Sequential recognition of EMG signals applied to the control of bioprosthetic hand: experimental comparative analysis of methods

Authors:
Marek Kurzynski;Andrzej Wolczowski
Affiliations:
Department of Systems and Computer Networks, Wroclaw University of Technology, Wroclaw, Poland;Department of Systems and Computer Networks, Wroclaw University of Technology, Wroclaw, Poland
Venue:
AIASABEBI'11 Proceedings of the 11th WSEAS international conference on Applied informatics and communications, and Proceedings of the 4th WSEAS International conference on Biomedical electronics and biomedical informatics, and Proceedings of the international conference on Computational engineering in systems applications
Year:
2011

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Abstract

The paper presents a concept of bio-prosthesis control via recognition of user intent on the basis of EMG signal analysis. The contextual (sequential) recognition is considered and the following methods of sequential classification are explored: Bayes approach with Markov model, multilayer perceptron, multiclassifier with competence function, classifier based on fuzzy logic and classifier based on Dempster-Shafer theory of evidence. The concept of measurement stand which was the source of information exploited in the experimental investigations of algorithms is described. An experimental comparative analysis of the proposed algorithms for real data is performed and results are discussed.