Identification of Wrist Elastic Moment in Healthy Subjects for Control by Functional Electrical Stimulation

Akinori Shimomura, S. Katsura
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Abstract

This study is for a functional electrical stimulation. Functional electrical stimulation is a system that uses electrical stimulation to generate specific joint movements. If the nerve is alive, it is possible to promote muscle contraction from the outside by electrical stimulation. If arbitrary movements are generated, to build a control system is necessary for functional electrical stimulation. A model of muscle contraction is needed for control using functional electrical stimulation. It is assumed that the control accuracy will be improved by incorporating the necessary information into the model based on human physiology. In this study, the angle-dependent term in the reaction during muscle contraction is focused as one of the necessary information characteristics. As the angle changes, the muscle condition changes, resulting in responses such as stretch reflexes and repulsive forces. This is important information because if such a response is not taken into consideration, an error will occur between the model and the actual output. In the conventional research, the angle-dependent term was identified by focusing on the lower limbs, and the parameter fitting was realized by using the double exponential function. In this study, the knowledge of the previous study is applied to the upper limbs to build a model. Since the response is different between the upper limbs and the lower limbs, the movements are not always the same. Therefore, verification was performed. From the experimental results, the model based on the double exponential function was a model that took individual differences into consideration even in the upper limbs.
功能电刺激控制下健康受试者手腕弹性矩的识别
本研究为功能性电刺激。功能性电刺激是一种利用电刺激产生特定关节运动的系统。如果神经是活的,就有可能通过电刺激从外部促进肌肉收缩。如果产生任意运动,则必须建立控制系统以实现功能性电刺激。使用功能性电刺激控制需要肌肉收缩模型。假设通过将必要的信息纳入基于人体生理学的模型,可以提高控制精度。在本研究中,肌肉收缩反应中的角度相关项被作为必要的信息特征之一。随着角度的变化,肌肉状况也会发生变化,从而产生拉伸反射和排斥力等反应。这是很重要的信息,因为如果不考虑这样的响应,模型和实际输出之间就会出现错误。在传统研究中,以下肢为中心识别角度相关项,采用双指数函数实现参数拟合。在本研究中,将前人研究的知识应用于上肢,建立模型。由于上肢和下肢的反应不同,所以动作并不总是相同的。因此,进行了验证。从实验结果来看,基于双指数函数的模型即使在上肢也是考虑了个体差异的模型。
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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