Out of the Lab and into the Fray: Towards Modeling Emotion in Everyday Life

  • Jennifer Healey
  • Lama Nachman
  • Sushmita Subramanian
  • Junaith Shahabdeen
  • Margaret Morris
Part of the Lecture Notes in Computer Science book series (LNCS, volume 6030)


We conducted a 19 participant study using a system comprised of wireless galvanic skin response (GSR), heart rate (HR), activity sensors and a mobile phone for aggregating sensor data and enabling affect logging by the user. Each participant wore the sensors daily for five days, generating approximately 900 hours of continuous data. We found that analysis of emotional events was highly dependent on correct windowing and report results on synthesized windows around annotated events. Where raters agreed on the timing and quality of the emotion we were able to recognize 85% of the high and low energy emotions and 70% of the positive and negative emotions. We also gained many insights regarding participant’s perception of their emotional state and the complexity of emotion in real life.


Affective computing emotional sensing mood detection 


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Copyright information

© Springer-Verlag Berlin Heidelberg 2010

Authors and Affiliations

  • Jennifer Healey
    • 1
  • Lama Nachman
    • 1
  • Sushmita Subramanian
    • 1
  • Junaith Shahabdeen
    • 1
  • Margaret Morris
    • 2
  1. 1.Intel LabsFuture Technology ResearchSanta Clara
  2. 2.Digital Health Group, Intel Corp.Portland

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