Prediction of obstructive sleep apnea using ensemble of recurrence plot convolutional neural networks (RPCNNs) from polysomnography signals

Y Taghizadegan, NJ Dabanloo, K Maghooli… - Medical hypotheses, 2021 - Elsevier
Abstract Obstructive Sleep Apnea (OSA) is a common disorder characterized by periodic
cessation of breathing during sleep. OSA affects daily life and poses a severe threat to …

Obstructive sleep apnea event prediction using recurrence plots and convolutional neural networks (RP-CNNs) from polysomnographic signals

Y Taghizadegan, NJ Dabanloo, K Maghooli… - … Signal Processing and …, 2021 - Elsevier
Abstract The prediction of Obstructive Sleep Apnea (OSA) through common
polysomnographic signals before stop breathing triggers the ventilation-aided machines …

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

V Barroso-García, M Fernández-Poyatos, B Sahelices… - Diagnostics, 2023 - mdpi.com
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 …

Deep-Learning Model Based on Convolutional Neural Networks to Classify Apnea–Hypopnea Events from the Oximetry Signal

F Vaquerizo-Villar, D Álvarez… - Advances in the …, 2022 - Springer
Automated analysis of the blood oxygen saturation (SpO2) signal from nocturnal oximetry
has shown usefulness to simplify the diagnosis of obstructive sleep apnea (OSA), including …

A novel deep learning model for obstructive sleep apnea diagnosis: hybrid CNN-Transformer approach for radar-based detection of apnea-hypopnea events

JW Choi, DL Koo, DH Kim, H Nam, JH Lee, SN Hong… - Sleep, 2024 - academic.oup.com
Abstract Study Objectives The demand for cost-effective and accessible alternatives to
polysomnography (PSG), the conventional diagnostic method for obstructive sleep apnea …

Sleep apnea event prediction using convolutional neural networks and Markov chains

R Haidar, I Koprinska, B Jeffries - 2020 International Joint …, 2020 - ieeexplore.ieee.org
Obstructive sleep apnea is a breathing disorder affecting 2-4% of the adult population. It is
characterized by periods of reduced breathing (hypopnea) or no breathing (apnea). Several …

[PDF][PDF] Convolutional neural networks based OSA event prediction from ECG scalograms and spectrograms

H Nasifoglu, O Erogul - 2021 - scholar.archive.org
In this study, we conducted a comparative analysis of deep convolutional neural network
(CNN) models in predicting Obstructive Sleep Apnea (OSA) using electrocardiograms …

Real-time apnea-hypopnea event detection during sleep by convolutional neural networks

SH Choi, H Yoon, HS Kim, HB Kim, HB Kwon… - Computers in biology …, 2018 - Elsevier
Sleep apnea-hypopnea event detection has been widely studied using various biosignals
and algorithms. However, most minute-by-minute analysis techniques have difficulty …

Predicting Obstructive Sleep Apnea Based on Computed Tomography Scan Using Deep Learning Models

JW Kim, K Lee, HJ Kim, HC Park, JY Hwang… - American Journal of …, 2024 - atsjournals.org
Rationale: The incidence of clinically undiagnosed obstructive sleep apnea (OSA) is high
among the general population due to limited access to polysomnography. Computed …

Deep learning for diagnosis and classification of obstructive sleep apnea: A nasal airflow-based multi-resolution residual network

H Yue, Y Lin, Y Wu, Y Wang, Y Li, X Guo… - Nature and Science …, 2021 - Taylor & Francis
Purpose This study evaluated a novel approach for diagnosis and classification of
obstructive sleep apnea (OSA), called Obstructive Sleep Apnea Smart System (OSASS) …