SensibleSleep: A Bayesian Model for Learning Sleep Patterns from Smartphone Events

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 participa...

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Detalles Bibliográficos
Autores principales: Cuttone, Andrea, Bækgaard, Per, Sekara, Vedran, Jonsson, Håkan, Larsen, Jakob Eg, Lehmann, Sune
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Public Library of Science 2017
Materias:
Research Article
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5226832/
https://www.ncbi.nlm.nih.gov/pubmed/28076375
http://dx.doi.org/10.1371/journal.pone.0169901

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5226832/
https://www.ncbi.nlm.nih.gov/pubmed/28076375
http://dx.doi.org/10.1371/journal.pone.0169901

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