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Bodily Electrodermal Representations for Affective Computing.

Authors :
Shui, Xinyu
Lin, Rongzan
Luo, Ziyang
Lin, Bingxin
Mao, Xinxin
Li, Haojie
Liu, Ran
Zhang, Dan
Source :
IEEE Transactions on Affective Computing; Jul-Sep2024, Vol. 15 Issue 3, p1018-1025, 8p
Publication Year :
2024

Abstract

The view of embodied emotion believes that emotions are the emotions of the body. While emotion-specific patterns of self-reported bodily sensation have been previously reported, the physiological bodily representation across emotions remains to be addressed. The present study aimed to investigate the effectiveness of multi-site bodily electrodermal representations of emotions. A multi-channel electrodermal measurement device was designed to record electrodermal activities from nine body sites (neck, back, chest, bilateral abdomen, bilateral wrist, and bilateral ankle) from thirty-six college students (all male), while they were presented with a series of emotional pictures. Using the integral skin conductance response feature and a random forest classification method, the classification of high and low arousal levels achieved an average classification accuracy of 80.4 ± 8.1%, and the classification of positive, neutral, and negative states reached an average classification accuracy of 76.4 ± 10.2%. The classification models for arousal and valence were found to rely on distinct bodily representations. Meanwhile, the classification results of multi-site measurement were significantly better than single-site results. Our findings for the first time illustrate the bodily electrodermal representations of emotion and suggest the feasibility of affective computing using bodily electrodermal signals. [ABSTRACT FROM AUTHOR]

Details

Language :
English
ISSN :
19493045
Volume :
15
Issue :
3
Database :
Complementary Index
Journal :
IEEE Transactions on Affective Computing
Publication Type :
Academic Journal
Accession number :
179509511
Full Text :
https://doi.org/10.1109/TAFFC.2023.3315973