维普中文期刊产品整合服务

Towards semi-supervised myoelectric finger motion recognition based on spatial motor units activation

查看全文 作　　者：GUO [1,2]WeiChao;WANG [1]Mian;SHENG [1,2]XinJun;ZHU [1,2]XiangYang 高影响力作者 机构地区：[1]State Key Laboratory of Mechanical System and Vibration,School of Mechanical Engineering,Shanghai Jiao Tong University,Shanghai 200240,China;[2]Meta Robotics Institute,Shanghai Jiao Tong University,Shanghai 200240,China高影响力机构 出　　处：《Science China(Technological Sciences)》索引2022年第65卷第6期,共11页高影响力期刊 基　　金：supported in part by the China National Key R&D Program(Grant No.2018YFB1307200);the National Natural Science Foundation of China (Grant Nos.51905339&91948302)。 摘　　要：It is vital to recognize the intention of finger motions for human-machine interaction(HMI).The latest research focuses on fine myoelectric control through the decoding of neural motor unit action potential trains(MUAPt) from high-density surface electromyographic(sEMG) signals.However,the existing EMG decoding algorithms rarely obtain the spatial matching relationship between decoded motion units(MU) and designated muscles,and the control interface can only recognize the trained hand gestures.In this study,a semi-supervised HMI based on MU-muscle matching(MMM) is proposed to recognize individual finger motions and even the untrained combined multi-finger actions.Through automatic channel selection from high-density s EMG signals,the optimal spatial positions to monitor the MU activation of finger muscles are determined.Finger tapping experiment is carried out on ten subjects,and the experimental results show that the proposed s EMG decomposition algorithm based on MMM can accurately identify single finger motions with an accuracy of 93.1%±1.4%,which is comparable to that of state-of-the-art pattern recognition methods.Furthermore,the MMM allows unsupervised recognizing the untrained combined multi-finger motions with an accuracy of 73%±3.8%.The outcomes of this study benefit the practical applications of HMI,such as controlling prosthetic hand and virtual keyboard. 关 键 词：myoelectric control SEMI-SUPERVISED motor units activation channel selection template matching
相关文献

参考文献(50)

引证文献(1)

耦合文献(6)

网站首页 | 关于我们 | 联系我们 | 产品服务 | 客服中心 | 广告服务 | 版权声明 | 网站联盟 | 友情链接 | 售卡网点

版权所有© 渝B2-20050021-1　渝公网安备 50019002500403号　违法和不良信息举报中心

互联网出版许可证 新出网证(渝)字10号 全国400电话 - 免长途话费