Towards the Stress Analytics Framework: Managing, Mining, and Visualizing Multi-modal Data for Stress Awareness

Abstract

Stress is experienced by many people on daily basis. Often it remains to be unrecognized and unnoticed. We propose a framework for stress analytics and describe technologies facilitating management and exploration of multi-modal affective data captured in physiological signals, such as galvanic skin response and heart rate, as well as in facial expression, in speech and in written text. We envision that stress analytics can become a useful tool as for individual personal use for stress-awareness as for researchers aiming to study the phenomenon of stress.