Recognition system for EMG signals by using non-negative matrix factorization

Author

Yazama, Yuuki ; Mitsukura, Yasue ; Fukumi, Minoru ; Akamatsu, Norio

Author_Institution

Dept. of Inf. Sci. & Intelligent Syst., Tokushima Univ., Japan

Volume

3

fYear

2003

fDate

20-24 July 2003

Firstpage

2130

Abstract

IN this paper, the feature vector of a few dimensions for the electromyograph (EMG) recognition systems is extracted. We aim at the construction of the comprehensive operation equipment to which the operation used frequently was summarized. Important frequency bands of EMG signals are selected by using a genetic algorithm. The EMG signals are a kind of the living organism signal. The EMG signals based on 7 operations at a wrist are measured and recognized. We perform a recognition experiment of EMG signals by neural network using the selected frequency band. We show the effectiveness of this method by means of computer simulations.

Keywords

backpropagation; electromyography; genetic algorithms; matrix decomposition; medical signal detection; neural nets; pattern recognition; EMG; backpropagation; comprehensive operation equipment; computer simulation; data mining; electromyograph recognition systems; electromyograph signals; feature vector; frequency band selection; genetic algorithm; living organism signal; neural network; nonnegative matrix factorization; Electrodes; Electromyography; Frequency; Genetic algorithms; Information science; Intelligent systems; Neural networks; Personal digital assistants; Systems engineering and theory; Wrist;

fLanguage

English

Publisher

ieee

Conference_Titel

Neural Networks, 2003. Proceedings of the International Joint Conference on

ISSN

1098-7576

Print_ISBN

0-7803-7898-9

Type

conf

DOI

10.1109/IJCNN.2003.1223737

Filename

1223737