On interactive data visualization of physiological low-cost-sensor data with focus on mental stress

Abstract

Emotions are important mental and physiological states influencing perception and cognition and have been a topic of interest in Human-Computer Interaction (HCI) for some time. Popular examples include stress detection or affective computing. The use of emotional effects for various applications in decision support systems is of increasing interest. Emotional and affective states represent very personal data and could be used for burn-out prevention. In this paper we report on first results and experiences of our EMOMES project, where the goal was to design and develop an end-user centered mobile software for interactive visualization of physiological data. Our solution was a star-plot visualization, which has been tested with data from N=50 managers (aged 25-55) taken during a burn-out prevention seminar. The results demonstrate that the leading psychologist could obtain insight into the data appropriately, thereby providing support in the prevention of stress and burnout syndromes. © 2013 IFIP International Federation for Information Processing.