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International Conference on User Modeling, Adaptation, and Personalization

UMAP 2015: User Modeling, Adaptation and Personalization pp 240-251 | Cite as

Smartphone Based Stress Prediction

  • Thomas Stütz
  • Thomas Kowar
  • Michael Kager
  • Martin Tiefengrabner
  • Markus Stuppner
  • Jens Blechert
  • Frank H. Wilhelm
  • Simon Ginzinger
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 9146)

Abstract

Smartphone usage has tremendously increased and most users keep their smartphones close throughout the day. Smartphones have a broad variety of sensors, that could automatically map and track the user’s life and behaviour. In this work we investigate whether automatically collected smartphone usage and sensor data can be employed to predict the experienced stress levels of a user using a customized brief version of the Perceived Stress Scale (PSS). To that end we have conducted a user study in which smartphone data and stress (as measured by the PSS seven times a day) were recorded for two weeks. We found significant correlations between stress scores and smartphone usage as well as sensor data, pointing to innovative ways for automatic stress measurements via smartphone technology. Stress is a prevalent risk factor for multiple diseases. Thus accurate and efficient prediction of stress levels could provide means for targeted prevention and intervention.

Keywords

Stress Prediction Smartphone sensing Data analysis Field study Observational study 

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Copyright information

© Springer International Publishing Switzerland 2015

Authors and Affiliations

  • Thomas Stütz
    • 1
  • Thomas Kowar
    • 1
  • Michael Kager
    • 1
  • Martin Tiefengrabner
    • 1
  • Markus Stuppner
    • 2
  • Jens Blechert
    • 2
  • Frank H. Wilhelm
    • 2
  • Simon Ginzinger
    • 1
  1. 1.Department of Multimedia TechnologyUniversity of Applied Sciences SalzburgPuch/SalzburgAustria
  2. 2.Department of PsychologyUniversity of SalzburgSalzburgAustria

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