Classifier Precision Analysis for Sleep Apnea Detection Using ECG Signals

Classifier Precision Analysis for Sleep Apnea Detection Using ECG Signals

This article presents a study on the efficiency of implementing classifiers for the detection of sleep apnea moments based on a minute-to-minute Electrocardiogram (ECG) signal, detailing the comparison of the accuracy for different classifiers. At each ECG signal, a Sgolay filter was applied to extr...

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Bibliographic Details
Main Authors: Nuno Pombo, Bruno M. C. Silva, Andre Miguel Pinho, Nuno Garcia
Format: Article
Language:English
Published: IEEE 2020-01-01
Series:IEEE Access
Subjects:
Sleep apnea
electrocardiogram
feature extraction
feature selection
artificial neural network
support vector machine
Online Access:https://ieeexplore.ieee.org/document/9249043/

Internet

https://ieeexplore.ieee.org/document/9249043/

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