Multimodal data collection framework for mental stress monitoring

Accurate recognition of people's responses to stress and timely management of stress is one of the important aspects of maintaining good health. However, recognizing such reactions is difficult since people react to stressful events in various ways. Accordingly, we propose a multi-modal stress monitoring framework to examine people's physiological and behavioral reactions to stressors. Our framework consists of (i) multimodal data collection related to mental stress, (ii) stress inducing experiment in a laboratory, and (iii) signal examination software in real-time and after the data collection. Through preliminary experiments, we have examined how people show various reactions to different kinds of stressful tasks. Finally, based on the proposed framework, we will establish a database contributing to the mental health sensing research.