Tutorial: Analysis of motor unit discharge characteristics from high-density surface EMG signals.


Journal

Journal of electromyography and kinesiology : official journal of the International Society of Electrophysiological Kinesiology
ISSN: 1873-5711
Titre abrégé: J Electromyogr Kinesiol
Pays: England
ID NLM: 9109125

Informations de publication

Date de publication:
Aug 2020
Historique:
pubmed: 22 5 2020
medline: 11 11 2020
entrez: 22 5 2020
Statut: ppublish

Résumé

Recent work demonstrated that it is possible to identify motor unit discharge times from high-density surface EMG (HDEMG) decomposition. Since then, the number of studies that use HDEMG decomposition for motor unit investigations has increased considerably. Although HDEMG decomposition is a semi-automatic process, the analysis and interpretation of the motor unit pulse trains requires a thorough inspection of the output of the decomposition result. Here, we report guidelines to perform an accurate extraction of motor unit discharge times and interpretation of the signals. This tutorial includes a discussion of the differences between the extraction of global EMG signal features versus the identification of motor unit activity for physiological investigations followed by a comprehensive guide on how to acquire, inspect, and decompose HDEMG signals, and robust extraction of motor unit discharge characteristics.

Identifiants

pubmed: 32438235
pii: S1050-6411(20)30041-9
doi: 10.1016/j.jelekin.2020.102426
pii:
doi:

Types de publication

Journal Article

Langues

eng

Sous-ensembles de citation

IM

Pagination

102426

Informations de copyright

Copyright © 2020 Elsevier Ltd. All rights reserved.

Auteurs

A Del Vecchio (A)

Department of Bioengineering, Imperial College London, SW7 2AZ London, UK.

A Holobar (A)

Faculty of Electrical Engineering and Computer Science, University of Maribor, Koroška cesta 46, 2000 Maribor, Slovenia.

D Falla (D)

Centre of Precision Rehabilitation for Spinal Pain (CPR Spine), School of Sport, Exercise and Rehabilitation Sciences, College of Life and Environmental Sciences, University of Birmingham, Birmingham, UK.

F Felici (F)

Department of Movement, Human and Health Sciences, University of Rome "Foro Italico", Rome, Italy.

R M Enoka (RM)

Department of Integrative Physiology, University of Colorado Boulder, CO, United States.

D Farina (D)

Department of Bioengineering, Imperial College London, SW7 2AZ London, UK. Electronic address: d.farina@imperial.ac.uk.

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Classifications MeSH