Automatic Sleep Stage Scoring Using Time-Frequency Analysis and Stacked Sparse Autoencoders

We developed a machine learning methodology for automatic sleep stage scoring. Our time-frequency analysis-based feature extraction is fine-tuned to capture sleep stage-specific signal features as described in the American Academy of Sleep Medicine manual that the human experts follow. We used ensem...

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Detalles Bibliográficos
Autores principales: Tsinalis, Orestis, Matthews, Paul M., Guo, Yike
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Springer US 2015
Materias:
Article
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4837220/
https://www.ncbi.nlm.nih.gov/pubmed/26464268
http://dx.doi.org/10.1007/s10439-015-1444-y

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4837220/
https://www.ncbi.nlm.nih.gov/pubmed/26464268
http://dx.doi.org/10.1007/s10439-015-1444-y

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