Classification methods to detect sleep apnea in adults based on respiratory and oximetry signals: a systematic review

MB Uddin, CM Chow, SW Su - Physiological measurement, 2018 - iopscience.iop.org
Objective: Sleep apnea (SA), a common sleep disorder, can significantly decrease the
quality of life, and is closely associated with major health risks such as cardiovascular …

Classification techniques on computerized systems to predict and/or to detect Apnea: A systematic review

N Pombo, N Garcia, K Bousson - Computer methods and programs in …, 2017 - Elsevier
Background and objective Sleep apnea syndrome (SAS), which can significantly decrease
the quality of life is associated with a major risk factor of health implications such as …

An intelligent sleep apnea classification system based on EEG signals

V Vimala, K Ramar, M Ettappan - Journal of medical systems, 2019 - Springer
Sleep Apnea is a sleep disorder which causes stop in breathing for a short duration of time
that happens to human beings and animals during sleep. Electroencephalogram (EEG) …

Predictive power of XGBoost_BiLSTM model: a machine-learning approach for accurate sleep apnea detection using electronic health data

A Javeed, JS Berglund, AL Dallora, MA Saleem… - International Journal of …, 2023 - Springer
Sleep apnea is a common disorder that can cause pauses in breathing and can last from a
few seconds to several minutes, as well as shallow breathing or complete cessation of …

Sleep apnea detection based on ECG signals using discrete wavelet transform and artificial neural network

M Qatmh, T Bonny, F Barneih… - 2022 Advances in …, 2022 - ieeexplore.ieee.org
Sleep apnea is a sleep disorder that can cause serious health problems. An Artificial Neural
Network classifier to detect sleep apnea has been presented in this paper by utilizing the …

Computer‐assisted diagnosis of the sleep apnea‐hypopnea syndrome: a review

D Alvarez-Estevez, V Moret-Bonillo - Sleep disorders, 2015 - Wiley Online Library
Automatic diagnosis of the Sleep Apnea‐Hypopnea Syndrome (SAHS) has become an
important area of research due to the growing interest in the field of sleep medicine and the …

Sleep apnea detection from ECG signal using deep CNN-based structures

A Ayatollahi, S Afrakhteh, F Soltani, E Saleh - Evolving Systems, 2023 - Springer
In this paper, transfer learning is used for the adaptation of pre-trained deep convolutional
neural networks (DCNNs) to find the best appropriate method for the classification of …

Speed and Accuracy Trade-off ANN/SVM Based Sleep Apnea Detection with FPGA Implementation

T Bonny, M Qatmh, K Obaideen… - Computer Methods in …, 2023 - Taylor & Francis
During sleep, some people experience breathing difficulties, leading to a condition known
as sleep apnoea, which can result in suffocation. This study focuses on detecting sleep …

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 …

Usefulness of artificial neural networks in the diagnosis and treatment of sleep apnea-hypopnea syndrome

D Álvarez, A Cerezo-Hernández… - Sleep Apnea-Recent …, 2017 - books.google.com
Sleep apnea-hypopnea syndrome (SAHS) is a chronic and highly prevalent disease
considered a major health problem in industrialized countries. The gold standard diagnostic …