Title :
Sensors Classification for Stress Analysis: Toward Automatic Stress Recognition
Author :
Sysoev, Mikhail ; Kos, Andrej ; Sedlar, Urban ; Pogacnik, Matevz
Author_Institution :
Lab. for Telecommun., Univ. of Ljubljana, Ljubljana, Slovenia
Abstract :
Stress affects people\´s health and well-being of the world\´s economies. Despite the progress in physiological stress recognition, there are problems that require solutions in the creation of automated systems of stress determination in prolonged real-life situations. These tasks are analysis of stress in daily life, during physical activity and personalization of this analysis. We described these tasks and answered the question: "Why it is important to use context and behavioral data into stress recognition systems?" We have presented sensors classification included behavioral and context data, physiological and physical features and others, like self-reports and questionnaires. And we have performed the stress model.
Keywords :
behavioural sciences computing; physiology; automatic stress recognition; behavioral data; physical activity; physical feature; physiological feature; physiological stress recognition; sensor classification; stress analysis; stress determination; stress recognition systems; Accuracy; Conferences; Context; Europe; Physiology; Sensors; Stress; behavioral data; mobile context; sensors classification; stress model; stress recognition;
Conference_Titel :
Identification, Information and Knowledge in the Internet of Things (IIKI), 2014 International Conference on
DOI :
10.1109/IIKI.2014.31