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Bodily Electrodermal Representations for Affective Computing

delete2024-07-01
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PRE
AI
X
Xinyu Shui
R
Rongzan Lin
Z
Ziyang Luo
B
Bingxin Lin
X
Xinxin Mao
H
Haojie Li
刘冉 cover
刘冉 (Ran Liu) *
张丹 cover
张丹 (Dan Zhang) *
DOI:10.1109/TAFFC.2023.3315973delete
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Abstract

Abstract

En 中文
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.
Keywords:
Skin
Sensors
Wrist
Abdomen
Physiology
Electrodes
Particle measurements
Affective computing
emotional responses
body regions
bioimpedance
multisensor systems

Journal

IEEE Transactions on Affective Computing cover
IEEE Transactions on Affective Computing
IF:
9.8
Papers:
1.4K
Citations:
9.1K

Organization

T
tsinghua university
Scholars:
11.9W
Papers: 10.0W
Citations: 137
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