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Study on exoskeletal rehabilitation robot for upper limb and its control method

  • Dong Yan Wang*
  • , Qing Ling Li
  • , Zhi Jiang Du
  • , Li Ning Sun
  • *Corresponding author for this work
  • Harbin Institute of Technology
  • Heilongjiang University of Traditional Chinese Medicine

Research output: Contribution to journalArticlepeer-review

Abstract

A 5-DOF exoskeletal rehabilitation robot, which can implement single joint and multi-joint complex motions and provide ADL training for hemiplegic patients, is presented. In general, hemiplegic patients are unilaterally impaired, so the surface electromyogram (sEMG) signal in the healthy limbs can be extracted to drive the rehabilitation robot to assist patients' impaired limb to carry out rehabilitation exercises. Herein two methods were involved: IAV and AR were used to extract features of sEMG acquired from four upper limb muscles which contribute to focused activities of that upper limb. The extracted features were used as the input to a back propagation neural network (BPN) in the Levenberg-Marquardt (LM) algorithm, then a relationship was formulated between sMEG and the rehablilitation motion with six upper limb rehabilitation exercise motions as outputs. Experiments prove the effectiveness of this method, which is useful for patient to train the nervous system, improve blood circulation and keep a sense of proper motion and improve range of motion.

Original languageEnglish
Pages (from-to)1008-1013
Number of pages6
JournalHarbin Gongcheng Daxue Xuebao/Journal of Harbin Engineering University
Volume28
Issue number9
StatePublished - Sep 2007

Keywords

  • Back propagation neural network
  • Exoskeletal rehabilitation robot
  • Levenberg Marquardt algorithm
  • Levenberg Marquardt parameter model
  • Surface electromyogram

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