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Smart Phone Sensing to Examine Effects of Social Interactions and Non-sedentary Work Time on Mood Changes

  • Aleksandar Matic
  • Venet Osmani
  • Andrei Popleteev
  • Oscar Mayora-Ibarra
Part of the Lecture Notes in Computer Science book series (LNCS, volume 6967)

Abstract

The typical approach taken by clinical studies examining the factors that affect mood is to use questionnaires in order to record the activities that impact the mood. However, recording activities in this manner suffers from a number of issues including floor effect and difficulty in recalling past activities. Our work instead has focused on using unobtrusive monitoring technology to study mood changes during office hours and two associated factors that influence these changes, namely social activity and non-sedentary patterns. The pilot study ran over the course of 7 days of measurements with the participation of 9 knowledge workers. The results have shown that mood changes are highly correlated with both social interactions and non-sedentary work style. This study is the first to investigate the correlation between mood changes and non-sedentary behavior patterns, opening up a research avenue to explore psychological effects of increasing prevalence of sedentary behavior.

Keywords

Sedentary behavior mood changes accelerometers sitting social interactions activity recognition pervasive computing 

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Copyright information

© Springer-Verlag Berlin Heidelberg 2011

Authors and Affiliations

  • Aleksandar Matic
    • 1
  • Venet Osmani
    • 1
  • Andrei Popleteev
    • 1
  • Oscar Mayora-Ibarra
    • 1
  1. 1.CREATE-NETPovoItaly

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