A new control approach to robot assisted rehabilitation

D. Erol, V. Mallapragada, N. Sarkar, E. Taub
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引用次数: 21

Abstract

The goal of our research is to develop a novel control framework to assist stroke patients during rehabilitation therapy. This framework is expected to provide an optimal time-varying assistive force to stroke patients in varying physical and environmental conditions. An artificial neural network (ANN)-based PI-gain scheduling direct force controller is designed to provide optimal force assistance. The human arm model is integrated within the control framework where the ANN uses estimated human arm parameters to select the appropriate PI gains. An online technique to estimate human arm parameters as well as off-line analyses of the force controller are presented in this paper to demonstrate the feasibility and efficacy of the proposed method.
一种新的机器人辅助康复控制方法
我们的研究目标是开发一种新的控制框架,以帮助中风患者在康复治疗期间。该框架有望在不同的身体和环境条件下为脑卒中患者提供最佳的时变辅助力。设计了一种基于人工神经网络(ANN)的pi增益调度直接力控制器,以提供最优力辅助。将人体手臂模型集成到控制框架中,人工神经网络使用估计的人体手臂参数来选择适当的PI增益。本文提出了一种在线估计人体手臂参数的方法,并对力控制器进行了离线分析,以验证该方法的可行性和有效性。
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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