title: On the Methodological Implications of Extracting Muscle Synergies from Human Locomotion.
abstract: 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.
authors.affiliation: 1 Department of Training and Movement, Sciences Humboldt-Universität zu Berlin, 10115 Berlin, Germany.
authors.forename: Alessandro
authors.initials: A
authors.lastname: Santuz
authors.affiliation: 1 Department of Training and Movement, Sciences Humboldt-Universität zu Berlin, 10115 Berlin, Germany.
authors.forename: Antonis
authors.initials: A
authors.lastname: Ekizos
authors.affiliation: 1 Department of Training and Movement, Sciences Humboldt-Universität zu Berlin, 10115 Berlin, Germany.
authors.forename: Lars
authors.initials: L
authors.lastname: Janshen
authors.affiliation: 2 Research Institute for Sport and Exercise Sciences, Liverpool John Moores University, Liverpool, L3 3AF Great Britain, UK www.ljmu.ac.uk.
authors.forename: Vasilios
authors.initials: V
authors.lastname: Baltzopoulos
authors.affiliation: 3 Department of Training and Movement, Sciences Humboldt-Universität zu Berlin, 10115 Berlin, Germany www.hu-berlin.de.
authors.forename: Adamantios
authors.initials: A
authors.lastname: Arampatzis
mesh_terms: D000328:Adult; D000465:Algorithms; D001696:Biomechanical Phenomena; D004576:Electromyography; D019054:Evoked Potentials, Motor / Q000502:physiology*; D005260:Female; D006801:Humans; D008297:Male; D018482:Muscle, Skeletal / Q000502:physiology*; D016011:Normal Distribution; D012420:Running / Q000502:physiology*; D013997:Time Factors; D016138:Walking / Q000502:physiology*; D055815:Young Adult
keywords: Muscle synergies; locomotion; motor module; motor primitive; non-negative matrix factorization