机器人辅助中风康复:利用遗传算法从肌电图估计肌肉力量/关节扭矩

Arif Wicaksana Oyong, S. Parasuraman, V. L. Jauw
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引用次数: 18

摘要

本项目致力于开发机器人辅助中风康复,通过肌电图(EMG)作为机器人与用户通信之间的接口。在本应用程序中实现肌电图的关键问题是将肌电图信号转换为扭矩数据。提出了一种基于遗传算法的肌电信号估计关节转矩转换的方法。本文讨论了遗传算法的基本原理、求解方法和实现方法。实验与现实生活中的肌电图数据进行了评估方法在机器人辅助中风康复问题的可行性。初步研究表明,该方法可用于肌电关节转矩转换算法。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Robot assisted stroke rehabilitation: Estimation of muscle force/joint torque from EMG using GA
This project focuses on the development of robot-assisted stroke rehabilitation by implementing electromyography (EMG) as the interface between robot and user communication. Key issue in implementation of EMG in this application is conversion of EMG signal into torque data. This paper presents a methodology of EMG signal to estimated joint torque conversion by using genetic algorithm (GA). Basic principle of GA, formulation, and implementation to the problem are discussed in this paper. Experimentation with real life EMG data has been carried out to assess the feasibility of the methodology in robot-assisted stroke rehabilitation problem. Preliminary investigations show that the methodology can be used in EMG to joint torque conversion algorithm.
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