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Wearing-independent hand gesture recognition method based on EMG armband

文献类型：期刊论文

作者Yang, Xiaodong3,4,5,7; Yu, Hanchao1,3,5,6; Chen, Yiqiang3,4,5,7; Zhang, Yingwei3,4,5,7; Liu, Hong1,2; Lu, Wang3,4,5,7
刊名PERSONAL AND UBIQUITOUS COMPUTING
出版日期2018-06-01
卷号22期号:3页码:511-524
关键词Human-computer interaction Hand gesture recognition Electromyographic (EMG)
ISSN号1617-4909
DOI10.1007/s00779-018-1152-3
英文摘要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%.
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
语种英语
WOS记录号WOS:000452546600006
出版者SPRINGER LONDON LTD
源URL[http://119.78.100.204/handle/2XEOYT63/3502]  
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.Shandong Prov Key Lab Distributed Comp Software N, Jinan, Shandong, Peoples R China
2.Shandong Normal Univ, Sch Informat Sci & Engn, Jinan, Shandong, Peoples R China
3.Beijing Key Lab Parkinsons Dis, Beijing, Peoples R China
4.Univ Chinese Acad Sci, Beijing, Peoples R China
5.Beijing Key Lab Mobile Comp & Pervas Device, Beijing, Peoples R China
6.Chinese Acad Sci, Beijing, Peoples R China
7.Chinese Acad Sci, Inst Comp Technol, Beijing, Peoples R China
推荐引用方式
GB/T 7714		 Yang, Xiaodong,Yu, Hanchao,Chen, Yiqiang,et al. Wearing-independent hand gesture recognition method based on EMG armband[J]. PERSONAL AND UBIQUITOUS COMPUTING,2018,22(3):511-524.
APA Yang, Xiaodong,Yu, Hanchao,Chen, Yiqiang,Zhang, Yingwei,Liu, Hong,&Lu, Wang.(2018).Wearing-independent hand gesture recognition method based on EMG armband.PERSONAL AND UBIQUITOUS COMPUTING,22(3),511-524.
MLA Yang, Xiaodong,et al."Wearing-independent hand gesture recognition method based on EMG armband".PERSONAL AND UBIQUITOUS COMPUTING 22.3(2018):511-524.

入库方式： OAI收割

来源：计算技术研究所

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