Feature analysis for the EMG signals based on the class distance

Yuuki Yazama, Yasue Mitsukura, Minora Fukumi, Norio Akamatsu

研究成果: Conference contribution

14 被引用数 (Scopus)

抄録

In this paper, a feature vector is extracted from an elec-tromyography (EMG) signal at a wrist, and the EMG signals based on 7 motions are recognized. In order to perform good pattern recognition, it is desirable that the distance in feature vector between classes is far, and that the variance in a class is small. In consideration of these, important frequency bands of EMG signals are selected by using a genetic algorithm. We use the selected frequency band to perform the recognition experiment of EMG signal by a neural network. Finally, the effectiveness of this method is demonstrated by means of computer simulations.

本文言語English
ホスト出版物のタイトルProceedings - 2003 IEEE International Symposium on Computational Intelligence in Robotics and Automation
ホスト出版物のサブタイトルComputational Intelligence in Robotics and Automation for the New Millennium
出版社Institute of Electrical and Electronics Engineers Inc.
ページ860-863
ページ数4
ISBN(電子版)0780378660
DOI
出版ステータスPublished - 2003 1月 1
外部発表はい
イベント2003 IEEE International Symposium on Computational Intelligence in Robotics and Automation, CIRA 2003 - Kobe, Japan
継続期間: 2003 7月 162003 7月 20

出版物シリーズ

名前Proceedings of IEEE International Symposium on Computational Intelligence in Robotics and Automation, CIRA
2

Other

Other2003 IEEE International Symposium on Computational Intelligence in Robotics and Automation, CIRA 2003
国/地域Japan
CityKobe
Period03/7/1603/7/20

ASJC Scopus subject areas

  • 計算数学

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