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A Presence-Based Context-Aware Chronic Stress Recognition System
Laboratory for Telecommunications, Faculty of Electrical Engineering, University of Ljubljana, Tržaška 25, 1000 Ljubljana, Slovenia
Mirabi Institute, Hrastje 223, 4000 Kranj, Slovenia
* Author to whom correspondence should be addressed.
Received: 20 September 2012; in revised form: 2 November 2012 / Accepted: 9 November 2012 / Published: 16 November 2012
Abstract: Stressors encountered in daily life may play an important role in personal well-being. Chronic stress can have a serious long-term impact on our physical as well as our psychological health, due to ongoing increased levels of the chemicals released in the ‘fight or flight’ response. The currently available stress assessment methods are usually not suitable for daily chronic stress measurement. The paper presents a context-aware chronic stress recognition system that addresses this problem. The proposed system obtains contextual data from various mobile sensors and other external sources in order to calculate the impact of ongoing stress. By identifying and visualizing ongoing stress situations of an individual user, he/she is able to modify his/her behavior in order to successfully avoid them. Clinical evaluation of the proposed methodology has been made in parallel by using electrodermal activity sensor. To the best of our knowledge, the system presented herein is the first one that enables recognition of chronic stress situations on the basis of user context.
Keywords: presence; chronic stress; context awareness; embedded sensors; Hidden Markov models; health monitoring
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Peternel, K.; Pogačnik, M.; Tavčar, R.; Kos, A. A Presence-Based Context-Aware Chronic Stress Recognition System. Sensors 2012, 12, 15888-15906.
Peternel K, Pogačnik M, Tavčar R, Kos A. A Presence-Based Context-Aware Chronic Stress Recognition System. Sensors. 2012; 12(11):15888-15906.
Peternel, Klemen; Pogačnik, Matevž; Tavčar, Rudi; Kos, Andrej. 2012. "A Presence-Based Context-Aware Chronic Stress Recognition System." Sensors 12, no. 11: 15888-15906.