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Recurrent Deep Neural Networks for Real-Time Sleep Stage Classification From Single Channel EEG
Objective: We investigate the design of deep recurrent neural networks for detecting sleep stages from single channel EEG signals recorded at home by non-expert users. We report the effect of data set size, architecture choices, regularization, and personalization on the classification performance....
| Autores principales: | , , |
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| Formato: | Online Artículo Texto |
| Lenguaje: | English |
| Publicado: |
Frontiers Media S.A.
2018
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| Materias: | |
| Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6198094/ https://www.ncbi.nlm.nih.gov/pubmed/30386226 http://dx.doi.org/10.3389/fncom.2018.00085 |