Advances in Mechanical Engineering (Mar 2015)

Robotic neurorehabilitation system design for stroke patients

  • Baoguo Xu,
  • Aiguo Song,
  • Guopu Zhao,
  • Guozheng Xu,
  • Lizheng Pan,
  • Renhuan Yang,
  • Huijun Li,
  • Jianwei Cui,
  • Hong Zeng

DOI
https://doi.org/10.1177/1687814015573768
Journal volume & issue
Vol. 7

Abstract

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In this article, a neurorehabilitation system combining robot-aided rehabilitation with motor imagery–based brain–computer interface is presented. Feature extraction and classification algorithm for the motor imagery electroencephalography is implemented under our brain–computer interface research platform. The main hardware platform for functional recovery therapy is the Barrett Whole-Arm Manipulator. The mental imagination of upper limb movements is translated to trigger the Barrett Whole-Arm Manipulator Arm to stretch the affected upper limb to move along the predefined trajectory. A fuzzy proportional–derivative position controller is proposed to control the Whole-Arm Manipulator Arm to perform passive rehabilitation training effectively. A preliminary experiment aimed at testing the proposed system and gaining insight into the potential of motor imagery electroencephalography-triggered robotic therapy is reported.