A systematic review of detecting sleep apnea using deep learning
Sleep apnea is a sleep related disorder that significantly affects the population.
Polysomnography, the gold standard, is expensive, inaccessible, uncomfortable and an …
Polysomnography, the gold standard, is expensive, inaccessible, uncomfortable and an …
Classification methods to detect sleep apnea in adults based on respiratory and oximetry signals: a systematic review
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 …
quality of life, and is closely associated with major health risks such as cardiovascular …
Deep learning approaches for automatic detection of sleep apnea events from an electrocardiogram
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 …
an aim to find the optimal method to automatically detect sleep apnea (SA) events from an …
Automated detection of obstructive sleep apnea events from a single-lead electrocardiogram using a convolutional neural network
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 …
(OSA) from a single-lead electrocardiogram (ECG) using a convolutional neural network …
Multiclass classification of obstructive sleep apnea/hypopnea based on a convolutional neural network from a single-lead electrocardiogram
Objective: In this paper, we propose a convolutional neural network (CNN)-based deep
learning architecture for multiclass classification of obstructive sleep apnea and hypopnea …
learning architecture for multiclass classification of obstructive sleep apnea and hypopnea …
Sleep apnea: a review of diagnostic sensors, algorithms, and therapies
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 …
remains a public health and economic challenge. Over the last two decades, extensive …
Obstructive sleep apnea event prediction using recurrence plots and convolutional neural networks (RP-CNNs) from polysomnographic signals
Abstract The prediction of Obstructive Sleep Apnea (OSA) through common
polysomnographic signals before stop breathing triggers the ventilation-aided machines …
polysomnographic signals before stop breathing triggers the ventilation-aided machines …
A fuzzy neural network approach for automatic K-complex detection in sleep EEG signal
R Ranjan, R Arya, SL Fernandes, E Sravya… - Pattern Recognition …, 2018 - Elsevier
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 …
parameter to identify the neurological disorders and test of mental activities nowadays …
Classification techniques on computerized systems to predict and/or to detect Apnea: A systematic review
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 …
the quality of life is associated with a major risk factor of health implications such as …
Automatic detection of sleep apnea based on EEG detrended fluctuation analysis and support vector machine
J Zhou, X Wu, W Zeng - Journal of clinical monitoring and computing, 2015 - Springer
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 …
studies focus on using simple and efficient methods for SAS detection instead of …