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)


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
Number of pages4
Publication statusPublished - 2006
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


Other2006 SICE-ICASE International Joint Conference
Country/TerritoryKorea, Republic of


  • 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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