Sleep apnea is a sleep related disorder that significantly affects the population.
Polysomnography, the gold standard, is expensive, inaccessible, uncomfortable and an …

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 …

Abstract Background and Objective This study demonstrates deep learning approaches with
an aim to find the optimal method to automatically detect sleep apnea (SA) events from an …

In this study, we propose a method for the automated detection of obstructive sleep apnea
(OSA) from a single-lead electrocardiogram (ECG) using a convolutional neural network …

Objective: In this paper, we propose a convolutional neural network (CNN)-based deep
learning architecture for multiclass classification of obstructive sleep apnea and hypopnea …

While public awareness of sleep related disorders is growing, sleep apnea syndrome (SAS)
remains a public health and economic challenge. Over the last two decades, extensive …

Abstract The prediction of Obstructive Sleep Apnea (OSA) through common
polysomnographic signals before stop breathing triggers the ventilation-aided machines …

The study of sleep stages and the associated signals have emerged as a very important
parameter to identify the neurological disorders and test of mental activities nowadays …

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 …

Sleep apnea syndrome (SAS) is prevalent in individuals and recently, there are many
studies focus on using simple and efficient methods for SAS detection instead of …