基于关节肌肉模型的功能性电刺激迭代学习控制

Jiaming Zhang, Lin Zhang, Shaocong Guo, W. Meng, Qingsong Ai, Quan Liu
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引用次数: 0

摘要

功能电刺激(FES)是脑卒中偏瘫患者康复的有效治疗方法。目前,由于电刺激的各种参数难以确定,且电刺激响应容易受到干扰的影响,难以准确控制康复过程中的功能性电刺激。为了提高重复训练过程中轨迹跟踪的控制精度和补偿外界干扰,本文以膝关节为例,设计了一种基于自适应网络模糊推理系统(ANFIS)和迭代学习控制(ILC)的功能性电刺激系统。首先,采用自适应模糊神经推理系统建立关节肌肉模型,采用pid型迭代学习控制器实现功能电刺激参数的调节;基于anfiss的肌肉模型最大误差为1.64Nm,均方根误差为0.4327Nm。实际膝关节运动与预期角度的最大角度误差为22.76°,迭代10次后的均方根误差为6.7413°。因此,本系统实现了功能电刺激在康复训练中的脉宽控制,使患者能够按照预期的轨迹进行康复训练,为脑卒中偏瘫患者的康复训练提供了方便。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Iterative Learning Control of Functional Electrical Stimulation Based on Joint Muscle Model
Functional electrical stimulation (FES) is an effective treatment for the rehabilitation of stroke patients with hemiplegia. At present, it is challenging to accurately control the functional electrical stimulation during rehabilitation as various parameters of electrical stimulation are difficult to determine, and the stimulation response is easily affected by interferences. To improve the control accuracy for trajectory tracking during repetitive training and to compensate external interference, in this paper we take the knee joint as an example designed a functional electrical stimulation system based on adaptive network-based fuzzy inference system (ANFIS) and iterative learning control (ILC). Firstly, an adaptive fuzzy neural inference system was used to establish the joint muscle model, and a PID-type iterative learning controller was used to achieve the adjustment of functional electrical stimulation parameters. The maximum error of the ANFIS-based muscle model was 1.64Nm and the root means square error was 0.4327Nm. The maximum angle error of the actual knee motion compared with the expected angle was 22.76°, and the root means square error was 6.7413° after 10 iterations. Therefore, the system realizes the control of the pulse width of functional electrical stimulation in rehabilitation training, so that patients can carry out rehabilitation training according to the expected trajectory, which provides convenience for the rehabilitation training of stroke hemiplegia patients.
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