Shen Zhihang, Zhang Ling, Su Yuehong, Xing Hongwei, Li Bin
Information Center, Sun Yat-sen University Cancer Center, Guangzhou, 510060.
Modern Education Technology Center, Guangzhou Vocational College of Technology & Business, Guangzhou, 511442.
Zhongguo Yi Liao Qi Xie Za Zhi. 2024 Jul 30;48(4):385-391. doi: 10.12455/j.issn.1671-7104.230642.
The control strategy of rehabilitation robots should not only adapt to patients with different levels of motor function but also encourage patients to participate voluntarily in rehabilitation training. However, existing control strategies usually consider only one of these aspects. This study proposes a voluntary and adaptive control strategy that solves both questions. Firstly, the controller switched to the corresponding working modes (including challenge, free, assistant, and robot-dominant modes) based on the trajectory tracking error of human-robot cooperative movement. To encourage patient participation, a musculoskeletal model was used to estimate the patient's active torque. The robot's output torque was designed as the product of the active torque and a coefficient, with the coefficient adaptively changing according to the working mode. Experiments were conducted on two healthy subjects and four hemiplegic patients using an ankle rehabilitation robot. The results showed that this controller not only provided adaptive the robot's output torque based on the movement performance of patients but also encouraged patients to complete movement tasks themselves. Therefore, the control strategy has high application value in the field of rehabilitation.
康复机器人的控制策略不仅应适应不同运动功能水平的患者,还应鼓励患者自愿参与康复训练。然而,现有的控制策略通常只考虑其中一个方面。本研究提出了一种同时解决这两个问题的自愿自适应控制策略。首先,控制器根据人机协同运动的轨迹跟踪误差切换到相应的工作模式(包括挑战、自由、辅助和机器人主导模式)。为了鼓励患者参与,使用肌肉骨骼模型来估计患者的主动扭矩。机器人的输出扭矩设计为主动扭矩与一个系数的乘积,该系数根据工作模式自适应变化。使用脚踝康复机器人对两名健康受试者和四名偏瘫患者进行了实验。结果表明,该控制器不仅能根据患者的运动表现自适应地调整机器人的输出扭矩,还能鼓励患者自己完成运动任务。因此,该控制策略在康复领域具有较高的应用价值。