Constructing Bodily Emotion Maps Based on High-Density Body Surface Potentials for Psychophysiological Computing

doi:10.1109/JBHI.2023.3339382

	Constructing Bodily Emotion Maps Based on High-Density Body Surface Potentials for Psychophysiological Computing
	Hu, Wenbiao 4; Bian, Guibin 3; Huang, Linfei 4; Pi, Yao 4; Zhang, Xianbin 4; Zhang, Xiaoyun 4; de Albuquerque, Victor Hugo C.2; Wu, Wanqing 1,4
刊名	IEEE JOURNAL OF BIOMEDICAL AND HEALTH INFORMATICS
	2024-05-01
卷号	28 期号:5 页码:2500-2511
关键词	Body surface potentials emotion maps psychophysiological computing
ISSN号	2168-2194
DOI	10.1109/JBHI.2023.3339382
通讯作者	Wu, Wanqing(wuwanqing@mail.sysu.edu.cn)
英文摘要	Emotion is a complex physiological and psychological activity, accompanied by subjective physiological sensations and objective physiological changes. The body sensation map describes the changes in body sensation associated with emotion in a topographic manner, but it relies on subjective evaluations from participants. Physiological signals are a more reliable measure of emotion, but most research focuses on the central nervous system, neglecting the importance of the peripheral nervous system. In this study, a body surface potential mapping (BSPM) system was constructed, and an experiment was designed to induce emotions and obtain high-density body surface potential information under negative and non-negative emotions. Then, by constructing and analyzing the functional connectivity network of BSPs, the high-density electrophysiological characteristics are obtained and visualized as bodily emotion maps. The results showed that the functional connectivity network of BSPs under negative emotions had denser connections, and emotion maps based on local clustering coefficient (LCC) are consistent with BSMs under negative emotions. in addition, our features can classify negative and non-negative emotions with the highest classification accuracy of 80.77%. In conclusion, this study constructs an emotion map based on high-density BSPs, which offers a novel approach to psychophysiological computing.
资助项目	National Key R&D Program of China
WOS关键词	RECOGNITION ; EEG
WOS研究方向	Computer Science ; Mathematical & Computational Biology ; Medical Informatics
语种	英语
出版者	IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC
WOS记录号	WOS:001221547700032
资助机构	National Key R&D Program of China
内容类型	期刊论文
源URL	[http://ir.ia.ac.cn/handle/173211/58433]
专题	智能机器人系统研究
通讯作者	Wu, Wanqing
作者单位	1.Sun Yat Sen Univ, Guangdong Prov Key Lab Sensor Technol & Biomed lIn, Guangzhou 518107, Peoples R China 2.Univ Fed Ceara, Dept Teleinformat Engn, BR-60020181 Fortaleza, Brazil 3.Chinese Acad Sci, Inst Automat, Beijing 100190, Peoples R China 4.Sun Yat Sen Univ, Sch Biomed Engn, Guangzhou 518107, Peoples R China
推荐引用方式 GB/T 7714	Hu, Wenbiao,Bian, Guibin,Huang, Linfei,et al. Constructing Bodily Emotion Maps Based on High-Density Body Surface Potentials for Psychophysiological Computing[J]. IEEE JOURNAL OF BIOMEDICAL AND HEALTH INFORMATICS,2024,28(5):2500-2511.
APA	Hu, Wenbiao.,Bian, Guibin.,Huang, Linfei.,Pi, Yao.,Zhang, Xianbin.,...&Wu, Wanqing.(2024).Constructing Bodily Emotion Maps Based on High-Density Body Surface Potentials for Psychophysiological Computing.IEEE JOURNAL OF BIOMEDICAL AND HEALTH INFORMATICS,28(5),2500-2511.
MLA	Hu, Wenbiao,et al."Constructing Bodily Emotion Maps Based on High-Density Body Surface Potentials for Psychophysiological Computing".IEEE JOURNAL OF BIOMEDICAL AND HEALTH INFORMATICS 28.5(2024):2500-2511.