Dual predictive control of electrically stimulated muscle using biofeedback for drop foot correction

Mitsuhiro Hayashibe, Qin Zhang, Christine Azevedo-Coste

研究成果: Conference contribution

13 被引用数 (Scopus)

抄録

Electrical stimulation (ES) is one of the solutions for drop foot correction. Conventional ES systems deliver predefined stimulation pattern to the affected muscles. However, time-variant muscle response may influence the gait performance as they are difficult to be taken into account in advance. Therefore, closed-loop ES control is important to obtain desired gait in presence of muscle response variation. In this work, a dual predictive control, which consists of two nonlinear generalized predictive controllers, is proposed to track desired torque. The stimulated muscle dynamics are modeled by Hammerstein cascades, with one representing stimulation to activation, the other representing activation to torque. Ankle dorsiflexion torque and ES-evoked EMG of tibialis anterior were recorded experimentally for model identification. The control scheme is validated by following desired torque trajectories with the identified model. The results show that the stimulation pattern obtained from the dual predictive control can produce good torque tracking according to the current muscle condition.

本文言語English
ホスト出版物のタイトルIROS'11 - 2011 IEEE/RSJ International Conference on Intelligent Robots and Systems
ホスト出版物のサブタイトルCelebrating 50 Years of Robotics
ページ1731-1736
ページ数6
DOI
出版ステータスPublished - 2011
外部発表はい
イベント2011 IEEE/RSJ International Conference on Intelligent Robots and Systems: Celebrating 50 Years of Robotics, IROS'11 - San Francisco, CA, United States
継続期間: 2011 9 252011 9 30

出版物シリーズ

名前IEEE International Conference on Intelligent Robots and Systems

Other

Other2011 IEEE/RSJ International Conference on Intelligent Robots and Systems: Celebrating 50 Years of Robotics, IROS'11
国/地域United States
CitySan Francisco, CA
Period11/9/2511/9/30

ASJC Scopus subject areas

  • 制御およびシステム工学
  • ソフトウェア
  • コンピュータ ビジョンおよびパターン認識
  • コンピュータ サイエンスの応用

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