Detection of sleep disordered breathing severity using acoustic biomarker and machine learning techniques

PURPOSE: Breathing sounds during sleep are altered and characterized by various acoustic specificities in patients with sleep disordered breathing (SDB). This study aimed to identify acoustic biomarkers indicative of the severity of SDB by analyzing the breathing sounds collected from a large number...

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Detalles Bibliográficos
Autores principales: Kim, Taehoon, Kim, Jeong-Whun, Lee, Kyogu
Formato: Online Artículo Texto
Lenguaje:English
Publicado: BioMed Central 2018
Materias:
Research
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5796501/
https://www.ncbi.nlm.nih.gov/pubmed/29391025
http://dx.doi.org/10.1186/s12938-018-0448-x

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5796501/
https://www.ncbi.nlm.nih.gov/pubmed/29391025
http://dx.doi.org/10.1186/s12938-018-0448-x

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