Obstructive Sleep Apnea Detection Based on Sleep Sounds via Deep Learning

PURPOSE: This study aimed to propose a novel deep-learning method for automatic sleep apneic event detection and thus to estimate the apnea hypopnea index (AHI) and identify obstructive sleep apnea (OSA) in an event-by-event manner solely based on sleep sounds obtained by a noncontact audio recorder...

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Detalles Bibliográficos
Autores principales: Wang, Bochun, Tang, Xianwen, Ai, Hao, Li, Yanru, Xu, Wen, Wang, Xingjun, Han, Demin
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Dove 2022
Materias:
Original Research
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9653035/
https://www.ncbi.nlm.nih.gov/pubmed/36394068
http://dx.doi.org/10.2147/NSS.S373367

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9653035/
https://www.ncbi.nlm.nih.gov/pubmed/36394068
http://dx.doi.org/10.2147/NSS.S373367

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