Wang Jiajin, Zuo Guokun, Zhang Jiaji, Shi Changcheng, Song Tao, Guo Shuai
Department of Mechanical Automation Engineering, School of Mechatronic Engineering and Automation, Shanghai University, Shanghai 200444, P.R.China;Ningbo Institute of Materials Technology and Engineering, Chinese Academy of Science, Ningbo, Zhejiang 315201, P.R.China.
Ningbo Institute of Materials Technology and Engineering, Chinese Academy of Science, Ningbo, Zhejiang 315201, P.R.China.
Sheng Wu Yi Xue Gong Cheng Xue Za Zhi. 2020 Feb 25;37(1):129-135. doi: 10.7507/1001-5515.201902023.
In order to stimulate the patients' active participation in the process of robot-assisted rehabilitation training of stroke patients, the rehabilitation robots should provide assistant torque to patients according to their rehabilitation needs. This paper proposed an assist-as-needed control strategy for wrist rehabilitation robots. Firstly, the ability evaluation rules were formulated and the patient's ability was evaluated according to the rules. Then the controller was designed. Based on the evaluation results, the controller can calculate the assistant torque needed by the patient to complete the rehabilitation training task and send commands to motor. Finally, the motor is controlled to output the commanded value, which assists the patient to complete the rehabilitation training task. The control strategy was implemented to the wrist function rehabilitation robot, which could achieve the training effect of assist-as-needed and could avoid the surge of assistance torque. In addition, therapists can adjust multiple parameters in the ability evaluation rules online to customize the difficulty of tasks for patients with different rehabilitation status. The method proposed in this paper does not rely on the information from force sensor, which reduces development costs and is easy to implement.
为了激发患者积极参与中风患者的机器人辅助康复训练过程,康复机器人应根据患者的康复需求为其提供辅助扭矩。本文提出了一种用于手腕康复机器人的按需辅助控制策略。首先,制定能力评估规则,并根据规则对患者的能力进行评估。然后设计控制器。基于评估结果,控制器可以计算患者完成康复训练任务所需的辅助扭矩,并向电机发送命令。最后,控制电机输出指令值,以协助患者完成康复训练任务。该控制策略应用于手腕功能康复机器人,可实现按需辅助的训练效果,并可避免辅助扭矩的激增。此外,治疗师可以在线调整能力评估规则中的多个参数,为不同康复状态的患者定制任务难度。本文提出的方法不依赖于力传感器的信息,降低了开发成本且易于实现。