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Deep Recurrent Neural Networks for Automatic Detection of Sleep Apnea from Single Channel Respiration Signals
Sleep apnea is a common sleep disorder that causes repeated breathing interruption during sleep. The performance of automated apnea detection methods based on respiratory signals depend on the signals considered and feature extraction methods. Moreover, feature engineering techniques are highly depe...
| Autores principales: | , , , , |
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| Formato: | Online Artículo Texto |
| Lenguaje: | English |
| Publicado: |
MDPI
2020
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| Materias: | |
| Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7570636/ https://www.ncbi.nlm.nih.gov/pubmed/32899819 http://dx.doi.org/10.3390/s20185037 |