Academic Journal
EmoSense: Revealing True Emotions Through Microgestures.
| Title: | EmoSense: Revealing True Emotions Through Microgestures. |
|---|---|
| Authors: | Fang, Le, Xing, Sark Pangrui, Long, Yonghao, Lee, Kun-Pyo, Wang, Stephen Jia |
| Source: | Advanced Intelligent Systems (2640-4567); Sep2023, Vol. 5 Issue 9, p1-16, 16p |
| Abstract: | Stress is a universally ubiquitous emotional state that takes place everywhere and microgestures (MGs) have been verified to indicate more accurate hidden emotions. However, only limited studies attempted to explore how MGs could reflect stress levels. Herein, EmoSense, an emerging technology for wearable systems containing a three‐layer stress detection mechanism, is proposed: 1) converting the MGs into digital signals; 2) training a machine learning‐based MG detection model; and 3) configuring the stress level based on the MG frequency. To detect the MGs, the swept frequency capacitive sensing technology to is adopted capture the MG signals and the random forest model to detect the MGs effectively is applied. 16 participants are recruited in the pilot study to verify the correlation between stress level and MG frequency. The experimental results further verify that stress level is highly related to other negative emotions that should be studied while handling high stress levels. [ABSTRACT FROM AUTHOR] |
| Copyright of Advanced Intelligent Systems (2640-4567) is the property of Wiley-Blackwell and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.) | |
| ISSN: | 26404567 |
| DOI: | 10.1002/aisy.202300050 |
| Database: | Complementary Index |
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