Standards of instrumentation of EMG Tankisi, Hatice; Burke, David; Cui, Liying ...
Clinical neurophysiology,
January 2020, 2020-Jan, 2020-01-00, 20200101, 2020, Volume:
131, Issue:
1
Journal Article
Peer reviewed
Open access
•Standard instrumentation ensures high quality recordings and enables comparison of results.•This consensus document on “Standards of Instrumentation of EMG” is written by an expert panel.•This ...report covers technical aspects as well as topics for optimal and standardized examinations.
Standardization of Electromyography (EMG) instrumentation is of particular importance to ensure high quality recordings. This consensus report on “Standards of Instrumentation of EMG” is an update and extension of the earlier IFCN Guidelines published in 1999. First, a panel of experts in different fields from different geographical distributions was invited to submit a section on their particular interest and expertise. Then, the merged document was circulated for comments and edits until a consensus emerged.
The first sections in this document cover technical aspects such as instrumentation, EMG hardware and software including amplifiers and filters, digital signal analysis and instrumentation settings. Other sections cover the topics such as temporary storage, trigger and delay line, averaging, electrode types, stimulation techniques for optimal and standardised EMG examinations, and the artefacts electromyographers may face and safety rules they should follow. Finally, storage of data and databases, report generators and external communication are summarized.
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.
When sampling electromyograms (EMGs) with one pair of electrodes, it seems implicitly assumed the detected signal reflects the net muscle excitation. However, this assumption is discredited by ...observations of local muscle excitation. Therefore, we hypothesize that the accurate assessment of muscle excitation requires multiple EMG detection and consideration of electrode-fiber alignment. We advise prudence when drawing inferences from individually collected EMGs.
Surface Electromyography (EMG)-based pattern recognition methods have been investigated over the past years as a means of controlling upper limb prostheses. Despite the very good reported performance ...of myoelectric controlled prosthetic hands in lab conditions, real-time performance in everyday life conditions is not as robust and reliable, explaining the limited clinical use of pattern recognition control. The main reason behind the instability of myoelectric pattern recognition control is that EMG signals are non-stationary in real-life environments and present a lot of variability over time and across subjects, hence affecting the system's performance. This can be the result of one or many combined changes, such as muscle fatigue, electrode displacement, difference in arm posture, user adaptation on the device over time and inter-subject singularity. In this paper an extensive literature review is performed to present the causes of the drift of EMG signals, ways of detecting them and possible techniques to counteract for their effects in the application of upper limb prostheses. The suggested techniques are organized in a table that can be used to recognize possible problems in the clinical application of EMG-based pattern recognition methods for upper limb prosthesis applications and state-of-the-art methods to deal with such problems.
Le CANVAS syndrome neurologique rare associe neuropathie sensitive, aréflexie vestibulaire et ataxie cérébelleuse. Il s’agit d’une pathologie autosomique récessive liée à l’expansion bi-allélique de ...l’intron AAAGG du gène RFC1.
À travers cette série de cas nous souhaitions établir les caractéristiques cliniques et électrophysiologiques de notre cohorte et de les confronter aux données de la littérature.
Nous avons recueilli les patients suivis au CHU d’Amiens pour lesquels le diagnostic de CANVAS avait été confirmé biologiquement. Nous avons recueilli les données neurophysiologiques : étude de la conduction nerveuse motrice et sensitive, réflexe H, blink reflex, étude en détection. Les données cliniques, les antécédents personnels et familiaux ont été consignés ainsi que les données paracliniques (imagerie, bilan ORL, bilan ophtalmologique, bilan paranéoplasique, bilan immunologique).
Huit patients (5 hommes, 3 femmes) présentaient un diagnostic confirmé de CANVAS. L’âge moyen de début des symptômes était de 53 ans, la symptomatologie évoluait en moyenne depuis 10,6 ans avec comme tableau initial soit des troubles de l’équilibre lentement évolutifs soit des troubles sensitifs des quatre membres. Cinq patients présentaient des antécédents de cancers familiaux ou personnels. Tous les patients présentaient une atteinte sensitive non longueur-dépendante, le réflexe H était préservé chez 7 patients.
Cette série illustre la présence des antécédents néoplasiques chez plus de la moitié des patients. Un lien potentiellement intéressant puisque la fonction des gènes RFC est d’activer l’ADN polymérase. La préservation du réflexe H chez la quasi-totalité de nos patients rejoint les données de la littérature, il s’agirait d’une neuropathie unique épargnant les fibres IA innervant les fibres musculaires afférentes.
Le CANVAS est une pathologie neurodégénérative multisystémique héréditaire dont la physiopathologie reste méconnue, notre série souligne la conservation du réflexe H et les antécédents néoplasiques.
A key challenge associated with myoelectric prosthesis limbs is the acquisition of a good quality gesture intent signal from the residual anatomy of an amputee. In this study, the authors aim to ...overcome this limitation by observing the classification accuracy of the fusion of wearable electromyography (EMG) and near‐infrared (NIR) to classify eight hand gesture motions across 12 able‐bodied participants. As part of the study, they investigate the classification accuracy across a multi‐layer perceptron neural network, linear discriminant analysis and quadratic discriminant analysis for different sensing configurations, i.e. EMG‐only, NIR‐only and EMG‐NIR. A separate offline ultrasound scan was conducted as part of the study and served as a ground truth and contrastive basis for the results picked up from the wearable sensors, and allowed for a closer study of the anatomy along the humerus during gesture motion. Results and findings from the work suggest that it could be possible to further develop transhumeral prosthesis using affordable, ergonomic and wearable EMG and NIR sensing, without the need for invasive neuromuscular sensors or further hardware complexity.
Les douleurs neuropathiques présentent une variation circadienne. Elles entraînent une altération de la qualité du sommeil. L’effet bénéfique du jeune intermittent est mis en évidence dans des études ...récentes.
Évaluer l’effet du jeune intermittent sur les douleurs neuropathiques. Étudier la corrélation de cet effet avec les données électromyographiques.
Étude cohorte colligeant 60 patients présentant une douleur neuropathique périphérique chronique confirmée par le score DN4. Ces patients ont suivi un jeune intermittent de 15 heures pendant 25 jours. Tous les patients ont eu un examen électroneuromyographique (ENMG). L’impact du jeune intermittent sur la douleur neuropathique a été évalué à l’aide de l’échelle numérique (EN), l’appréciation de la qualité du sommeil et l’évolution circadienne avant et durant le jeune.
Le jeune intermittent s’accompagne d’une modification de l’évolution circadienne de la douleur neuropathique chez 28,4 % des patients, d’une diminution de la moyenne du score EN (p<0,001). Une amélioration de la qualité de sommeil est rapportée (p<0,001). Cependant, aucune corrélation entre la sévérité électrique objectivée par électroneuromyogramme et l’effet du jeune sur les douleurs neuropathiques n’a été trouvé (p=0,1).
Des études cliniques sur le jeûne intermittent ont montré une amélioration des douleurs chroniques En effet, le jeune intermittent réduit le taux de cytokines pro-inflammatoires. Nos résultats confirment l’impact bénéfique du jeune intermittent. Cependant, la sévérité électrique n’a pas d’effet sur l’évolution de la douleur neuropathique durant le jeune intermittent.
Notre étude montre un effet bénéfique du jeune intermittent chez les patients souffrant de douleurs neuropathiques mais cet effet n’est pas corrélé à la sévérité électrique de la neuropathie.
•Standards for EMG and Neurography are suggested.•Electrophysiological tests in Pediatric practice are summarized.•Implementation and clinical utility of less common methods for EMG and neurography ...are presented.
This document is an update and extension of ICCN Standards published in 1999. It is the consensus of experts on the current status of EMG and Neurography methods. A panel of authors from different countries with different approach to routines in neurophysiological methods was chosen based on their particular interest and previous publications. Each member of the panel submitted a section on their particular area of interest and these submissions were circulated among the panel members for edits and comments. This process continued until a consensus was reached.
The document covers EMG topics such as conventional EMG, Macro EMG, applications of surface EMG and electrical impedance myography. Single Fiber EMG is not included, since it is the topic in a separate IFCN document. A neurography section covers topics such as motor and sensory neurography, F wave recordings, H-reflex, short segment recordings, CMAP scan and motor unit number methods. Other sections cover repetitive nerve stimulation and Pediatric electrodiagnostic testing.
Each method includes a description of methodologies, pitfalls, and the use of reference values. Clinical applications accompany some of these sections.
Aims
The innervation zone asymmetry of the external anal sphincter (EAS) has been investigated as a risk factor for the development of fecal incontinence (FI). This study aims to utilize an ...intra‐rectal high‐density surface electromyogram (HD‐sEMG) recording and advanced HD‐sEMG decomposition technique to characterize the effects of aging on the asymmetry of EAS functional innervation.
Methods
HD‐sEMG signals were recorded intra‐rectally from six healthy young and seven healthy elderly women during voluntary contractions of the EAS. EMG signals were decomposed into constituent motor unit action potentials (MUAPs) and the innervation zone of each decomposed motor unit was identified. Asymmetry index (AI) was defined and calculated for all subjects. The maximum squeezing pressures of the EAS were also measured for all subjects as a comparison.
Results
The HD‐sEMG decomposition and AI calculation were successfully performed from EMG data acquired from all the subjects. The AI values were 28.7 ± 17.0% for the young group and 55.6 ± 18.8% for the elderly group. The AI and EAS contraction strength were found to be negatively correlated (P < 0.05). A two‐tailed student's t‐test demonstrated a significant increase in AI with age by comparison between two groups (P < 0.05).
Conclusions
Our work demonstrates, for the first time, that EAS functional innervation tends to become increasingly asymmetrical with advancing age, and this increase is associated with a compromised anorectal function. Results suggest that the intra‐rectal HD‐sEMG will serve as an advanced tool for assessing and monitoring the anorectal neuromuscular function minimally invasively under different pathophysiological conditions.
•A neural-network (NN) approach to assess gait events from sEMG signal was proposed.•The influence on NN performances of different sEMG-signal processing is tested.•Linear envelope (cut-off frequency ...= 5 Hz) allows to achieve the best NN performances.•The effect of decreasing sEMG-probe number included in the set-up is also tested.•Reducing to two distal-leg probes seems a good compromise to meet clinical needs.
Machine-learning approaches are satisfactorily implemented for classifying and assessing gait events from only surface electromyographic (sEMG) signals during walking. However, it is acknowledged that the choice of sEMG-processing type may affect the reliability of methodologies based on it. Analogously, the number of sEMG signals involved in machine-learning procedure could influence the classification process. Aim of this study is to quantify the impact of different EMGsignal- processing specifications and/or different complexity of the experimental sEMG-protocol (different number of sEMG-sensors) on the performance of a neural-network-based approach for binary classifying gait phases and predicting gait-event timing. To this purpose, sEMG signals are collected from eight leg-muscles in about 10.000 strides from 23 healthy adults during walking and then fed to a multi-layer perceptron model. Four different signal-processing approaches are tested and five experimental set-ups (from four to one sEMG sensors per leg) are compared. Results indicate that both the choice of sEMG processing and the reduction of sEMG-protocol complexity actually affect classification/prediction performances. Moreover, the study succeeds in the double goal of identifying the linear envelope as the sEMG-processing type which reaches the best neural-network performance (classification accuracy of 93.4 ± 2.3 %; mean absolute error 21.6 ± 7.0 and 38.1 ± 15.2 ms for heel-strike/toe-off prediction, respectively) and providing a quantification of the progressive deterioration of classification/prediction performances with the reduction of the number of sensors used (from 93.4 ± 2.3%–79.9 ± 6.1 % for classification accuracy). These findings could be very useful for clinics to the aim of choosing the most suitable approach balancing technical performances, patient comfort, and clinical needs.
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