sEMG-Based Gesture Recognition Method for Coal Mine Inspection Manipulator Using Multistream CNN

doi:10.1109/JSEN.2023.3264646

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	sEMG-Based Gesture Recognition Method for Coal Mine Inspection Manipulator Using Multistream CNN
	Tong, Lina 1; Zhang, Mingjia 1; Ma, Hanghang 1; Wang, Chen 2; Peng, Liang 2
刊名	IEEE SENSORS JOURNAL
	2023-05-15
卷号	23 期号:10 页码:11082-11090
关键词	Sensors Muscles Inspection Coal mining Robots Feature extraction Gesture recognition Coal mine inspection manipulator gestures recognition multistream convolutional neural network (CNN) surface electromyography (sEMG) time--frequency graph feature
ISSN号	1530-437X
DOI	10.1109/JSEN.2023.3264646
通讯作者	Wang, Chen(wangchen2016@ia.ac.cn)
英文摘要	With the rapid development of intelligent mining technology, remote-operated underground inspection and rescue robot have been widely used. This article recognized the operator's emergency gestures based on forearm surface electromyography (sEMG). First, a wireless six-channel sEMG acquisition device is built and a dataset named coal mine inspection manipulator gestures (CMMG) is acquired; then, the features of each channel signal are extracted to a 2-D graph by a continue wavelet transform (CWT) method. The multistream convolutional neural network (CNN) model is built to analyze the feature graphs so as to detect action segments. The comparative experiments showed that the method improved the accuracy and showed better performance on both the CMMG dataset and the public Ninapro DB1 dataset.
资助项目	National Key Research and Development Program of China[2022YFC3601200] ; National Natural Science Foundation of China[62203441] ; National Natural Science Foundation of China[U21A20479] ; Beijing Natural Science Foundation[4232053]
WOS关键词	NETWORK ; ERROR
WOS研究方向	Engineering ; Instruments & Instrumentation ; Physics
语种	英语
出版者	IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC
WOS记录号	WOS:000991857800081
资助机构	National Key Research and Development Program of China ; National Natural Science Foundation of China ; Beijing Natural Science Foundation
内容类型	期刊论文
源URL	[http://ir.ia.ac.cn/handle/173211/53480]
专题	多模态人工智能系统全国重点实验室
通讯作者	Wang, Chen
作者单位	1.China Univ Min & Technol Beijing, Dept Elect Engn & Automat, Beijing 100083, Peoples R China 2.Chinese Acad Sci, Inst Automat, State Key Lab Multimodal Artificial Intelligence S, Beijing 100190, Peoples R China
推荐引用方式 GB/T 7714	Tong, Lina,Zhang, Mingjia,Ma, Hanghang,et al. sEMG-Based Gesture Recognition Method for Coal Mine Inspection Manipulator Using Multistream CNN[J]. IEEE SENSORS JOURNAL,2023,23(10):11082-11090.
APA	Tong, Lina,Zhang, Mingjia,Ma, Hanghang,Wang, Chen,&Peng, Liang.(2023).sEMG-Based Gesture Recognition Method for Coal Mine Inspection Manipulator Using Multistream CNN.IEEE SENSORS JOURNAL,23(10),11082-11090.
MLA	Tong, Lina,et al."sEMG-Based Gesture Recognition Method for Coal Mine Inspection Manipulator Using Multistream CNN".IEEE SENSORS JOURNAL 23.10(2023):11082-11090.