How Many Muscles? Optimal Muscles Set Search for Optimizing Myocontrol Performance.

EMG electrodes muscles myocontrol optimization rehabilitation robotics synergies

Journal

Frontiers in computational neuroscience
ISSN: 1662-5188
Titre abrégé: Front Comput Neurosci
Pays: Switzerland
ID NLM: 101477956

Informations de publication

Date de publication:
2021
Historique:
received: 16 02 2021
accepted: 06 09 2021
entrez: 25 10 2021
pubmed: 26 10 2021
medline: 26 10 2021
Statut: epublish

Résumé

In myo-control, for computational and setup constraints, the measurement of a high number of muscles is not always possible: the choice of the muscle set to use in a myo-control strategy depends on the desired application scope and a search for a reduced muscle set, tailored to the application, has never been performed. The identification of such set would involve finding the minimum set of muscles whose difference in terms of intention detection performance is not statistically significant when compared to the original set. Also, given the intrinsic sensitivity of muscle synergies to variations of EMG signals matrix, the reduced set should not alter synergies that come from the initial input, since they provide physiological information on motor coordination. The advantages of such reduced set, in a rehabilitation context, would be the reduction of the inputs processing time, the reduction of the setup bulk and a higher sensitivity to synergy changes after training, which can eventually lead to modifications of the ongoing therapy. In this work, the existence of a minimum muscle set, called optimal set, for an upper-limb myoelectric application, that preserves performance of motor activity prediction and the physiological meaning of synergies, has been investigated. Analyzing isometric contractions during planar reaching tasks, two types of optimal muscle sets were examined: a subject-specific one and a global one. The former relies on the subject-specific movement strategy, the latter is composed by the most recurrent muscles among subjects specific optimal sets and shared by all the subjects. Results confirmed that the muscle set can be reduced to achieve comparable hand force estimation performances. Moreover, two types of muscle synergies namely "

Identifiants

pubmed: 34690729
doi: 10.3389/fncom.2021.668579
pmc: PMC8529110
doi:

Types de publication

Journal Article

Langues

eng

Pagination

668579

Informations de copyright

Copyright © 2021 Camardella, Junata, Tse, Frisoli and Tong.

Déclaration de conflit d'intérêts

The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.

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Auteurs

Cristian Camardella (C)

Perceptual Robotics (PERCRO) Laboratory, TECIP Institute, Scuola Superiore Sant'Anna, Pisa, Italy.

Melisa Junata (M)

Biomedical Engineering (BME) Laboratory, Department of Biomedical Engineering, The Chinese University of Hong Kong, Hong Kong, Hong Kong, SAR China.

King Chun Tse (KC)

Biomedical Engineering (BME) Laboratory, Department of Biomedical Engineering, The Chinese University of Hong Kong, Hong Kong, Hong Kong, SAR China.

Antonio Frisoli (A)

Perceptual Robotics (PERCRO) Laboratory, TECIP Institute, Scuola Superiore Sant'Anna, Pisa, Italy.

Raymond Kai-Yu Tong (RK)

Biomedical Engineering (BME) Laboratory, Department of Biomedical Engineering, The Chinese University of Hong Kong, Hong Kong, Hong Kong, SAR China.

Classifications MeSH