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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Vydané v:	IEEE transactions on human-machine systems Ročník 55; číslo 1; s. 58 - 70
Hlavní autori:	Kusuru, Durgesh, Turlapaty, Anish C., Thakur, Mainak
Médium:	Journal Article
Jazyk:	English
Vydavateľské údaje:	IEEE 01.02.2025
Predmet:	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
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