Sleep stage classification from heart-rate variability using long short-term memory neural networks

Automated sleep stage classification using heart rate variability (HRV) may provide an ergonomic and low-cost alternative to gold standard polysomnography, creating possibilities for unobtrusive home-based sleep monitoring. Current methods however are limited in their ability to take into account lo...

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Detalles Bibliográficos
Autores principales: Radha, Mustafa, Fonseca, Pedro, Moreau, Arnaud, Ross, Marco, Cerny, Andreas, Anderer, Peter, Long, Xi, Aarts, Ronald M.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Nature Publishing Group UK 2019
Materias:
Article
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6775145/
https://www.ncbi.nlm.nih.gov/pubmed/31578345
http://dx.doi.org/10.1038/s41598-019-49703-y

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6775145/
https://www.ncbi.nlm.nih.gov/pubmed/31578345
http://dx.doi.org/10.1038/s41598-019-49703-y

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