Prediction of the Sleep Apnea Severity Using 2D-Convolutional Neural Networks and Respiratory Effort Signals

Prediction of the Sleep Apnea Severity Using 2D-Convolutional Neural Networks and Respiratory Effort Signals

The high prevalence of sleep apnea and the limitations of polysomnography have prompted the investigation of strategies aimed at automated diagnosis using a restricted number of physiological measures. This study aimed to demonstrate that thoracic (THO) and abdominal (ABD) movement signals are usefu...

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Bibliographic Details
Main Authors: Verónica Barroso-García, Marta Fernández-Poyatos, Benjamín Sahelices, Daniel Álvarez, David Gozal, Roberto Hornero, Gonzalo C. Gutiérrez-Tobal
Format: Article
Language:English
Published: MDPI AG 2023-10-01
Series:Diagnostics
Subjects:
central sleep apnea
obstructive sleep apnea
abdominal respiratory signal
thoracic respiratory signal
convolutional neural network
deep learning
Online Access:https://www.mdpi.com/2075-4418/13/20/3187

Internet

https://www.mdpi.com/2075-4418/13/20/3187

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