English

Wearable Affective Life-Log System for Understanding Emotion Dynamics in Daily Life

Artificial Intelligence 2019-11-07 v2 Human-Computer Interaction Neural and Evolutionary Computing

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.

Keywords

Cite

@article{arxiv.1911.01072,
  title  = {Wearable Affective Life-Log System for Understanding Emotion Dynamics in Daily Life},
  author = {Byung Hyung Kim and Sungho Jo},
  journal= {arXiv preprint arXiv:1911.01072},
  year   = {2019}
}