An Automatic Sleep Stage Classification Algorithm Using Improved Model Based Essence Features

The automatic sleep stage classification technique can facilitate the diagnosis of sleep disorders and release the medical expert from labor-consumption work. In this paper, novel improved model based essence features (IMBEFs) were proposed combining locality energy (LE) and dual state space models...

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Detalles Bibliográficos
Autores principales: Shen, Huaming, Ran, Feng, Xu, Meihua, Guez, Allon, Li, Ang, Guo, Aiying
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2020
Materias:
Article
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7506989/
https://www.ncbi.nlm.nih.gov/pubmed/32825024
http://dx.doi.org/10.3390/s20174677

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7506989/
https://www.ncbi.nlm.nih.gov/pubmed/32825024
http://dx.doi.org/10.3390/s20174677

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