On the Methodological Implications of Extracting Muscle Synergies from Human Locomotion

We investigated the influence of three different high-pass (HP) and low-pass (LP) filtering conditions and a Gaussian (GNMF) and inverse-Gaussian (IGNMF) non-negative matrix factorization algorithm on the extraction of muscle synergies from myoelectric signals during human walking and running. To ev...

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Vydáno v:International journal of neural systems Ročník 27; číslo 5; s. 1750007
Hlavní autoři: Santuz, Alessandro, Ekizos, Antonis, Janshen, Lars, Baltzopoulos, Vasilios, Arampatzis, Adamantios
Médium: Journal Article
Jazyk:angličtina
Vydáno: Singapore 01.08.2017
Témata:
Adult
Algorithms
Biomechanical Phenomena
Electromyography
Evoked Potentials, Motor - physiology
Female
Humans
Male
Muscle, Skeletal - physiology
Normal Distribution
Running - physiology
Time Factors
Walking - physiology
Young Adult
motor primitive
non-negative matrix factorization
Muscle synergies
motor module
locomotion
ISSN:0129-0657, 1793-6462, 1793-6462
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Shrnutí:We investigated the influence of three different high-pass (HP) and low-pass (LP) filtering conditions and a Gaussian (GNMF) and inverse-Gaussian (IGNMF) non-negative matrix factorization algorithm on the extraction of muscle synergies from myoelectric signals during human walking and running. To evaluate the effects of signal recording and processing on the outcomes, we analyzed the intraday and interday computation reliability. Results show that the IGNMF achieved a significantly higher reconstruction quality and on average needs one less synergy to sufficiently reconstruct the original signals compared to the GNMF. For both factorizations, the HP with a cut-off frequency of 250[Formula: see text]Hz significantly reduces the number of synergies. We identified the filter configuration of fourth order, HP 50[Formula: see text]Hz and LP 20[Formula: see text]Hz as the most suitable to minimize the combination of fundamental synergies, providing a higher reliability across all filtering conditions even if HP 250[Formula: see text]Hz is excluded. Defining a fundamental synergy as a single-peaked activation pattern, for walking and running we identified five and six fundamental synergies, respectively using both algorithms. The variability in combined synergies produced by different filtering conditions and factorization methods on the same data set suggests caution when attributing a neurophysiological nature to the combined synergies.
Bibliografie:ObjectType-Article-1
SourceType-Scholarly Journals-1
ObjectType-Feature-2
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ISSN:0129-0657
1793-6462
1793-6462
DOI:10.1142/S0129065717500071