基于GA-SVR模型的肌力康复电刺激系统的设计研究
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1.天津工业大学机械工程学院 天津 300387; 2.天津市现代机电装备技术重点实验室 天津 300387

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TP202

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中国航空科学基金(201729Q2001)项目资助


Design and research of electrical stimulation system for muscle strength rehabilitation based on GA-SVR model
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1.School of Mechanical Engineering, Tian Gong University,Tianjin 300387, China; 2.Tianjin Modern Electromechanical Equipment Technology Key Laboratory,Tianjin 300387, China

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    摘要:

    为了实现康复电刺激系统治疗参数的个性化定制及实时调整,提出了一种基于调制中频电刺激的下肢肌力康复闭环电刺激系统。设计低频调制中频刺激电路,基于遗传算法建立了电刺激参数与膝关节角度之间的支持向量机回归预测模型,并搭建基于模糊内模控制PID的闭环反馈系统,以达到更精确稳定的参数设置效果。通过膝关节运动实验表明,被试者在无痛感的前提下更接近预期的关节运动轨迹,30组膝关节运动角度与预期值最大均方根误差为10.21°,最小均方根误差为5.48°。相比传统低频电刺激,肌电平均振幅具有20 μV以上提升。本文提出的电刺激系统参数可实现因人而异,且可根据闭环反馈结果进行实时调整,该系统能有效活化肌肉、提升肌力,在肌力康复步态训练中有较好的应用前景。

    Abstract:

    In order to realize the personalized customization and realtime adjustment of the therapeutic parameters of the rehabilitation electrical stimulation system, a closedloop electrical stimulation system for lower limb muscle strength rehabilitation based on modulated medium frequency electrical stimulation was proposed in this paper. A low-frequency modulation and medium-frequency stimulation circuit was designed, and a support vector machine regression prediction model between the electrical stimulation parameters and the angle of the knee joint was established based on the genetic algorithm. A closed-loop feedback system based on fuzzy internal model control PID was built to achieve a more accurate and stable parameter setting effect. The knee motion experiment showed that the subjects were closer to the expected joint motion trajectory without pain. The maximum root mean square error between the knee motion Angle and the expected value in the 30 groups was 10.21°, and the minimum root mean square error was 5.48°. Compared with traditional low-frequency electrical stimulation, the mean amplitude of myoelectric stimulation was increased by more than 20 microvolts. The parameters of the electrical stimulation system proposed in this paper can be realized from person to person, and can be adjusted in real time according to the closed-loop feedback results. The system can effectively activate muscles and improve muscle strength, and has a good application prospect in the gait training of muscle strength rehabilitation.

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隋修武,梁天翼,杨静文.基于GA-SVR模型的肌力康复电刺激系统的设计研究[J].电子测量技术,2023,46(19):35-41

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  • 在线发布日期: 2024-01-15
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