Cargando…
Ambulatory sleep scoring using accelerometers—distinguishing between nonwear and sleep/wake states
BACKGROUND: Differentiating nonwear time from sleep and wake times is essential for the estimation of sleep duration based on actigraphy data. To efficiently analyze large-scale data sets, an automatic method of identifying these three different states is required. Therefore, we developed a classifi...
Autores principales: | Barouni, Amna, Ottenbacher, Jörg, Schneider, Johannes, Feige, Bernd, Riemann, Dieter, Herlan, Anne, El Hardouz, Driss, McLennan, Darren |
---|---|
Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
PeerJ Inc.
2020
|
Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6942683/ https://www.ncbi.nlm.nih.gov/pubmed/31915581 http://dx.doi.org/10.7717/peerj.8284 |
Ejemplares similares
-
Identifying accelerometer nonwear and wear time in older adults
por: Hutto, Brent, et al.
Publicado: (2013) -
Imputing accelerometer nonwear time in children influences estimates of sedentary time and its associations with cardiometabolic risk
por: Borghese, M. M., et al.
Publicado: (2019) -
Decreased electrocortical temporal complexity distinguishes sleep from wakefulness
por: González, Joaquín, et al.
Publicado: (2019) -
Nonwearable Gaze Tracking System for Controlling Home Appliance
por: Heo, Hwan, et al.
Publicado: (2014) -
Potential corner case cautions regarding publicly available implementations of the National Cancer Institute’s nonwear/wear classification algorithm for accelerometer data
por: Moore, Hyatt E., et al.
Publicado: (2018)