Context Aware Stress Detection in the AWARE Framework

Physiological signals are good predictors of stress, which can be thought of as part of a user’s context. In this work, an option to combine the user’s stress level with other contextual factors is presented. This is done in the form of two AWARE plugins-Android applications that can be incorporated into a smartphone monitoring setup. In the first part, the stress detection method is described, which consists of a lab stress detector, an activity classier, and a context-aware stress model. In the second part, two plugins are described. One streams the data from the Empatica E4 wristband and the other one uses this physiological data to predict stress. Finally, some possibilities to improve this work are presented.