Surface EMG-Based Instantaneous Hand Gesture Recognition Using Convolutional Neural Network with the Transfer Learning Method

doi:10.3390/s21072540

	Surface EMG-Based Instantaneous Hand Gesture Recognition Using Convolutional Neural Network with the Transfer Learning Method
	Yu, Zhipeng 1,2; Zhao, Jianghai 1; Wang, Yucheng 1; He, Linglong 2; Wang, Shaonan 1,2
刊名	SENSORS
	2021-04-01
卷号	21
关键词	transfer learning instantaneous gesture recognition surface electromyography convolutional neural network
DOI	10.3390/s21072540
通讯作者	Zhao, Jianghai(jhzhao@iamt.ac.cn)
英文摘要	In recent years, surface electromyography (sEMG)-based human-computer interaction has been developed to improve the quality of life for people. Gesture recognition based on the instantaneous values of sEMG has the advantages of accurate prediction and low latency. However, the low generalization ability of the hand gesture recognition method limits its application to new subjects and new hand gestures, and brings a heavy training burden. For this reason, based on a convolutional neural network, a transfer learning (TL) strategy for instantaneous gesture recognition is proposed to improve the generalization performance of the target network. CapgMyo and NinaPro DB1 are used to evaluate the validity of our proposed strategy. Compared with the non-transfer learning (non-TL) strategy, our proposed strategy improves the average accuracy of new subject and new gesture recognition by 18.7% and 8.74%, respectively, when up to three repeated gestures are employed. The TL strategy reduces the training time by a factor of three. Experiments verify the transferability of spatial features and the validity of the proposed strategy in improving the recognition accuracy of new subjects and new gestures, and reducing the training burden. The proposed TL strategy provides an effective way of improving the generalization ability of the gesture recognition system.
资助项目	Anhui Provincial Natural Science Foundation[1908085MF196] ; The Open Funding Project of National Key Laboratory of Human Factors Engineering[6142222190311] ; The Key Research and Development Plan of Jiangsu Province[BE2017007-1]
WOS研究方向	Chemistry ; Engineering ; Instruments & Instrumentation
语种	英语
出版者	MDPI
WOS记录号	WOS:000638843500001
资助机构	Anhui Provincial Natural Science Foundation ; The Open Funding Project of National Key Laboratory of Human Factors Engineering ; The Key Research and Development Plan of Jiangsu Province
内容类型	期刊论文
源URL	[http://ir.hfcas.ac.cn:8080/handle/334002/121557]
专题	中国科学院合肥物质科学研究院
通讯作者	Zhao, Jianghai
作者单位	1.Chinese Acad Sci, Hefei Inst Phys Sci, Hefei 230031, Peoples R China 2.Univ Sci & Technol China, Hefei 230026, Peoples R China
推荐引用方式 GB/T 7714	Yu, Zhipeng,Zhao, Jianghai,Wang, Yucheng,et al. Surface EMG-Based Instantaneous Hand Gesture Recognition Using Convolutional Neural Network with the Transfer Learning Method[J]. SENSORS,2021,21.
APA	Yu, Zhipeng,Zhao, Jianghai,Wang, Yucheng,He, Linglong,&Wang, Shaonan.(2021).Surface EMG-Based Instantaneous Hand Gesture Recognition Using Convolutional Neural Network with the Transfer Learning Method.SENSORS,21.
MLA	Yu, Zhipeng,et al."Surface EMG-Based Instantaneous Hand Gesture Recognition Using Convolutional Neural Network with the Transfer Learning Method".SENSORS 21(2021).