down 40 Hz. Secondly, using a 40 Hz highpass filter, we cut out most of the frequencies belonging to the movement artifacts. Finally, we checked whether the latencies and amplitudes of reflex and direct muscle responses were still observed in the highpass-filtered sEMG. We showed that the 40 Hz highpass filter did not significantly alter reflex and direct muscle variables. Therefore, we recommend that researchers who use sEMG under similar conditions employ the recommended level of highpass filtering to reduce movement artifacts from their records. However, suppose different movement conditions are used. In that case, it is best to estimate the frequency characteristics of the movement artifact before applying any highpass filtering to minimize movement artifacts and their harmonics from sEMG.

Comparison of EMG activity in shank muscles between individuals with and without chronic ankle instability when running on a treadmill

Changes in movement capabilities after an injury to the ankle may impose adaptations in the peripheral and central nervous system. The purpose of our study was to compare the electromyogram (EMG) profile of ankle stabilizer muscles and stride-time variation during treadmill running in individuals with and without chronic ankle instability (CAI). Recreationally active individuals with (n = 12) and without (n = 15) CAI ran on a treadmill at two speeds. EMG activity of four shank muscles as well as tibial acceleration data were recorded during the running trials. EMG amplitude, timing of EMG peaks, and variation in stride-time were analyzed from 30 consecutive stride cycles. EMG data were time-normalized to stride duration and amplitude was normalized relative to the appropriate maximal voluntary contraction (MVC) task. Individuals with CAI had similar EMG amplitudes and peak timing, but an altered order of peak EMG activity in ankle stabilizer muscles, a significantly greater EMG amplitude for PL with an increase in speed, and a greater stride-time variability during treadmill running compared with individuals who had no history of ankle sprains. The results of our study indicate that individuals with CAI exhibit altered activation strategies for ankle stabilizer muscles when running on a treadmill.

Current developments in surface electromyography

Background/aim

Surface electromyography (surface EMG) is a primary technique to detect the electrical activities of muscles through surface electrodes. In recent years, surface EMG applications have grown from conventional fields into new fields. However, there is a gap between the progress in the research of surface EMG and its clinical acceptance, characterized by the translational knowledge and skills in the widespread use of surface EMG among the clinician community. To reduce this gap, it is necessary to translate the updated surface EMG applications and technological advances into clinical research. Therefore, we aimed to present a perspective on recent developments in the application of surface EMG and signal processing methods.

Materials and methods

We conducted this scoping review following the Joanna Briggs Institute (JBI) method. We conducted a general search of PubMed and Web of Science to identify key search terms. Following the search, we uploaded selected articles into Rayyan and removed duplicates. After prescreening 133 titles and abstracts, we assessed 91 full texts according to the inclusion criteria.

Results

We concluded that surface EMG has made innovative technological progress and has research potential for routine clinical applications and a wide range of applications, such as neurophysiology, sports and art performances, biofeedback, physical therapy and rehabilitation, assessment of physical exercises, muscle strength, fatigue, posture and postural control, movement analysis, muscle coordination, motor synergies, modelling, and more. Novel methods have been applied for surface EMG signals in terms of time domain, frequency domain, time-frequency domain, statistical methods, and nonlinear methods.

Conclusion

Translating innovations in surface EMG and signal analysis methods into routine clinical applications can be a helpful tool with a growing and valuable role in muscle activation measurement in clinical practices. Thus, researchers must build many more interfaces that give opportunities for continuing education and research with more contemporary techniques and devices.

Comparison of EMG Activity in Leg Muscles between Overground and Treadmill Running

INTRODUCTION

Treadmills have been widely used for training and performance testing during which the treadmill grade is usually set to 0%-2% grade. The purpose of our study was to compare the level of activation of lower body muscles when running at two speeds in an overground condition and on a treadmill at 0%, 1%, and 2% grades.

METHODS

We recorded EMG data of eight lower body muscles from 13 recreationally active individuals during overground and treadmill running at 2.92 and 4.58 m·s -1 . Maximal voluntary contraction (MVC) tests were performed (3 × 6 s) to identify maximal torque and EMG values. The stride cycles, from one foot strike to the next, were identified using a pair of triaxial accelerometers. A two-way repeated-measures ANOVA was used to examine the differences in EMG activity across running conditions and speeds. Cohen's d effect size was calculated to indicate the difference between the overground and the treadmill running conditions.

RESULTS

The effect sizes were moderate to negligible for differences between the EMG integral values for overground running and the three treadmill grades. The coefficient of variation for stride time during overground running was significantly larger than that of the treadmill running at 4.58 m·s -1 .

CONCLUSIONS

The results showed that the overall EMG profiles of the thigh and shank muscles were similar for the overground and treadmill conditions, but the similarity was greatest for thigh muscles when running on the treadmill at 1% grade and for shank muscles at 2% grade. The variability in stride time was greater during overground running than when running on a treadmill and was associated with elevated EMG activity of some muscles.

Comparing Motor-Evoked Potential Characteristics of NEedle versus suRFACE Recording Electrodes during Spinal Cord Monitoring-The NERFACE Study Part I

Muscle-recorded transcranial electrical stimulation motor-evoked potentials (mTc-MEPs) are used to assess the spinal cord integrity. They are commonly recorded with subcutaneous needle or surface electrodes, but the different characteristics of mTc-MEP signals recorded with the two types of electrodes have not been formally compared yet. In this study, mTc-MEPs were simultaneously recorded from the tibialis anterior (TA) muscles using surface and subcutaneous needle electrodes in 242 consecutive patients. Elicitability, motor thresholds, amplitude, area under the curve (AUC), signal-to-noise ratio (SNR), and the variability between mTc-MEP amplitudes were compared. Whereas amplitude and AUC were significantly higher in subcutaneous needle recordings (p < 0.01), motor thresholds and elicitability were similar for surface and subcutaneous needle recordings. Moreover, the SNRs were >2 in more than 99.5% of the surface and subcutaneous needle recordings, and the variability between consecutive amplitudes was not significantly different between the two recording electrode types (p = 0.34). Surface electrodes appear to be a good alternative to needle electrodes for spinal cord monitoring. They are non-invasive, can record signals at similar threshold intensities, have adequately high SNRs, and record signals with equivalent variability. Whether surface electrodes are non-inferior to subcutaneous needle electrodes in detecting motor warnings is investigated in part II of the NERFACE study.

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

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

A Novel Screen-Printed Textile Interface for High-Density Electromyography Recording

Recording electrical muscle activity using a dense matrix of detection points (high-density electromyography, EMG) is of interest in a range of different applications, from human-machine interfacing to rehabilitation and clinical assessment. The wider application of high-density EMG is, however, limited as the clinical interfaces are not convenient for practical use (e.g., require conductive gel/cream). In the present study, we describe a novel dry electrode (TEX) in which the matrix of sensing pads is screen printed on textile and then coated with a soft polymer to ensure good skin-electrode contact. To benchmark the novel solution, an identical electrode was produced using state-of-the-art technology (polyethylene terephthalate with hydrogel, PET) and a process that ensured a high-quality sample. The two electrodes were then compared in terms of signal quality as well as functional application. The tests showed that the signals collected using PET and TEX were characterised by similar spectra, magnitude, spatial distribution and signal-to-noise ratio. The electrodes were used by seven healthy subjects and an amputee participant to recognise seven hand gestures, leading to similar performance during offline analysis and online control. The comprehensive assessment, therefore, demonstrated that the proposed textile interface is an attractive solution for practical applications.

Translation of surface electromyography to clinical and motor rehabilitation applications: The need for new clinical figures

Advanced sensors/electrodes and signal processing techniques provide powerful tools to analyze surface electromyographic signals (sEMG) and their features, to decompose sEMG into the constituent motor unit action potential trains, and to identify synergies, neural muscle drive, and EEG-sEMG coherence. However, despite thousands of articles, dozens of textbooks, tutorials, consensus papers, and European and International efforts, the translation of this knowledge into clinical activities and assessment procedures has been very slow, likely because of lack of clinical studies and competent operators in the field. Understanding and using sEMG-based hardware and software tools requires a level of knowledge of signal processing and interpretation concepts that is multidisciplinary and is not provided by most academic curricula in physiotherapy, movement sciences, neurophysiology, rehabilitation, sport, and occupational medicine. The chasm existing between the available knowledge and its clinical applications in this field is discussed as well as the need for new clinical figures. The need for updating the training of physiotherapists, neurophysiology technicians, and clinical technologists is discussed as well as the required competences of trainers and trainees. Indications and examples are suggested and provide a basis for addressing the problem. Two teaching examples are provided in the Supplementary Material.

Frontal plane ankle stiffness increases with axial load independent of muscle activity

Ankle sprains are the most common musculoskeletal injury, typically resulting from excessive inversion of the ankle. One way to prevent excessive inversion and maintain ankle stability is to generate a stiffness that is sufficient to resist externally imposed rotations. Frontal-plane ankle stiffness increases as participants place more weight on their ankle, but whether this effect is due to muscle activation or axial loading of the ankle is unknown. Identifying whether and to what extent axial loading affects ankle stiffness is important in understanding what role the passive mechanics of the ankle joint play in maintaining its stability. The objective of this study was to determine the effect of passive axial load on frontal-plane ankle stiffness. We had subjects seated in a chair as an axial load was applied to the ankle ranging from 10% to 50% body weight. Small rotational perturbations were applied to the ankle in the frontal plane to estimate stiffness. We found a significant, linear, 3-fold increase in ankle stiffness with axial load from the range of 0% body weight to 50% body weight. This increase could not be due to muscle activity as we observed no significant axial-load-dependent change in any of the recorded muscle activations. These results demonstrate that axial loading is a significant contributor to maintaining frontal-plane ankle stability, and that disruptions to the mechanism mediating this sensitivity of stiffness to axial loading may result in pathological cases of ankle instability.

Indexes for motor performance assessment in job integration/reintegration of people with neuromuscular disorders: A systematic review

Individuals of working age affected by neuromuscular disorders frequently experience issues with their capacity to get employment, difficulty at work, and premature work interruption. Anyway, individuals with a disability could be able to return to work, thanks to targeted rehabilitation as well as ergonomic and training interventions. Biomechanical and physiological indexes are important for evaluating motor and muscle performance and determining the success of job integration initiatives. Therefore, it is necessary to determinate which indexes from the literature are the most appropriate to evaluate the effectiveness and efficiency of the return-to-work programs. To identify current and future valuable indexes, this study uses a systematic literature review methodology for selecting articles published from 2011 to March 30, 2021 from Scopus, Web of Science, and PubMed and for checking the eligibility and the potential bias risks. The most used indexes for motor performance assessment were identified, categorized, and analyzed. This review revealed a great potential for kinetic, kinematic, surface electromyography, postural, and other biomechanical and physiological indexes to be used for job integration/reintegration. Indeed, wearable miniaturized sensors, kinematic, kinetic, and sEMG-based indexes can be used to control collaborative robots, classify residual motor functions, and assess pre-post-rehabilitation and ergonomic therapies.

Mental fatigue does not substantially alter neuromuscular function in young, healthy males and females

The neuromuscular mechanisms leading to impaired motor performance after mental fatigue (MF) are not well-understood and little is known of sex-specific differences in the neuromuscular response to MF. The purpose of this study was to investigate sex-related differences in the impact of MF on neuromuscular function. Thirty young, healthy adults (15F, 15M) performed the Psychomotor Vigilance Task (PVT) to induce MF and watched the Earth documentary (control) for 30 min in a random and counterbalanced order. Before and after each task, measurements of neuromuscular function during submaximal dorsiflexion contractions were obtained. At the end of the PVT, females and males had a slower reaction time (p<0.001, η²_p=0.41) and reported higher fatigue (p<0.001, η²_p=0.50), suggesting the PVT induced MF. After the PVT, females and males demonstrated a decline in force during 10% maximum voluntary contractions (MVC) (p=0.006, η²_p=0.24), slower motor unit firing rate during 20% MVC (p=0.04, η²_p=0.15) and a longer cortical silent period (p=0.01, η²_p=0.22). However, similar changes were observed in the control condition suggesting MF is unlikely to substantially alter neuromuscular function during submaximal isometric contractions in young, healthy adults. Results also suggest neuromuscular function after a MF task is similar between young, healthy females and males. Further research is required to investigate populations with higher fatigue, such as multiple sclerosis or chronic fatigue syndrome.

Teaching Essential EMG Theory to Kinesiologists and Physical Therapists Using Analogies Visual Descriptions, and Qualitative Analysis of Biophysical Concepts

Electromyography (EMG) is a multidisciplinary field that brings together allied health (kinesiology and physical therapy) and the engineering sciences (biomedical and electrical). Since the physical sciences are used in the measurement of a biological process, the presentation of the theoretical foundations of EMG is most conveniently conducted using math and physics. However, given the multidisciplinary nature of EMG, a course will most likely include students from diverse backgrounds, with varying levels of math and physics. This is a pedagogical paper that outlines an approach for teaching foundational concepts in EMG to kinesiologists and physical therapists that uses a combination of analogies, visual descriptions, and qualitative analysis of biophysical concepts to develop an intuitive understanding for those who are new to surface EMG. The approach focuses on muscle fiber action potentials (MFAPs), motor unit action potentials (MUAPs), and compound muscle action potentials (CMAPs) because changes in these waveforms are much easier to identify and describe in comparison to the surface EMG interference pattern (IP).

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

OBJECTIVE

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

APPROACH

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

MAIN RESULTS

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

SIGNIFICANCE

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

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.

Applying Machine Learning to Finger Movements Using Electromyography and Visualization in Opensim

Electromyographic signals have been used with low-degree-of-freedom prostheses, and recently with multifunctional prostheses. Currently, they are also being used as inputs in the human-computer interface that controls interaction through hand gestures. Although there is a gap between academic publications on the control of an upper-limb prosthesis developed in laboratories and its service in the natural environment, there are attempts to achieve easier control using multiple muscle signals. This work contributes to this, using a database and biomechanical simulation software, both open access, to seek simplicity in the classifiers, anticipating their implementation in microcontrollers and their execution in real time. Fifteen predefined finger movements of the hand were identified using classic classifiers such as Bayes, linear and quadratic discriminant analysis. The idealized movements of the database were modeled with Opensim for visualization. Combinations of two preprocessing methods-the forward sequential selection method and the feature normalization method-were evaluated to increase the efficiency of these classifiers. The statistical methods of cross-validation, analysis of variance (ANOVA) and Duncan were used to validate the results. Furthermore, the classifier with the best recognition result was redesigned into a new feature space using the sparse matrix algorithm to improve it, and to determine which features can be eliminated without degrading the classification. The classifiers yielded promising results-the quadratic discriminant being the best, achieving an average recognition rate for each individual considered of 96.16%, and with 78.36% for the total sample group of the eight subjects, in an independent test dataset. The study ends with the visual analysis under Opensim of the classified movements, in which the usefulness of this simulation tool is appreciated by revealing the muscular participation, which can be useful during the design of a multifunctional prosthesis.

Influence of Feet Position and Execution Velocity on Muscle Activation and Kinematic Parameters During the Inclined Leg Press Exercise

BACKGROUND

The leg press is one of the most typical exercises for strengthening the lower limbs. The objectives of this study were to compare 5 inclined leg press exercise conditions, varying the feet width stance (100% or 150% hip width), the feet rotation (0° or 45° external rotation) on the footplate and using 2 different movement velocities (MVs; maximum intended, and 2:2 seconds steady-paced velocities) to determine their effect on muscle activation as well as on the kinematic parameters between trained men and trained women.

HYPOTHESES

There will be no significant differences in muscle activation with regard to the feet position. The higher the MV, the greater the muscle activation.

STUDY DESIGN

A cross-sectional cohort study.

LEVEL OF EVIDENCE

Level 3.

METHODS

A repeated-measures between-group design was performed to examine muscle activation and kinematic parameters for the different conditions between gender groups. The level of significance was set at alpha = 0.05 for all statistical analyses.

RESULTS

Muscle activation presented no differences between conditions regarding feet width stance or feet rotation. Furthermore, muscle activation was greater during positive phases than negative phases of the exercise for all conditions and was also greater under maximum intended velocity conditions compared with steady-paced conditions. Otherwise, the muscle activation pattern presented slight differences by gender. In men, the greatest muscle activation was for the vastus medialis, followed by the vastus lateralis (VL), rectus femoris (RF), and gluteus medialis (GMED), while in women, the greatest muscle activation was for the vastus medialis, followed by the RF, VL, and GMED. Finally, greater mean propulsive velocity, maximum velocity, maximum power, and footplate displacement values were reported for men than for women under all the conditions.

CONCLUSION

The inclined leg press exercise produces the highest muscle activation in the vastus medialis, regardless of the velocity, feet stance, or gender.

CLINICAL RELEVANCE

Given that there are no differences in muscle activation regarding the feet stance, a participant's preferred feet stance should be encouraged during the inclined leg press exercise. Furthermore, the MV would preferably depend on the session objective (a training or a rehabilitation program), being aware that there is greater muscle activation at higher speeds. The inclined leg press exercise could be performed as a closed kinetic chain exercise when the main objective is to activate the vastus medialis.

Real-time classification of movement patterns of tremor patients

The process of diagnosing tremor patients often leads to misdiagnoses. Therefore, existing technical methods for analysing tremor are needed to more effectively distinguish between different diseases. For this purpose, a system has been developed that classifies measured tremor signals in real time. To achieve this, the hand tremor of 561 subjects has been measured in different hand positions. Acceleration and surface electromyography are recorded during the examination. For this study, data from subjects with Parkinson's Disease, Essential Tremor, and physiological tremor are considered. In a first signal analysis feature extraction is performed, and the resulting features are examined for their discriminative value. In a second step, three classification models based on different pattern recognition techniques are developed to classify the subjects with respect to their tremor type. With a trained decision tree, the three tremor types can be classified with a relative diagnostic accuracy of 83.14%. A neural network achieves 84.24% and the combination of both classifiers yields a relative diagnostic accuracy of 85.76%. The approach is promising and involving more features of the recorded time series will improve the discriminative value.