CASIA OpenIR  > 智能感知与计算研究中心
A real-time EMG pattern recognition method for virtual myoelectric hand control
Xing, Kexin1; Yang, Peipei2; Huang, Jian3; Wang, Yongji3; Zhu, Quanmin4,5
Source PublicationNEUROCOMPUTING
2014-07-20
Volume136Issue:1Pages:345-355
SubtypeArticle
AbstractThis study proposes a real-time electro-myogram (EMG) pattern recognition approach for the control of multifunction myoelectric hands. In techniques, time and frequency information is extracted by wavelet packet transform (WPT) and the node energy of the WPT coefficients is selected as the feature of the EMG signals. Then a novel feature selection method based on a depth recursive search algorithm is developed so that the high-dimensional features can be reduced by a supervised feature reduction algorithm. Consequently, the support vector machine (SVM) is adopted to give the recognition result. In the experiment, a real-time EMG pattern recognition system is developed to control a virtual hand with EMG signals from antebrachium. The experimental results show both the high accuracy and better real-time performance of the proposed method. (C) 2014 Elsevier B.V. All rights reserved.
KeywordEmg Real-time Pattern Recognition Wavelet Packet Non-parametric Weighted Feature Extraction Svm
WOS HeadingsScience & Technology ; Technology
WOS KeywordFEATURE-EXTRACTION ; FEATURE-PROJECTION ; FEATURE REDUCTION ; CLASSIFICATION ; SIGNAL ; REPRESENTATION ; SYSTEM
Indexed BySCI
Language英语
WOS Research AreaComputer Science
WOS SubjectComputer Science, Artificial Intelligence
WOS IDWOS:000335708800035
Citation statistics
Document Type期刊论文
Identifierhttp://ir.ia.ac.cn/handle/173211/8017
Collection智能感知与计算研究中心
Corresponding AuthorYang, Peipei
Affiliation1.Zhejiang Univ Technol, Coll Informat Engn, Hangzhou 310023, Zhejiang, Peoples R China
2.Chinese Acad Sci, Inst Automat, Natl Lab Pattern Recognit, Ctr Res Intelligent Percept & Comp, Beijing 100190, Peoples R China
3.Huazhong Univ Sci & Technol, Sch Automat, Key Lab Image Proc & Intelligent Control, Wuhan 430074, Peoples R China
4.China Univ Petr, Coll Chem Engn, Dept Chem Ind Equipment & Control Engn, Qingdao 266580, Peoples R China
5.Univ W England, Dept Engn Design & Math, Bristol BS16 1QY, Avon, England
Corresponding Author AffilicationChinese Acad Sci, Inst Automat, Natl Lab Pattern Recognit, Beijing 100190, Peoples R China
Recommended Citation
GB/T 7714
Xing, Kexin,Yang, Peipei,Huang, Jian,et al. A real-time EMG pattern recognition method for virtual myoelectric hand control[J]. NEUROCOMPUTING,2014,136(1):345-355.
APA Xing, Kexin,Yang, Peipei,Huang, Jian,Wang, Yongji,&Zhu, Quanmin.(2014).A real-time EMG pattern recognition method for virtual myoelectric hand control.NEUROCOMPUTING,136(1),345-355.
MLA Xing, Kexin,et al."A real-time EMG pattern recognition method for virtual myoelectric hand control".NEUROCOMPUTING 136.1(2014):345-355.
Files in This Item: Download All
File Name/Size DocType Version Access License
1-s2.0-S092523121400(1882KB)期刊论文作者接受稿开放获取CC BY-NC-SAView Download
Related Services
Recommend this item
Bookmark
Usage statistics
Export to Endnote
Google Scholar
Similar articles in Google Scholar
[Xing, Kexin]'s Articles
[Yang, Peipei]'s Articles
[Huang, Jian]'s Articles
Baidu academic
Similar articles in Baidu academic
[Xing, Kexin]'s Articles
[Yang, Peipei]'s Articles
[Huang, Jian]'s Articles
Bing Scholar
Similar articles in Bing Scholar
[Xing, Kexin]'s Articles
[Yang, Peipei]'s Articles
[Huang, Jian]'s Articles
Terms of Use
No data!
Social Bookmark/Share
File name: 1-s2.0-S0925231214000162-main.pdf
Format: Adobe PDF
All comments (0)
No comment.
 

Items in the repository are protected by copyright, with all rights reserved, unless otherwise indicated.