Tutorial: Analysis of motor unit discharge characteristics from high-density surface EMG signals - Del Vecchio, Alessandro; Holobar, A.; Falla, D.; Felici, F.; Enoka, R. M.; Farina, D. (Journal of Electromyography and Kinesiology, 2020)
Recent work demonstrated that it is possible to identify motor unit discharge times from high-density surface EMG (HDEMG) decomposition. Since then, the number of studies that use HDEMG decomposition for motor unit investigations has increased considerably. Although HDEMG decomposition is a semi-automatic process, the analysis and interpretation of the motor unit pulse trains requires a thorough inspection of the output of the decomposition result. Here, we report guidelines to perform an accurate extraction of motor unit discharge times and interpretation of the signals. This tutorial includes a discussion of the differences between the extraction of global EMG signal features versus the identification of motor unit activity for physiological investigations followed by a comprehensive guide on how to acquire, inspect, and decompose HDEMG signals, and robust extraction of motor unit discharge characteristics.
CRIS-Team Scopus Importer:2020-10-12
Keywords: Blind source separation; Decomposition; Motor units; Neural drive