An Improved Compound Gaussian Model for Bivariate Surface EMG Signals Related to Strength Training

Recent literature suggests that the surface electromyography (sEMG) signals have nonstationary statistical characteristics, specifically due to the random nature of the covariance. Thus, the suitability of a statistical model for sEMG signals is determined by the choice of an appropriate model for d...

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Veröffentlicht in:	IEEE transactions on human-machine systems Jg. 55; H. 1; S. 58 - 70
Hauptverfasser:	Kusuru, Durgesh, Turlapaty, Anish C., Thakur, Mainak
Format:	Journal Article
Sprache:	Englisch
Veröffentlicht:	IEEE 01.02.2025
Schlagworte:	Adaptation models Compound Gaussian (CG) models Electromyography expectation maximization (EM) algorithm Expectation-maximization algorithms exponential random variable Force Gaussian processes Muscles Random variables surface electromyography (sEMG) Training
ISSN:	2168-2291, 2168-2305
Online-Zugang:	Volltext
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