Back to Search Start Over

Identifying Motor Units in Longitudinal Studies with High-Density Surface Electromyography

Authors :
Francesco Negro
Eduardo Martinez-Valdes
Dario Farina
Deborah Falla
Christopher M. Laine
Frank Mayer
Source :
Biosystems & Biorobotics ISBN: 9783319466682
Publication Year :
2016
Publisher :
Springer International Publishing, 2016.

Abstract

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 following interventions or during the progression of neuromuscular disorders.

Details

ISBN :
978-3-319-46668-2
ISBNs :
9783319466682
Database :
OpenAIRE
Journal :
Biosystems & Biorobotics ISBN: 9783319466682
Accession number :
edsair.doi.dedup.....901e50c1f923b40d996ab4293f5f4b8d
Full Text :
https://doi.org/10.1007/978-3-319-46669-9_27