Institute of Computing Technology, Chinese Academy IR
Dual layer transfer learning for sEMG-based user-independent gesture recognition | |
Zhang, Yingwei1,2; Chen, Yiqiang1,2,3; Yu, Hanchao1; Yang, Xiaodong1,2; Lu, Wang1,2 | |
2020-04-05 | |
发表期刊 | PERSONAL AND UBIQUITOUS COMPUTING |
ISSN | 1617-4909 |
页码 | 12 |
摘要 | During the last few years, significant attention has been paid to surface electromyographic (sEMG) signal-based gesture recognition. Nevertheless, sEMG signal is sensitive to various user-dependent factors, like skin impedance and muscle strength, which causes the existing gesture recognition models not suitable for new users and huge precision dropping. Therefore, we propose a dual layer transfer learning framework, named dualTL, to realize user-independent gesture recognition based on sEMG signal. DualTL is composed of two layers. The first layer of dualTL leverages the correlations of sEMG signal among different users to label partial gestures with high confidence from new users. Then, according to the consistencies of sEMG signal from the same users, the rest gestures are labeled in the second layer. We compare our method with three universal machine learning methods, seven representative transfer learning methods, and two deep learning-based sEMG gesture recognition methods. Experimental results show that the average recognition accuracy of dualTL is 80.17%. Comparing with SMO, KNN, RF, PCA, TCA, STL, and CWT, the performance improves 24.26% approximately. |
关键词 | Gesture recognition Surface electro-myography User-independent Transfer learning Dual layer |
DOI | 10.1007/s00779-020-01397-0 |
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[61972383] ; R&D Plan in Key Field of Guangdong Province[2019B010109001] ; Alibaba Group through Alibaba Innovative Research (AIR) Program |
WOS研究方向 | Computer Science ; Telecommunications |
WOS类目 | Computer Science, Information Systems ; Telecommunications |
WOS记录号 | WOS:000523580600001 |
出版者 | SPRINGER LONDON LTD |
引用统计 | |
文献类型 | 期刊论文 |
条目标识符 | http://119.78.100.204/handle/2XEOYT63/14113 |
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, Beijing Key Lab Mobile Comp & Pervas Device, Inst Comp Technol, Beijing, Peoples R China 2.Univ Chinese Acad Sci, Beijing, Peoples R China 3.Pengcheng Lab, Shenzhen, Peoples R China |
推荐引用方式 GB/T 7714 | Zhang, Yingwei,Chen, Yiqiang,Yu, Hanchao,et al. Dual layer transfer learning for sEMG-based user-independent gesture recognition[J]. PERSONAL AND UBIQUITOUS COMPUTING,2020:12. |
APA | Zhang, Yingwei,Chen, Yiqiang,Yu, Hanchao,Yang, Xiaodong,&Lu, Wang.(2020).Dual layer transfer learning for sEMG-based user-independent gesture recognition.PERSONAL AND UBIQUITOUS COMPUTING,12. |
MLA | Zhang, Yingwei,et al."Dual layer transfer learning for sEMG-based user-independent gesture recognition".PERSONAL AND UBIQUITOUS COMPUTING (2020):12. |
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