Estimation of user's hand motion based on EMG and EEG signals

Kazuo Kiguchi, Kaori Tamura, Yoshiaki Hayashi

研究成果: 書籍/レポート タイプへの寄稿会議への寄与

2 被引用数 (Scopus)

抄録

A surface EMG signal is one of the most widely used signals as input signals to wearable robots. However, EMG signals that are used to estimate motions are not always available to all users. On the other hand, an EEG signal has drawn attention as input signals for those robots in recent years. The EEG signals can be measured even with amputees and paralyzed patients who are not able to generate some EMG signals. However, the measured EEG signal does not have one-to-one relationships with the corresponding brain part. Therefore, it is more difficult to find the required signals for the control of the robot in accordance with the intention of the user's motion using the EEG signals compared with that using the EMG signals. In this paper, both the EMG and EEG signals are used to estimate the user's motion intention. In the proposed method, the EMG signals are used as main input signals because the EMG signals have higher relative to the motion of a user in comparison with the EEG signals. The EEG signals are used as sub signals in order to cover the estimation of the intention of the user's motion when all required EMG signals cannot be measured. The effectiveness of the proposed method has been evaluated by performing experiments.

本文言語英語
ホスト出版物のタイトルWorld Automation Congress Proceedings
出版社IEEE Computer Society
ページ713-717
ページ数5
ISBN(電子版)9781889335490
DOI
出版ステータス出版済み - 10月 24 2014
イベント2014 World Automation Congress, WAC 2014 - Waikoloa, 米国
継続期間: 8月 3 20148月 7 2014

出版物シリーズ

名前World Automation Congress Proceedings
ISSN(印刷版)2154-4824
ISSN(電子版)2154-4832

その他

その他2014 World Automation Congress, WAC 2014
国/地域米国
CityWaikoloa
Period8/3/148/7/14

!!!All Science Journal Classification (ASJC) codes

  • 制御およびシステム工学

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