論文

査読有り 筆頭著者
2016年9月

An EMG-Driven Weight Support System With Pneumatic Artificial Muscles

IEEE SYSTEMS JOURNAL
  • Jun-ichiro Furukawa
  • ,
  • Tomoyuki Noda
  • ,
  • Tatsuya Teramae
  • ,
  • Jun Morimoto

10
3
開始ページ
1026
終了ページ
1034
記述言語
英語
掲載種別
研究論文(学術雑誌)
DOI
10.1109/JSYST.2014.2330376
出版者・発行元
IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC

In this paper, we introduce our newly developed biosignal-based vertical weight support system that is composed of pneumatic artificial muscles (PAMs) and an electromyography (EMG) measurement device. By using our developed weight support system, assist force can be varied based on measured muscle activities; most existing systems can only generate constant assist forces. In this paper, we estimated knee and ankle joint torques from measured EMGs using floating base inverse dynamics. Knee and ankle joint estimated torques are converted to vertical forces by the kinematic model of a subject. The converted vertical forces are used as force inputs for the PAM actuator system. To validate our system's control performance, four healthy subjects performed a one-leg squat with his left leg while his right leg was assisted by our proposed system. We used the vertical force estimated from the measured EMG signals as a control input to the weight support system. We compared EMG magnitudes with four different experimental conditions: 1) normal two-leg squat; 2) one-leg squat without the assist system; 3) one-leg squat with EMG-based weight support; and 4) one-leg squat with constant force support. The EMG magnitude with the proposed weight support system was much closer to that with normal two-leg squat than that with one-leg squat without the assist system and than that with one-leg squat with constant force support.

リンク情報
DOI
https://doi.org/10.1109/JSYST.2014.2330376
Web of Science
https://gateway.webofknowledge.com/gateway/Gateway.cgi?GWVersion=2&SrcAuth=JSTA_CEL&SrcApp=J_Gate_JST&DestLinkType=FullRecord&KeyUT=WOS:000383260300017&DestApp=WOS_CPL
ID情報
  • DOI : 10.1109/JSYST.2014.2330376
  • ISSN : 1932-8184
  • eISSN : 1937-9234
  • Web of Science ID : WOS:000383260300017

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