文献类型：期刊文献

中文题名：基于肌音信号的虚拟假肢控制

英文题名：Control of Virtual Prosthesis Based on Mechanomyogram Signal

作者：夏春明[1];杨正宜[1];曹炜[1];曹恒[1]

机构：[1]华东理工大学机械与动力工程学院,上海200237

年份：2010

卷号：36

期号：4

起止页码：591

中文期刊名：华东理工大学学报（自然科学版）

外文期刊名：Journal of East China University of Science and Technology

收录：CSTPCD;;Scopus;北大核心:【北大核心2008】；CSCD:【CSCD2011_2012】；

基金：国家自然科学基金项目(50775072)

语种：中文

中文关键词：肌音;特征提取;分类;假肢控制;虚拟手

外文关键词：MMG; feature extraction; classification; prosthetics control; virtual hand

摘要：将肌音(Mechanomyography,MMG)信号作为假肢控制的生理信号源,实现了对于虚拟假肢的抓放控制。针对手部在握紧-张开动作过程中前臂肌肉声音信号,提取动作信号的7种时域特征并利用线性分类器进行分类识别,用以分辨手部动作类型,正确率为(95.63±2.55)%,并利用辨识结果产生控制信号实现对虚拟手的控制。结果表明肌音信号的动作判断具有很高的正确率,为利用肌音信号控制假肢提供了依据。
A novel way was presented to drive a virtual hand by using mechanomyography（MMG） signal. The MMG signal of the hand open grip motion is acquired from the forearm, and seven kinds of time-domain features were extracted. Linear discriminant analysis was used for hand motion modes recognition. The final classification accuracy of motion modes is （95. 63±2. 55）%. Motion recognition results were utilized to generate proper pulses to manipulate a virtual prosthesis. The results show that the MMG signal has high accuracy of judging movements, and provides basis for prosthetic control of using MMG signal.