Machine‐learning‐derived sleep–wake staging from around‐the‐ear electroencephalogram outperforms manual scoring and actigraphy

Quantification of sleep is important for the diagnosis of sleep disorders and sleep research. However, the only widely accepted method to obtain sleep staging is by visual analysis of polysomnography (PSG), which is expensive and time consuming. Here, we investigate automated sleep scoring based on...

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Detalles Bibliográficos
Autores principales: Mikkelsen, Kaare B., Ebajemito, James K., Bonmati‐Carrion, Maria A., Santhi, Nayantara, Revell, Victoria L., Atzori, Giuseppe, della Monica, Ciro, Debener, Stefan, Dijk, Derk‐Jan, Sterr, Annette, de Vos, Maarten
Formato: Online Artículo Texto
Lenguaje:English
Publicado: John Wiley and Sons Inc. 2018
Materias:
Methods in Sleep Research and Sleep Medicine
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6446944/
https://www.ncbi.nlm.nih.gov/pubmed/30421469
http://dx.doi.org/10.1111/jsr.12786

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6446944/
https://www.ncbi.nlm.nih.gov/pubmed/30421469
http://dx.doi.org/10.1111/jsr.12786

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