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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...
Autores principales: | Tsinalis, Orestis, Matthews, Paul M., Guo, Yike |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Springer US
2015
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Materias: | |
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 |
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