Feature ranking and rank aggregation for automatic sleep stage classification: a comparative study.

Background: Nowadays, sleep quality is one of the most important measures of healthy life, especially considering the huge number of sleep-related disorders. Identifying sleep stages using polysomnographic (PSG) signals is the traditional way of assessing sleep quality. However, the manual process o...

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Detalles Bibliográficos
Publicado en:BioMedical Engineering OnLine Vol. 16; pp. 1 - 20
Autores principales: Najdi, Shirin, Gharbali, Ali, Fonseca, José, Gharbali, Ali Abdollahi, Fonseca, José Manuel
Formato: research Journal Article
Publicado: BioMed Central 2017 Supplement
Acceso en línea:Ver este registro en EBSCOhost