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

--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. For instance, today's coffee is not always the same as yesterday's coffee. The cup of coffee we drank today may not be as enjoyable as the cup of coffee we drank yesterday. While drinking coffee generally helps to reduce a person's stress, the stress-relieving effects of coffee may vary from day to day for many reasons. For a person who likes calm and quiet surronding, a cup of coffee drunk today in a crowded coffee shop with distracting background noise is likely to be less enjoyable than a cup of coffee drunk yesterday in the quiet kitchen of one's own home. This instance shows that a person can have different emotional responses to the same life events in different circumstances. Why and how does a person experience various emotions from a single event under different situations? Answering this question could improve human life in a variety of ways, as by improving physical health. People who suffer from depression are more vulnerable to heart disease than people with no history of depression. Therefore, discovering life elements related to depression and offering guidance to avoid such elements can help sufferers to lessen their suffering and lead a meaningful life. In response to this question, recent researches on recognizing human affect has made use of a variety of physiological sensors in many ways. B. Kim and S. Jo are with the School of Computing, KAIST, Republic of Korea. S. Jo is the corresponding author.