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Author:

Li, J. (Li, J..) | Zhou, Y. (Zhou, Y..) | Dong, M. (Dong, M..) | Rong, X. (Rong, X..)

Indexed by:

EI Scopus SCIE

Abstract:

Isokinetic muscle strength training refers to the mode of movement based on constant speed and variable resistance, which can guarantee the maximum resistance and force-distance output of each muscle in different angles of exercise. In this paper, we develop an isokinetic muscle strength training strategy based on adaptive gain and cascade PID controller for ankle rehabilitation on our newly developed ankle robotic system. At first, a heuristic threshold intention recognition method based on time series integrated was proposed to precisely recognize the motion intention, thus inducing the motion in this direction. Then, an adaptive gain algorithm was developed to provide speed gain for the isokinetic training, to avoid jitter during speed switching. At last, the isokinetic characteristic was realized by cascade PID controller, which can control the motion velocity in a given range with fast response speed. Experiments with healthy subjects showed good performance in the smoothness of the control system, the accuracy, and the real-time performance of velocity tracking. By introducing the isokinetic characteristic in ankle rehabilitation, the ankle robot can provide resistance training at a constant speed no matter how much force the patient uses, which is a very functional supplement and improvement for ankle rehabilitation. IEEE

Keyword:

Torque measurement Ankle rehabilitation robot Immune system Muscles Torque cascade PID controller. adaptive gain Training Rehabilitation robotics Servomotors motion intention recognition

Author Community:

  • [ 1 ] [Li J.]Beijing Key Laboratory of Advanced Manufacturing Technology, Faculty of Materials and Manufacturing, Beijing University of Technology, Beijing, 100124, P.R. China.
  • [ 2 ] [Zhou Y.]Beijing Key Laboratory of Advanced Manufacturing Technology, Faculty of Materials and Manufacturing, Beijing University of Technology, Beijing, 100124, P.R. China.
  • [ 3 ] [Dong M.]Beijing Key Laboratory of Advanced Manufacturing Technology, Faculty of Materials and Manufacturing, Beijing University of Technology, Beijing, 100124, P.R. China.
  • [ 4 ] [Dong M.]Beijing Key Laboratory of Advanced Manufacturing Technology, Faculty of Materials and Manufacturing, Beijing University of Technology, Beijing, 100124, P.R. China. (e-mail: dongmj@bjut.edu.cn)
  • [ 5 ] [Rong X.]Hospital of Qingdao University, Qingdao, 266000, P.R. China.

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Source :

IEEE Transactions on Cognitive and Developmental Systems

ISSN: 2379-8920

Year: 2022

Issue: 1

Volume: 15

Page: 100-110

Cited Count:

WoS CC Cited Count: 0

SCOPUS Cited Count: 14

ESI Highly Cited Papers on the List: 0 Unfold All

WanFang Cited Count:

Chinese Cited Count:

30 Days PV: 17

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