title: SensibleSleep: A Bayesian Model for Learning Sleep Patterns from Smartphone Events.
abstract: We propose a Bayesian model for extracting sleep patterns from smartphone events. Our method is able to identify individuals' daily sleep periods and their evolution over time, and provides an estimation of the probability of sleep and wake transitions. The model is fitted to more than 400 participants from two different datasets, and we verify the results against ground truth from dedicated armband sleep trackers. We show that the model is able to produce reliable sleep estimates with an accuracy of 0.89, both at the individual and at the collective level. Moreover the Bayesian model is able to quantify uncertainty and encode prior knowledge about sleep patterns. Compared with existing smartphone-based systems, our method requires only screen on/off events, and is therefore much less intrusive in terms of privacy and more battery-efficient.
authors.affiliation: DTU Compute, Technical University of Denmark, Kgs. Lyngby, Denmark.
authors.forename: Andrea
authors.initials: A
authors.lastname: Cuttone
authors.affiliation: DTU Compute, Technical University of Denmark, Kgs. Lyngby, Denmark.
authors.forename: Per
authors.initials: P
authors.lastname: Bækgaard
authors.affiliation: DTU Compute, Technical University of Denmark, Kgs. Lyngby, Denmark.|Sony Mobile, Nya Vattentornet, Mobilvägen, Lund, Sweden.
authors.forename: Vedran
authors.initials: V
authors.lastname: Sekara
authors.affiliation: Sony Mobile, Nya Vattentornet, Mobilvägen, Lund, Sweden.
authors.forename: Håkan
authors.initials: H
authors.lastname: Jonsson
authors.affiliation: DTU Compute, Technical University of Denmark, Kgs. Lyngby, Denmark.
authors.forename: Jakob Eg
authors.initials: JE
authors.lastname: Larsen
authors.affiliation: DTU Compute, Technical University of Denmark, Kgs. Lyngby, Denmark.|The Niels Bohr Institute, University of Copenhagen, Copenhagen, Denmark.
authors.forename: Sune
authors.initials: S
authors.lastname: Lehmann
mesh_terms: D001499:Bayes Theorem; D000066949:Biobehavioral Sciences; D006184:Habits; D006801:Humans; D007858:Learning / Q000502:physiology*; D008954:Models, Biological; D011336:Probability; D012890:Sleep / Q000502:physiology*; D000068997:Smartphone