The Science of Sweet Dreams: Predicting Sleep Efficiency from Wearable Device Data

Aarti Sathyanarayana, Jaideep Srivastava, Luis Fernandez

Research output: Contribution to specialist publicationArticle

10 Citations (Scopus)


Lack of sleep can Erode mental and physical well-being, often exacerbating health problems such as obesity. Wearable devices that capture and analyze sleep quality through predictive methodologies can help patients and medical practitioners make behavioral health decisions that can lead to better sleep and improved health. In the web extra at, guest editor Katarzyna Wac interviews lead author Aarti Sathyanarayana, a PhD student in the University of Minnesota's Department of Computer Science.

Original languageEnglish
Number of pages9
Specialist publicationComputer
Publication statusPublished - 1 Mar 2017



  • big data
  • data analysis
  • health monitoring
  • health tracking
  • healthcare
  • mobile
  • QoL technologies
  • quality-of-life technologies
  • sleep
  • sleep science
  • wearable devices

ASJC Scopus subject areas

  • Computer Science(all)

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