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ALIS: Learning Affective Causality Behind Daily Activities From a Wearable Life-Log System
IEEE Transactions on Cybernetics ( IF 11.8 ) Pub Date : 2021-09-08 , DOI: 10.1109/tcyb.2021.3106638
Byung Hyung Kim , Sungho Jo , Sunghee Choi

Human emotions and behaviors are reciprocal components that shape each other in everyday life. While the past research on each element has made use of various physiological sensors in many ways, their interactive relationship in the context of 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 accurately detect emotional changes and determine the cause-and-effect relationship between emotions and emotional situations in users’ lives. The proposed system records how a user feels in certain situations during long-term activities using physiological sensors. Based on the long-term monitoring, the system analyzes how the contexts of the user’s life affect his/her emotional changes and builds causal structures between emotions and observable behaviors in daily situations. Furthermore, we demonstrate that the proposed system enables us to build causal structures to find individual sources of mental relief suited to negative situations in school life.

中文翻译:

ALIS:从可穿戴生活日志系统学习日常活动背后的情感因果关系

人类的情绪和行为是相互影响的,在日常生活中相互影响。虽然过去对每个元素的研究都以多种方式利用了各种生理传感器,但尚未探索它们在日常生活中的相互作用关系。在这项工作中,我们提出了一种可穿戴的情感生活日志系统 (ALIS),该系统功能强大且易于在日常生活中使用,以准确检测情绪变化并确定用户情绪与情绪状况之间的因果关系。生活。拟议的系统使用生理传感器记录用户在长期活动期间在某些情况下的感受。基于长期监测,该系统分析用户的生活情境如何影响他/她的情绪变化,并在日常情境中建立情绪与可观察行为之间的因果结构。此外,我们证明所提出的系统使我们能够建立因果结构,以找到适合学校生活中负面情况的个人精神缓解来源。
更新日期:2021-09-08
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