DocumentCode :
3761849
Title :
Upper-limb movement classification through logistic regression sEMG signal processing
Author :
Vinicius Horn Cene;Alexandre Balbinot
Author_Institution :
Department of Electric Engineering, Federal University of Rio Grande do Sul (UFRGS), Porto Alegre, Brazil
fYear :
2015
Firstpage :
1
Lastpage :
5
Abstract :
Several computational intelligence algorithms have been used to classify biological signals of stochastic nature. This paper aims to evaluate the application of logistic regression technique for the classification of electromyography signals originated from hand-arm segment. Therefore, the algorithm was implemented using multinomial logistic regression and an optimization heuristic based on gradient descent. Classification tests were performed with three subjects and an accuracy rate of 90.2 ± 3.8% was achieved.
Keywords :
"Mathematical model","Electromyography","Classification algorithms","Signal processing algorithms","Logistics","Optimization","Wrist"
Publisher :
ieee
Conference_Titel :
Computational Intelligence (LA-CCI), 2015 Latin America Congress on
Type :
conf
DOI :
10.1109/LA-CCI.2015.7435940
Filename :
7435940
Link To Document :
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