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Well-Being Tracking via Smartphone-Measured Activity and Sleep: Cohort Study.

Orianna DeMasiSidney FeyginAluma DemboAdrian AguileraBenjamin Recht
Published in: JMIR mHealth and uHealth (2017)
Measures of activity and sleep inferred from smartphone activity were strongly related to and somewhat predictive of participants' well-being. Whereas the improvement over naive models was modest, it reaffirms the importance of considering physical activity and sleep for predicting mood and for making automatic mood monitoring a reality.
Keyphrases
  • physical activity
  • sleep quality
  • machine learning
  • body mass index
  • depressive symptoms
  • deep learning
  • hiv infected