电子器件2025，Vol.48Issue(1)：25-30,6.DOI:10.3969/j.issn.1005-9490.2025.01.005
基于自适应VMD的sEMG信号识别研究
Research on sEMG Signal Recognition Based on Adaptive VMD
摘要
Abstract
To solve the problem of low accuracy of gesture recognition based on sEMG signal due to surface electromyography(sEMG)signal noise,a gesture recognition algorithm based on adaptive variational mode decomposition(AVMD)of sEMG signal is proposed.Firstly,the sEMG signal is denoised by using AVMD algorithm and improved wavelet threshold.Then,the mean value and fuzzy entropy of sEMG signal are extracted as eigenvalues.Finally,support vector machine(SVM)is used for gesture recognition.The experimental re-sults show that the noise reduction performance index of the sEMG signal gesture recognition method based on AVMD is higher than that of other methods,the gesture recognition accuracy reaches 97.5%,and the corresponding gestures can be accurately recognized in real time in the master-slave training system of the hand rehabilitation robot.关键词
手势识别/表面肌电信号/自适应变分模态分解/信号降噪Key words
gesture recognition/surface electromyography/adaptive variational mode decomposition/signal noise reduction分类
信息技术与安全科学引用本文复制引用
胡家铭,曾庆军,韩春伟,周成诚..基于自适应VMD的sEMG信号识别研究[J].电子器件,2025,48(1):25-30,6.基金项目
国家自然科学基金项目(11574120) （11574120）
江苏省产业前瞻与共性关键技术项目(BE2018103) （BE2018103）
