Cooperative Control of An Ankle Rehabilitation Robot Based on Human Intention

Qingsong Ai, Lei Wang, Kun Chen, Anqi Chen, Jiwei Hu, Yilin Fang, Quan Liu, Zude Zhou
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引用次数: 1

Abstract

Motor imagery electroencephalogram (EEG) is a kind of brain signal induced by subjective consciousness. Relevant studies in the field of sports rehabilitation show that motor imagery training can promote the recovery of damaged nerves and the reconstruction of motor nerve pathways. This paper proposes a human-brain cooperative control strategy of a pneumatic muscle-driven ankle rehabilitation robot based on motor imagery EEG. Robots provide assisted rehabilitation training for patients with impaired neural transmission but with movement intentions. The brain network algorithm is used to select the optimal channels for the motor imagery signal, and the common spatial pattern (CSP) method is combined with the time-frequency analysis method local characteristic-scale decomposition (LCD) to extract the time-frequency information. Finally, the classification is processed by the spectral regression discriminant analysis (SRDA) classifier. In addition, two rehabilitation training modes are designed, namely, synchronous rehabilitation training and asynchronous rehabilitation training. The experimental results prove that a brain intention driven human robot cooperative control method is realized to complete an ankle rehabilitation training task effectively.
基于人意向的踝关节康复机器人协同控制
运动意象脑电图(EEG)是一种由主观意识诱发的脑信号。运动康复领域的相关研究表明,运动意象训练可以促进受损神经的恢复和运动神经通路的重建。提出了一种基于运动图像脑电的气动肌肉驱动踝关节康复机器人的人机协同控制策略。机器人为神经传递受损但有运动意图的患者提供辅助康复训练。采用脑网络算法选择运动图像信号的最优通道,并将公共空间模式(CSP)方法与时频分析方法局部特征尺度分解(LCD)相结合提取时频信息。最后,采用光谱回归判别分析(SRDA)分类器进行分类处理。此外,还设计了同步康复训练和异步康复训练两种康复训练模式。实验结果证明,实现了脑意图驱动的人-机器人协同控制方法,有效地完成了踝关节康复训练任务。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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