功能电刺激控制中基于肌电图的转矩估计

Hossein Kavianirad, Satoshi Endo, T. Keller, S. Hirche
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引用次数: 2

摘要

功能性电刺激(FES)通过皮肤对肌肉纤维施加电脉冲,以帮助运动障碍患者进行功能性运动。肌肉活动反馈(如意志肌电图(vEMG))可以优化FES系统在康复或日常生活活动(ADL)中的性能,然而,在同一块肌肉上同时使用FES和肌电图所产生的伪影会污染肌电图信号。本文采用自适应滤波器,研究了从滤波后的vEMG中估计意志转矩的方法。在此基础上,对5名健康参与者进行了自适应转矩估计的可用性和性能研究,结果表明该滤波器可用于转矩估计。在接下来的步骤中,展示了如何将该映射用于闭环FES控制中以估计意志转矩。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
EMG-Based Volitional Torque Estimation in Functional Electrical Stimulation Control
Functiona1 electrical stimulation (FES) applies electrical pulses to muscle fibers through the skin for assisting functional movements in patients with motor disability. Muscle activity feedback such as volitional Electromyography (vEMG) can optimize the performance of the FES system in both rehabilitation or activity of daily living (ADL), however, artifacts caused by simultaneous use of FES and EMG on the same muscles contaminate the EMG signal. This paper, using an adaptive filter, aims to investigate the estimation of the volitional torque from filtered vEMG. Based on this estimation, the usability and performance of the adaptive filter for estimating volitional torque are studied on 5 healthy participants and we show that this filter can be used for volitional torque estimation. In the next step, it is shown how this map can be used in closed-loop FES control for estimating volitional torque.
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