Tutorial: Analysis of motor unit discharge characteristics from high-density surface EMG signals.
Blind source separation
Decomposition
Motor units
Neural drive
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
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
102426Informations de copyright
Copyright © 2020 Elsevier Ltd. All rights reserved.