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Clinical experimental research on adaptive robot-aided therapy control methods for upper-limb rehabilitation

Published online by Cambridge University Press:  15 January 2014

Guozheng Xu,
Aiguo Song,
Lizheng Pan,
Xiang Gao,
Zhiwei Liang,
Jinfei Li and
Baoguo Xu
Guozheng Xu*
Affiliation:
College of Automation, Nanjing University of Posts and Telecommunications, Nanjing 210046, P. R. China
Aiguo Song
Affiliation:
School of Instrument Science and Engineering, Southeast University, Nanjing 210096, P. R. China
Lizheng Pan
Affiliation:
School of Instrument Science and Engineering, Southeast University, Nanjing 210096, P. R. China
Xiang Gao
Affiliation:
College of Automation, Nanjing University of Posts and Telecommunications, Nanjing 210046, P. R. China
Zhiwei Liang
Affiliation:
College of Automation, Nanjing University of Posts and Telecommunications, Nanjing 210046, P. R. China
Jinfei Li
Affiliation:
Department of Rehabilitation Medicine of Nanjing Tongren Hospital, Nanjing 211102, P. R. China
Baoguo Xu
Affiliation:
School of Instrument Science and Engineering, Southeast University, Nanjing 210096, P. R. China
*
*Corresponding author. E-mail: xgznjupt@gmail.com
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Summary

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This study presents novel robotic therapy control algorithms for upper-limb rehabilitation, using newly developed passive and progressive resistance therapy modes. A fuzzy-logic based proportional-integral-derivative (PID) position control strategy, integrating a patient's biomechanical feedback into the control loop, is proposed for passive movements. This allows the robot to smoothly stretch the impaired limb through increasingly rigorous training trajectories. A fuzzy adaptive impedance force controller is addressed in the progressive resistance muscle strength training and the adaptive resistive force is generated according to the impaired limb's muscle strength recovery level, characterized by the online estimated impaired limb's bio-damping and bio-stiffness. The proposed methods are verified with a custom constructed therapeutic robot system featuring a Barrett WAM™ compliant manipulator. Twenty-four recruited stroke subjects were randomly allocated in experimental and control groups and enrolled in a 20-week rehabilitation training program. Preliminary results show that the proposed therapy control strategies can not only improve the impaired limb's joint range of motion but also enhance its muscle strength.

Keywords

Rehabilitation robotClinical experimentFuzzy logicPosition controlImpedance control

Information

Type
Articles
Information
Robotica , Volume 32 , Issue 7 , October 2014, pp. 1081 - 1100
Copyright
Copyright © Cambridge University Press 2014 

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