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Sleep Apnea Syndromes

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Automated detection of sleep apnea using sparse residual entropy features with various dictionaries extracted from heart rate and EDR signals.

Computers in biology and medicine
Sleep is a prominent physiological activity in our daily life. Sleep apnea is the category of sleep disorder during which the breathing of the person diminishes causing the alternation in the upper airway resistance. The electrocardiogram derived res...

A RR interval based automated apnea detection approach using residual network.

Computer methods and programs in biomedicine
BACKGROUND AND OBJECTIVE: Apnea is one of the most common conditions that causes sleep-disorder breathing. With growing number of patients worldwide, more and more patients suffer from complications of apnea. But most of them stay untreated due to th...

Convolutional Neural Networks to Detect Pediatric Apnea-Hypopnea Events from Oximetry.

Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference
Pediatric sleep apnea-hypopnea syndrome (SAHS) is a highly prevalent breathing disorder that is related to many negative consequences for the children's health and quality of life when it remains untreated. The gold standard for pediatric SAHS diagno...

Sleep Apnea Severity Estimation from Respiratory Related Movements Using Deep Learning.

Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference
Sleep apnea is a common chronic respiratory disorder which occurs due to the repetitive complete or partial cessations of breathing during sleep. The gold standard assessment of sleep apnea requires full night polysomnography in a sleep laboratory wh...

Deep learning approaches for automatic detection of sleep apnea events from an electrocardiogram.

Computer methods and programs in biomedicine
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 electrocardiogram (ECG) signal.

Tracheal Sound Analysis Using a Deep Neural Network to Detect Sleep Apnea.

Journal of clinical sleep medicine : JCSM : official publication of the American Academy of Sleep Medicine
STUDY OBJECTIVES: Portable devices for home sleep apnea testing are often limited by their inability to discriminate sleep/wake status, possibly resulting in underestimations. Tracheal sound (TS), which can be visualized as a spectrogram, carries inf...

Artificial neural network analysis of the oxygen saturation signal enables accurate diagnostics of sleep apnea.

Scientific reports
The severity of obstructive sleep apnea (OSA) is classified using apnea-hypopnea index (AHI). Accurate determination of AHI currently requires manual analysis and complicated registration setup making it expensive and labor intensive. Partially for t...

[VOTE versus ACLTE: comparison of two snoring noise classifications using machine learning methods].

HNO
BACKGROUND: Acoustic snoring sound analysis is a noninvasive method for diagnosis of the mechanical mechanisms causing snoring that can be performed during natural sleep. The objective of this work is development and evaluation of classification sche...

A hierarchical sequential neural network with feature fusion for sleep staging based on EOG and RR signals.

Journal of neural engineering
OBJECTIVE: Currently, the automatic sleep staging methods mainly face two problems: the first problem is that although the algorithms which use electroencephalogram (EEG) signals perform well, acquiring EEG signals is complicated and uncomfortable; t...

A Systematic Review of Detecting Sleep Apnea Using Deep Learning.

Sensors (Basel, Switzerland)
Sleep apnea is a sleep related disorder that significantly affects the population. Polysomnography, the gold standard, is expensive, inaccessible, uncomfortable and an expert technician is needed to score. Numerous researchers have proposed and imple...