This article presents a review of signals used for measuring physiology and activity during
sleep and techniques for extracting information from these signals. We examine both clinical …

Background: Sleep is essential for human health. Considerable effort has been put into
academic and industrial research and in the development of wireless body area networks for …

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 …

Traditional approaches for obstructive sleep apnea (OSA) diagnosis are apt to using
multiple channels of physiological signals to detect apnea events by dividing the signals into …

EEG Signal Processing and Machine Learning Explore cutting edge techniques at the
forefront of electroencephalogram research and artificial intelligence from leading voices in …

Obstructive sleep apnoea (OSA) is a sleep disorder with long-term consequences. Long-
term effects include sleep-related issues and cardiovascular diseases. OSA is often …

Purpose This study evaluated a novel approach for diagnosis and classification of
obstructive sleep apnea (OSA), called Obstructive Sleep Apnea Smart System (OSASS) …

Tracheal sounds have been the subject of many research studies. In this review, we
describe the state of the art, original work relevant to upper airways obstruction during sleep …

Humans need sleep. It is important for physical and psychological recreation. During sleep
our consciousness is suspended or least altered. Hence, our ability to avoid or react to …