Constructing Bodily Emotion Maps Based on High-Density Body Surface Potentials for Psychophysiological Computing
文献类型：期刊论文
| 作者 | Hu, Wenbiao1; Bian, Guibin2 ; Huang, Linfei1; Pi, Yao1; Zhang, Xianbin1; Zhang, Xiaoyun1; de Albuquerque, Victor Hugo C.3; Wu, Wanqing1,4
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| 刊名 | IEEE JOURNAL OF BIOMEDICAL AND HEALTH INFORMATICS
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| 出版日期 | 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. |
| WOS关键词 | RECOGNITION ; EEG |
| 资助项目 | National Key R&D Program of China |
| WOS研究方向 | Computer Science ; Mathematical & Computational Biology ; Medical Informatics |
| 语种 | 英语 |
| WOS记录号 | WOS:001221547700032 |
| 出版者 | IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC |
| 资助机构 | National Key R&D Program of China |
| 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, Sch Biomed Engn, Guangzhou 518107, Peoples R China 2.Chinese Acad Sci, Inst Automat, Beijing 100190, Peoples R China 3.Univ Fed Ceara, Dept Teleinformat Engn, BR-60020181 Fortaleza, Brazil 4.Sun Yat Sen Univ, Guangdong Prov Key Lab Sensor Technol & Biomed lIn, 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. |
入库方式： OAI收割
来源：自动化研究所
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