Robotic Hand–Assisted Training for Spinal Cord Injury Driven by Myoelectric Pattern Recognition

Abstract

A 51-year-old man with an incomplete C6 spinal cord injury sustained 26 yrs ago attended twenty 2-hr visits over 10 wks for robot-assisted hand training driven by myoelectric pattern recognition. In each visit, his right hand was assisted to perform motions by an exoskeleton robot, while the robot was triggered by his own motion intentions. The hand robot was designed for this study, which can perform six kinds of motions, including hand closing/opening; thumb, index finger, and middle finger closing/opening; and middle, ring, and little fingers closing/opening. After the training, his grip force increased from 13.5 to 19.6 kg, his pinch force remained the same (5.0 kg), his score of Box and Block test increased from 32 to 39, and his score from the Graded Redefined Assessment of Strength, Sensibility, and Prehension test Part 4.B increased from 22 to 24. He accomplished the tasks in the Graded Redefined Assessment of Strength, Sensibility, and Prehension test Part 4.B 28.8% faster on average. The results demonstrate the feasibility and effectiveness of robot-assisted training driven by myoelectric pattern recognition after spinal cord injury.