科研之友
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摘要
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.
