Wearable Affective Life-Log System for Understanding Emotion Dynamics in Daily Life
November 04, 2019 Β· Declared Dead Β· π arXiv.org
"No code URL or promise found in abstract"
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Authors
Byung Hyung Kim, Sungho Jo
arXiv ID
1911.01072
Category
cs.AI: Artificial Intelligence
Cross-listed
cs.HC,
cs.NE
Citations
1
Venue
arXiv.org
Last Checked
4 months ago
Abstract
Past research on recognizing human affect has made use of a variety of physiological sensors in many ways. Nonetheless, how affective dynamics are influenced in the context of human daily life has not yet been explored. In this work, we present a wearable affective life-log system (ALIS), that is robust as well as easy to use in daily life to detect emotional changes and determine their cause-and-effect relationship on users' lives. The proposed system records how a user feels in certain situations during long-term activities with physiological sensors. Based on the long-term monitoring, the system analyzes how the contexts of the user's life affect his/her emotion changes. Furthermore, real-world experimental results demonstrate that the proposed wearable life-log system enables us to build causal structures to find effective stress relievers suited to every stressful situation in school life.
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