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A robotic system with reinforcement learning for lower extremity hemiparesis rehabilitation
Industrial Robot ( IF 1.8 ) Pub Date : 2021-02-08 , DOI: 10.1108/ir-10-2020-0230
Jiajun Xu , Linsen Xu , Gaoxin Cheng , Jia Shi , Jinfu Liu , Xingcan Liang , Shengyao Fan

Purpose

This paper aims to propose a bilateral robotic system for lower extremity hemiparesis rehabilitation. The hemiplegic patients can complete rehabilitation exercise voluntarily with the assistance of the robot. The reinforcement learning is included in the robot control system, enhancing the muscle activation of the impaired limbs (ILs) efficiently with ensuring the patients’ safety.

Design/methodology/approach

A bilateral leader–follower robotic system is constructed for lower extremity hemiparesis rehabilitation, where the leader robot interacts with the healthy limb (HL) and the follow robot is worn by the IL. The therapeutic training is transferred from the HL to the IL with the assistance of the robot, and the IL follows the motion trajectory prescribed by the HL, which is called the mirror therapy. The model reference adaptive impedance control is used for the leader robot, and the reinforcement learning controller is designed for the follower robot. The reinforcement learning aims to increase the muscle activation of the IL and ensure that its motion can be mastered by the HL for safety. An asynchronous algorithm is designed by improving experience relay to run in parallel on multiple robotic platforms to reduce learning time.

Findings

Through clinical tests, the lower extremity hemiplegic patients can rehabilitate with high efficiency using the robotic system. Also, the proposed scheme outperforms other state-of-the-art methods in tracking performance, muscle activation, learning efficiency and rehabilitation efficacy.

Originality/value

Using the aimed robotic system, the lower extremity hemiplegic patients with different movement abilities can obtain better rehabilitation efficacy.



中文翻译:

一种用于下肢偏瘫康复的强化学习机器人系统

目的

本文旨在提出一种用于下肢偏瘫康复的双边机器人系统。偏瘫患者可以在机器人的协助下自主完成康复锻炼。机器人控制系统中包含强化学习,有效增强受损肢体(IL)的肌肉激活,同时确保患者的安全。

设计/方法/方法

为下肢偏瘫康复构建了双侧领导-跟随机器人系统,其中领导机器人与健康肢体 (HL) 交互,跟随机器人由 IL 佩戴。治疗训练在机器人的协助下从HL转移到IL,IL遵循HL规定的运动轨迹,称为镜像治疗。领导机器人采用模型参考自适应阻抗控制,跟随机器人设计强化学习控制器。强化学习旨在增加 IL 的肌肉激活,并确保 HL 可以安全地控制其运动。通过改进经验中继设计异步算法以在多个机器人平台上并行运行以减少学习时间。

发现

通过临床试验,下肢偏瘫患者可以使用机器人系统高效康复。此外,所提出的方案在跟踪性能、肌肉激活、学习效率和康复功效方面优于其他最先进的方法。

原创性/价值

使用有针对性的机器人系统,不同运动能力的下肢偏瘫患者可以获得更好的康复效果。

更新日期:2021-02-08
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