Robot assisted stroke rehabilitation: Estimation of muscle force/joint torque from EMG using GA
Robot assisted stroke rehabilitation: Estimation of muscle force/joint torque from EMG using GA
复制标题
机器人辅助中风康复：使用 GA 根据 EMG 估计肌肉力/关节扭矩
DOI：
--
复制
发表时间：
2010
期刊：
影响因子：
--
通讯作者：
V. L. Jauw
中科院分区：
文献类型：
--
作者：
Arif Wicaksana Oyong;S. Parasuraman;V. L. Jauw
该项目的重点是通过使用肌电图（EMG）作为机器人和用户通信之间的接口来开发机器人辅助中风康复。在该应用中实现 EMG 的关键问题是将 EMG 信号转换为扭矩数据。本文提出了一种利用遗传算法（GA）将 EMG 信号转换为估计关节扭矩的方法。本文讨论了遗传算法的基本原理、问题的表述和实现。我们利用现实生活中的肌电图数据进行了实验，以评估该方法在机器人辅助中风康复问题中的可行性。初步研究表明该方法可用于肌电图到关节扭矩的转换算法。
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.
影响因子：
4.3
作者：
Fasoli, SE;Krebs, HI;Hogan, N
通讯作者：
Hogan, N