Lu Zhiyuan, Tong Kai-Yu, Shin Henry, Stampas Argyrios, Zhou Ping
From the Department of Physical Medicine and Rehabilitation, University of Texas Health Science Center, Houston, Texas (ZL, HS, AS, PZ); TIRR Memorial Hermann Research Center, Houston, Texas (ZL, HS, AS, PZ); Division of Biomedical Engineering, Department of Electronic Engineering, Chinese University of Hong Kong, Hong Kong, China (KT); and Guangdong Work Injury Rehabilitation Center, Guangzhou, China (PZ).
Am J Phys Med Rehabil. 2017 Oct;96(10 Suppl 1):S146-S149. doi: 10.1097/PHM.0000000000000798.
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.
一名51岁男性，26年前发生不完全性C6脊髓损伤，在10周内接受了20次、每次2小时的机器人辅助手部训练，该训练由肌电模式识别驱动。每次训练时，其右手由一个外骨骼机器人辅助进行运动，而机器人则由他自己的运动意图触发。手部机器人是为该研究设计的，可执行六种运动，包括手部闭合/张开；拇指、食指和中指闭合/张开；以及中指、无名指和小指闭合/张开。训练后，他的握力从13.5千克增加到19.6千克，捏力保持不变（5.0千克），箱块测试得分从32分提高到39分，力量、感觉和抓握能力分级重新评估测试第4.B部分的得分从22分提高到24分。他在力量、感觉和抓握能力分级重新评估测试第4.B部分完成任务的平均速度快了28.8%。结果证明了脊髓损伤后由肌电模式识别驱动的机器人辅助训练的可行性和有效性。
