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Stress Detection Using Smart Phone Data

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eHealth 360°

Abstract

In today’s society, working environments are becoming more stressful. The problem of occupational stress is generally recognized as one of the major factors leading to a wide spectrum of health problems. However work should, ideally, be a source of health, pride and happiness, in the sense of enhancing motivation and strengthening personal development. In this work, we present StayActive, a system which aims to detect stress and burn-out risks by analyzing the behaviour of the users via their smartphone. The main purpose of StayActive is the use of the mobile sensor technology for detecting stress. Then a mobile service can recommend and present various relaxation activities “just in time” in order to allow users to carry out and solve everyday tasks and problems at work. In particular, we collect data from people’s daily phone usage gathering information about the sleeping pattern, the social interaction and the physical activity of the user. We assign a weight factor to each of these three dimensions of wellbeing according to the user’s personal perception and build a stress detection system. We evaluate our system in a real world environment with young adults and people working in the transportation company of Geneva. This paper highlights the architecture and model of this innovative stress detection system. The main innovation of this work is addressed in the fact that the way the stress level is computed is as less invasive as possible for the users.

This work was co-funded by the State Secretariat for Education, Research and Innovation of the Swiss federal government and the European Union, in the frame of the EU AAL project StayActive (aal-2013-6-126).

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Correspondence to Panagiotis Kostopoulos .

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© 2017 ICST Institute for Computer Sciences, Social Informatics and Telecommunications Engineering

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Kostopoulos, P., Kyritsis, A.I., Deriaz, M., Konstantas, D. (2017). Stress Detection Using Smart Phone Data. In: Giokas, K., Bokor, L., Hopfgartner, F. (eds) eHealth 360°. Lecture Notes of the Institute for Computer Sciences, Social Informatics and Telecommunications Engineering, vol 181. Springer, Cham. https://doi.org/10.1007/978-3-319-49655-9_41

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  • DOI: https://doi.org/10.1007/978-3-319-49655-9_41

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-49654-2

  • Online ISBN: 978-3-319-49655-9

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