南京信息工程大学学报2026，Vol.18Issue(1)：1-10,10.DOI:10.13878/j.cnki.jnuist.20250114002
手腕运动下的动态肌电解码研究
Dynamic electromyography decoding under wrist movements
摘要
Abstract
The wrist is among the most flexible joints in the human body.Decomposing the surface Electromyogra-phy(sEMG)signals enables the estimation of the deep neural drives underlying human body movements.Current research on wrist moments primarily focuses on isometric contractions,leaving the decoding of neural drives under dynamic conditions an area requiring substantial exploration.This study investigated Motor Unit(MU)decomposi-tion during wrist movements under varying resistance levels,which were precisely controlled using a magnetorheolog-ical damper.The collected continuous electromyography signals were segmented into short intervals where Motor Unit Action Potential(MUAP)waveforms remained relatively stable.Then,a classic decomposition algorithm was applied to each short interval to obtain the Motor Unit Spike Train(MUST),and the MUs were tracked across con-secutive intervals via their overlapping parts to reconstruct complete firing sequences.This paper studied the decom-position of MUs during wrist extension and flexion under three resistance levels:20%,40%,and 60%of the Maxi-mum Voluntary Contraction(MVC).Results showed that the proposed dynamic decomposition algorithm effectively decomposed MUs from forearm sEMG signals,although performance somewhat declined with increasing resistance.During wrist extension,up to 10±1 MUs were decomposed,with Pulse-to-Noise Ratio(PNR)and Silhouette Coeffi-cient(SIL)reaching 19.87±1.42 dB and 0.91±0.03,respectively.While during wrist flexion,up to 22±3 MUs were decomposed,with PNR and SIL values of 20.69±2.14 dB and 0.92±0.03,respectively.This study confirms the feasibility of neural drive decoding from sEMG signals during wrist movements under different resistances,high-lighting significant potential for the application of High-Density sEMG(HD-sEMG)under dynamic muscle contrac-tions.关键词
高密度肌电/手腕运动/运动解码/动态分解/神经驱动Key words
high-density surface electromyography(HD-sEMG)/wrist movement/movement decoding/dynamic decomposition/neural drive分类
信息技术与安全科学引用本文复制引用
杨心昊,徐宝国,宋爱国..手腕运动下的动态肌电解码研究[J].南京信息工程大学学报,2026,18(1):1-10,10.基金项目
国家重点研发计划(202022YFC2405602) （202022YFC2405602）
江苏省前沿引领技术基础研究专项(BK20192004A) （BK20192004A）
江苏省自然科学基金(BK20221464) （BK20221464）
