IEEE Trans Biomed Circuits Syst. 2021 Dec;15(6):1332-1342. doi: 10.1109/TBCAS.2021.3130090. Epub 2022 Feb 17.
Reach-and-grasp is one of the most fundamental activities in daily life, while few rehabilitation robots provide integrated and active training of the arm and hand for patients after stroke to improve their mobility. In this study, a novel hybrid arm-hand rehabilitation robot (HAHRR) was built for the reach-and-grasp task. This hybrid structure consisted of a cable-driven module for three-dimensional arm motion and an exoskeleton for hand motion, which enabled assistance of the arm and hand simultaneously. To implement active compliance control, an EMG-based admittance controller was applied to the HAHRR. Experimental results showed that the HAHRR with the EMG-based admittance controller could not only assist the subject in fulfilling the reach-and-grasp task, but also generate smoother trajectories compared with the force-sensing-based admittance controller. These findings also suggested that the proposed approach might be applicable to post-stroke arm-hand rehabilitation training.
伸手抓握是日常生活中最基本的活动之一，而很少有康复机器人为中风后患者提供手臂和手部的综合主动训练，以提高他们的活动能力。在这项研究中，构建了一种新型的混合手臂-手部康复机器人（HAHRR），用于伸手抓握任务。这种混合结构由用于三维手臂运动的绳索驱动模块和用于手部运动的外骨骼组成，能够同时辅助手臂和手部。为了实现主动顺应性控制，将基于肌电的导纳控制器应用于 HAHRR。实验结果表明，带有基于肌电的导纳控制器的 HAHRR 不仅可以帮助受试者完成伸手抓握任务，而且与基于力感测的导纳控制器相比，还可以生成更平滑的轨迹。这些发现还表明，所提出的方法可能适用于中风后手臂-手部康复训练。
