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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Autores:

Tipo de recurso:

Fecha de publicación:

2015

Institución:

Universidad del Rosario

Repositorio:

Repositorio EdocUR - U. Rosario

Idioma:

eng

OAI Identifier:

oai:repository.urosario.edu.co:10336/27664

Acceso en línea:

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

Palabra clave:

Electrocardiography
Sleep apnea
Heart rate
Morphology
Principal component analysis
Feature extraction
Eigenvalues and eigenfunctions

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