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Scalable Passive Sleep Monitoring Using Mobile Phones: Opportunities and Obstacles.

Sohrab SaebThaddeus R CybulskiStephen Matthew SchuellerKonrad Paul KordingDavid C Mohr
Published in: Journal of medical Internet research (2017)
We find that mobile phones provide adequate sleep monitoring in typical use cases, and that our methods generalize well to a broader population than has previously been studied. However, we also observe several types of data artifacts when collecting data in uncontrolled settings. Some of these can be resolved through corrections, but others likely impose a ceiling on the accuracy of sleep prediction for certain subjects. Future research will need to focus more on the understanding of people's behavior in their natural settings in order to develop sleep monitoring tools that work reliably in all cases for all people.
Keyphrases
  • sleep quality
  • physical activity
  • electronic health record
  • big data
  • magnetic resonance imaging
  • magnetic resonance
  • machine learning
  • depressive symptoms