A Deep Learning Framework for Automatic Sleep Apnea Classification Based on Empirical Mode Decomposition Derived from Single-Lead Electrocardiogram

Background: Although polysomnography (PSG) is a gold standard tool for diagnosing sleep apnea (SA), it can reduce the patient’s sleep quality by the placement of several disturbing sensors and can only be interpreted by a highly trained sleep technician or scientist. In recent years, electrocardiogr...

Descripción completa

Detalles Bibliográficos
Autores principales: Setiawan, Febryan, Lin, Che-Wei
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2022
Materias:
Article
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9605343/
https://www.ncbi.nlm.nih.gov/pubmed/36294943
http://dx.doi.org/10.3390/life12101509

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9605343/
https://www.ncbi.nlm.nih.gov/pubmed/36294943
http://dx.doi.org/10.3390/life12101509

Ejemplares similares