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Identifying motor units in longitudinal studies with high-density surface electromyography

  • We investigated the possibility to identify motor units (MUs) with high-density surface electromyography (HDEMG) over experimental sessions in different days. 10 subjects performed submaximal knee extensions across three sessions in three days separated by one week, while EMG was recorded from the vastus medialis muscle with high-density electrode grids. The shapes of the MU action potentials (MUAPs) over multiple channels extracted from HDEMG decomposition were matched across sessions by cross-correlation. Forty and twenty percent of the MUs decomposed could be tracked across two and three sessions, respectively (average cross correlation 0.85 +/- 0.04). The estimated properties of the matched motor units were similar across the sessions. For example, mean discharge rate and recruitment thresholds were measured with an intra-class correlation coefficient (ICCs) > 0.80. These results strongly suggest that the same MUs were indeed identified across sessions. This possibility will allow monitoring changes in MU properties followingWe investigated the possibility to identify motor units (MUs) with high-density surface electromyography (HDEMG) over experimental sessions in different days. 10 subjects performed submaximal knee extensions across three sessions in three days separated by one week, while EMG was recorded from the vastus medialis muscle with high-density electrode grids. The shapes of the MU action potentials (MUAPs) over multiple channels extracted from HDEMG decomposition were matched across sessions by cross-correlation. Forty and twenty percent of the MUs decomposed could be tracked across two and three sessions, respectively (average cross correlation 0.85 +/- 0.04). The estimated properties of the matched motor units were similar across the sessions. For example, mean discharge rate and recruitment thresholds were measured with an intra-class correlation coefficient (ICCs) > 0.80. These results strongly suggest that the same MUs were indeed identified across sessions. This possibility will allow monitoring changes in MU properties following interventions or during the progression of neuromuscular disorders.show moreshow less

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Author details:Eduardo Martinez-ValdesORCiDGND, Francesco Negro, Christopher M. Laine, Deborah L. Falla, Frank MayerORCiDGND, Dario Farina
DOI:https://doi.org/10.1007/978-3-319-46669-9_27
ISBN:978-3-319-46669-9
ISBN:978-3-319-46668-2
ISSN:2195-3562
Title of parent work (English):Converging clinical and engineering research on neurorehabilitation II
Publisher:Springer
Place of publishing:Cham
Publication type:Other
Language:English
Date of first publication:2016/06/13
Publication year:2016
Release date:2022/09/26
Volume:15
Number of pages:5
First page:147
Last Page:151
Organizational units:Humanwissenschaftliche Fakultät / Strukturbereich Kognitionswissenschaften / Department Sport- und Gesundheitswissenschaften
DDC classification:6 Technik, Medizin, angewandte Wissenschaften / 61 Medizin und Gesundheit / 610 Medizin und Gesundheit
Peer review:Referiert
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