摘要
智能膝关节假肢是截肢患者恢复日常运动的重要辅具。对人体下肢运动意图的识别是实现下肢假肢控制的关键。该文针对此问题,提出了一种通过表面肌电信号预测膝关节角度的方法。对表面肌电提取时域特征,通过BP神经网络模型建立平地行走过程中表面肌电信号和膝关节角度的映射关系,预测膝关节角度。
Robotic knee prosthesis plays an important role to assist amputation subjects while recovering in daily living activities and human lower limb motion intention mapping based on surface electromyography(sEMG)is the key step towards the control of robotic knee prosthesis.In this paper,we propose a method for predicting knee joint angles base on sEMG.Predict the knee joint angle by extraction of the time domain features of sEMG and building the mapping relationship between sEMG and knee joint angle during flat walking through BP neural network model.
作者
杜妍辰
孙洁
汪晓铭
黎林荣
杨良栋
喻洪流
DU Yanchen;SUN Jie;WANG Xiaoming;LI Linrong;YANG Liangdong;YU Hongliu(Institute of Rehabilitation Engineering and Technology,University of Shanghai for Science and Technology,Shanghai 200093,China;Shanghai Engineering Research Center of Assistive Devices,Shanghai 200093,China;Key Laboratory of Neural-functional Information and Rehabilitation Engineering of the Ministry of Civil Affairs,Shanghai 200093,China)
出处
《生物医学工程学进展》
CAS
2023年第2期158-162,共5页
Progress in Biomedical Engineering
关键词
表面肌电信号
智能膝关节假肢
BP神经网络
Surface Electromyography(sEMG)
Robotic Knee Prosthesis
BP Neural Network
