Wearing-independent hand gesture recognition method based on EMG armband

doi:10.1007/s00779-018-1152-3

	Wearing-independent hand gesture recognition method based on EMG armband
	Zhang, Yingwei 1,3,4,5; Chen, Yiqiang 1,3,4,5; Yu, Hanchao 2,3,5,7; Yang, Xiaodong 1,3,4,5; Lu, Wang 1,3,4,5; Liu, Hong 6,7
	2018-06-01
发表期刊	PERSONAL AND UBIQUITOUS COMPUTING
ISSN	1617-4909
卷号	22 期号:3 页码:511-524
摘要	Electromyographic (EMG) armband with electrodes mounted around the user's forearm is one of the most ergonomic wearable EMG devices and is used to recognize fine hand gesture with great popularity. Definitely, the distributions of signal differ greatly in different wearing positions of armband based on the physiological characters of EMG, which will cause the performance decline and even the inapplicability of the recognition model built in one position. Hence, this paper proposes a wearing-independent hand gesture recognition method based on EMG armband. To eliminate the influence of wearing position, Standard Space is proposed in this paper. Based on the sequential features of EMG in different scales, the wearing position of armband is predicted and helps unify the original features to the proposed space. Then, with the unified signals, fine hand gesture can be recognized accurately and robustly with lightweight Random Forest (RF). The experimental results showed that the recognition accuracy of the proposed method was 91.47% approximately. And compared with the method without fine feature extraction and feature space unification, the performance was improved by 10.12%.
关键词	Human-computer interaction Hand gesture recognition Electromyographic (EMG)
DOI	10.1007/s00779-018-1152-3
收录类别	SCI
语种	英语
资助项目	National Key Research and Development Plan of China[2017YFB1002801] ; Natural Science Foundation of China[61502456] ; Natural Science Foundation of China[61572471] ; Beijing Science and Technology Committee ; Brain Science Research Program of Beijing[Z161100000216140]
WOS研究方向	Computer Science ; Telecommunications
WOS类目	Computer Science, Information Systems ; Telecommunications
WOS记录号	WOS:000452546600006
出版者	SPRINGER LONDON LTD
引用统计	被引频次：28[WOS] [WOS记录] [WOS相关记录]
文献类型	期刊论文
条目标识符	http://119.78.100.204/handle/2XEOYT63/3503
专题	中国科学院计算技术研究所期刊论文_英文
通讯作者	Chen, Yiqiang
作者单位	1.Chinese Acad Sci, Inst Comp Technol, Beijing, Peoples R China 2.Chinese Acad Sci, Beijing, Peoples R China 3.Beijing Key Lab Mobile Comp & Pervas Device, Beijing, Peoples R China 4.Univ Chinese Acad Sci, Beijing, Peoples R China 5.Beijing Key Lab Parkinsons Dis, Beijing, Peoples R China 6.Shandong Normal Univ, Sch Informat Sci & Engn, Jinan, Shandong, Peoples R China 7.Shandong Prov Key Lab Distributed Comp Software N, Jinan, Shandong, Peoples R China
推荐引用方式 GB/T 7714	Zhang, Yingwei,Chen, Yiqiang,Yu, Hanchao,et al. Wearing-independent hand gesture recognition method based on EMG armband[J]. PERSONAL AND UBIQUITOUS COMPUTING,2018,22(3):511-524.
APA	Zhang, Yingwei,Chen, Yiqiang,Yu, Hanchao,Yang, Xiaodong,Lu, Wang,&Liu, Hong.(2018).Wearing-independent hand gesture recognition method based on EMG armband.PERSONAL AND UBIQUITOUS COMPUTING,22(3),511-524.
MLA	Zhang, Yingwei,et al."Wearing-independent hand gesture recognition method based on EMG armband".PERSONAL AND UBIQUITOUS COMPUTING 22.3(2018):511-524.