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A novel algorithm for the automatic detection of sleep apnea from single-lead ECG

Goal: This paper presents a methodology for the automatic detection of sleep apnea from single-lead ECG. Methods: It uses two novel features derived from the ECG, and two well-known features in heart rate variability analysis, namely the standard deviation and the serial correlation coefficients of...

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Detalles Bibliográficos
Autores Principales: Varon, Carolina, Caicedo, Alexander, Testelmans, Dries, Buyse, Bertien, Van Huffel, Sabine
Formato: Artículo (Article)
Lenguaje:Inglés (English)
Publicado: IEEE 2015
Materias:
Electrocardiography
Sleep apnea
Heart rate
Morphology
Principal component analysis
Feature extraction
Eigenvalues and eigenfunctions
Acceso en línea:https://repository.urosario.edu.co/handle/10336/27664
https://doi.org/10.1109/TBME.2015.2422378

Internet

https://repository.urosario.edu.co/handle/10336/27664
https://doi.org/10.1109/TBME.2015.2422378

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