Prosthetic Leg Locomotion-Mode Identification Based on High-Order Zero-Crossing Analysis Surface Electromyography  

作　　者：LIU Lei YANG Peng LIU Zuojun SONG Yinmao 刘磊;杨鹏;刘作军;宋寅卯(College of Building Environment Engineering,Zhengzhou University of Light Industry,Zhengzhou 450002,China;.2.College of Artificial Intelligence and Data Science,Hebei University of Technology,Tianjin 300130,China)

机构地区：[1]College of Building Environment Engineering,Zhengzhou University of Light Industry,Zhengzhou 450002,China [2]College of Artificial Intelligence and Data Science,Hebei University of Technology,Tianjin 300130,China

出　　处：《Journal of Shanghai Jiaotong university(Science)》2021年第1期84-92,共9页上海交通大学学报（英文版）

基　　金：the Center Plain Science and Technology Innovation Talents(No.194200510016);the Science and Technology Innovation Team Project of Henan Province University(No.19IRTSTHN013);the Key Scien-tific Research Support Project for Institutions of Higher Learning in Henan Province(No.18A413014)。

摘　　要：The research purpose was to improve the accuracy in identifying the prosthetic leg locomotion mode.Surface electromyography(sEMG)combined with high-order zero-crossing was used to identify the prosthetic leg locomotion modes.sEMG signals recorded from residual thigh muscles were chosen as inputs to pattern classifier for locomotion-mode identification.High-order zero-crossing were computed as the sEMG features regarding locomotion modes.Relevance vector machine(RVM)classifier was investigated.Bat algorithm(BA)was used to compute the RVM classifier kernel function parameters.The classification performance of the particle swarm optimization-relevance vector machine(PSO-RVM)and RVM classifiers was compared.The BA-RVM produced lower classification error in sEMG pattern recognition for the transtibial amputees over a variety of locomotion modes:upslope,downgrade,level-ground walking and stair ascent/descent.

关 键 词：intelligent prosthesis surface electromyography(sEMG) relevance vector machine(RVM) high-order zero-crossing bat algorithm(BA) locomotion-mode identification 

分 类 号：TP391[自动化与计算机技术—计算机应用技术]