Pattern recognition of EMG signals by the evolutionary algorithms

Kentaro Tohi, Yasue Mitsukura, Yuki Yazama, Minoru Fukumi

Research output: Chapter in Book/Report/Conference proceedingConference contribution

4 Citations (Scopus)

Abstract

In this paper, we propose a method of function derivation for performing recognition of wrist operations by the Electromyographic (EMG) signals extracted from 4-channel EMG sensor. In designing a recognition device of operations, the important fewer amount of information is needed for reduction of cost and accuracy improvement in practical systems. Then, date mining is performed by specifying important frequency bands using genetic algorithm (GA) and neural network (NN). The derivation of function for generating a feature vector is performed only using the important frequency bands obtained by GA and NN. In this case, the feature vector which consists of frequency spectrum to be used is mapped to another space. We use the generated function as an input feature to perform recognition experiments of EMG signal by NN. Finally, the effectiveness of this method is demonstrated by means of computer simulations

Original languageEnglish
Title of host publication2006 SICE-ICASE International Joint Conference
Pages2574-2577
Number of pages4
DOIs
Publication statusPublished - 2006 Dec 1
Externally publishedYes
Event2006 SICE-ICASE International Joint Conference - Busan, Korea, Republic of
Duration: 2006 Oct 182006 Oct 21

Publication series

Name2006 SICE-ICASE International Joint Conference

Other

Other2006 SICE-ICASE International Joint Conference
CountryKorea, Republic of
CityBusan
Period06/10/1806/10/21

Keywords

  • Electromyographic
  • Feature vector
  • Genetic algorithm
  • Neural network

ASJC Scopus subject areas

  • Computer Science Applications
  • Control and Systems Engineering
  • Electrical and Electronic Engineering

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  • Cite this

    Tohi, K., Mitsukura, Y., Yazama, Y., & Fukumi, M. (2006). Pattern recognition of EMG signals by the evolutionary algorithms. In 2006 SICE-ICASE International Joint Conference (pp. 2574-2577). [4108078] (2006 SICE-ICASE International Joint Conference). https://doi.org/10.1109/SICE.2006.314791