Recognition System for EMG Signals by using Non-negative Matrix Factorization

Yuuki Yazama, Yasue Mitsukura, Minoru Fukumi, Norio Akamatsu

Research output: Contribution to conferencePaper

1 Citation (Scopus)

Abstract

IIn this paper, the feature vector of a few dimension 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.

Original languageEnglish
Pages2130-2133
Number of pages4
Publication statusPublished - 2003 Sep 24
Externally publishedYes
EventInternational Joint Conference on Neural Networks 2003 - Portland, OR, United States
Duration: 2003 Jul 202003 Jul 24

Other

OtherInternational Joint Conference on Neural Networks 2003
CountryUnited States
CityPortland, OR
Period03/7/2003/7/24

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ASJC Scopus subject areas

  • Software
  • Artificial Intelligence

Cite this

Yazama, Y., Mitsukura, Y., Fukumi, M., & Akamatsu, N. (2003). Recognition System for EMG Signals by using Non-negative Matrix Factorization. 2130-2133. Paper presented at International Joint Conference on Neural Networks 2003, Portland, OR, United States.