Citation

Bragazzi NL, Guglielmi O, Garbarino AS. Int. J. Environ. Res. Public Health 2019; 16(2): e16020291.

Affiliation

Department of Neuroscience, Rehabilitation, Ophthalmology, Genetics, Maternal and Child Health (DINOGMI), Genoa University, 16132 Genoa, Italy. sgarbarino.neuro@gmail.com.

Copyright

(Copyright © 2019, MDPI: Multidisciplinary Digital Publishing Institute)

DOI

10.3390/ijerph16020291

PMID

30669659

Abstract

Sleep disorders have reached epidemic proportions worldwide, affecting the youth as well as the elderly, crossing the entire lifespan in both developed and developing countries. "Real-life" behavioral (sensor-based), molecular, digital, and epidemiological big data represent a source of an impressive wealth of information that can be exploited in order to advance the field of sleep research. It can be anticipated that big data will have a profound impact, potentially enabling the dissection of differences and oscillations in sleep dynamics and architecture at the individual level ("sleepOMICS"), thus paving the way for a targeted, "one-size-does-not-fit-all" management of sleep disorders ("precision sleep medicine").

Language: en

Keywords

OMICS sciences; behavioral informatics; big data; connectomics; infodemiology; infoveillance; personalized sleep medicine; precision sleep medicine; sleep; sleep disorders; wearable sensors