Non-negative matrix factorisation is the most appropriate method for extraction of muscle synergies in walking and running

Muscle synergies provide a simple description of a complex motor control mechanism. Synergies are extracted from muscle activation patterns using factorisation methods. Despite the availability of several factorisation methods in the literature, the most appropriate method for muscle synergy extract...

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Published inScientific reports Vol. 10; no. 1; p. 8266
Main Authors Rabbi, Mohammad Fazle, Pizzolato, Claudio, Lloyd, David G., Carty, Chris P., Devaprakash, Daniel, Diamond, Laura E.
Format Journal Article
LanguageEnglish
Published London Nature Publishing Group UK 19.05.2020
Nature Publishing Group
Subjects
631/378/116
639/166/985
Adult
Factor analysis
Factor Analysis, Statistical
Humanities and Social Sciences
Humans
Male
Methods
Motor task performance
multidisciplinary
Muscle Contraction
Muscle, Skeletal - physiology
Principal components analysis
Probability distribution
Running
Science
Science (multidisciplinary)
Walking
Young Adult
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ISSN2045-2322
2045-2322
DOI10.1038/s41598-020-65257-w

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Summary:Muscle synergies provide a simple description of a complex motor control mechanism. Synergies are extracted from muscle activation patterns using factorisation methods. Despite the availability of several factorisation methods in the literature, the most appropriate method for muscle synergy extraction is currently unknown. In this study, we compared four muscle synergy extraction methods: non-negative matrix factorisation, principal component analysis, independent component analysis, and factor analysis. Probability distribution of muscle activation patterns were compared with the probability distribution of synergy excitation primitives obtained from the four factorisation methods. Muscle synergies extracted using non-negative matrix factorisation best matched the probability distribution of muscle activation patterns across different walking and running speeds. Non-negative matrix factorisation also best tracked changes in muscle activation patterns compared to the other factorisation methods. Our results suggest that non-negative matrix factorisation is the best factorisation method for identifying muscle synergies in dynamic tasks with different levels of muscle contraction.
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ISSN:2045-2322
2045-2322
DOI:10.1038/s41598-020-65257-w