机械制造与自动化2025，Vol.54Issue(2)：22-26,5.DOI:10.19344/j.cnki.issn1671-5276.2025.02.004
基于不同负载下sEMG的肩肘关节角度预测研究
Prediction of Shoulder and Elbow Joint Angles Based on sEMG under Different Loads
摘要
Abstract
To address the issue of the impact of exoskeleton weight on the accuracy of joint angle prediction,this paper explores the impact of different loads on the accuracy of joint angle prediction models based on electromyography signals,and determines the optimal load.Surface electromyographies are collected under different loads,and time-domain feature values are extracted as feature input signals,all of which are trained through BP neural network and support vector machine to achieve continuous motion prediction of the upper limb shoulder and elbow joints in the sagittal plane.Experiments show that under a load of 10%1RM,the root mean square error of joint angle prediction for the shoulder and elbow joints is the lowest,which can effectively improve the accuracy of joint angle prediction.关键词
上肢负载/表面肌电信号/BP神经网络/支持向量机/角度预测Key words
upper limb load/surface electromyography/BP neural network/support vector machine/angle prediction分类
信息技术与安全科学引用本文复制引用
陆浩琪,郭佳乐,陈劲舟,殷正龙,左敦稳..基于不同负载下sEMG的肩肘关节角度预测研究[J].机械制造与自动化,2025,54(2):22-26,5.基金项目
江苏省科研与实践创新计划项目(SJCX22_0097) （SJCX22_0097）
