Context-Aware Stress Detection in the AWARE Framework
Marija Trajanoska, Hristijan Gjoreski, Marko Katrasnik, Junos Lukan, Martin Gjoreski, Mitja Lustrek
Journal of Information Security Research, Vol. 9, No. 4, 2018.
DOI: 
Link: http://www.dline.info/jisr/fulltext/v9n4/jisrv9n4_2.pdf
Abstract:
Physiological signals are good predictors of stress, which can be thought of as part of a userâ€™s context. In this
work, an option to combine the userâ€™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.