AI Article Synopsis

  • This study introduces a method to analyze decomposed electromyographic signals for better understanding motor units (MUs).
  • It consists of two main steps: clustering MUs based on firing rates, recruitment thresholds, and action potential amplitude, followed by data segmentation at specific times.
  • The research investigates MUs during knee extension, revealing distinct differences in firing rates, clustered groups, and segmented MU data for different contraction types.

Article Abstract

This study proposes a method for analysing decomposed electromyographic signals to enhance the characterization of motor units (MU). It involves two steps: (i) clustering groups of motor units based on firing rate (FR), recruitment threshold, and MU action potential amplitude, and (ii) segmentation of data at the time of interest. Such method, capable of distinguishing different groups of MU, could help understanding muscle force production. FR of MU in and during knee extension was investigated. The findings distinguish MU groups and reveals differences in: FR between both contractions types; clustered groups; and segmented MU data in both contraction types.

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Source
http://dx.doi.org/10.1080/10255842.2024.2422900DOI Listing

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