AIMC Topic: Sleep Apnea Syndromes

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Apnoea detection using ECG signal based on machine learning classifiers and its performances.

Journal of medical engineering & technology Apr 16, 2024
Sleep apnoea is a common disorder affecting sleep quality by obstructing the respiratory airway. This disorder can also be correlated to certain diseases like stroke, depression, neurocognitive disorder, non-communicable disease, etc. We implemented ...
Sleep Apnea Syndromes Support Vector Machine Signal Processing, Computer-Assisted Algorithms Adult Middle Aged Humans Female Male Electrocardiography Machine Learning
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U-PASS: An uncertainty-guided deep learning pipeline for automated sleep staging.

Computers in biology and medicine Feb 23, 2024
With the increasing prevalence of machine learning in critical fields like healthcare, ensuring the safety and reliability of these systems is crucial. Estimating uncertainty plays a vital role in enhancing reliability by identifying areas of high an...
Reproducibility of Results Aged Humans Sleep Uncertainty Sleep Stages Deep Learning Sleep Apnea Syndromes
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Deep learning of sleep apnea-hypopnea events for accurate classification of obstructive sleep apnea and determination of clinical severity.

Sleep medicine Jan 11, 2024
BACKGROUND: /Objective: Automatic apnea/hypopnea events classification, crucial for clinical applications, often faces challenges, particularly in hypopnea detection. This study aimed to evaluate the efficiency of a combined approach using nasal resp...
Deep Learning Sleep Apnea Syndromes Sleep Apnea, Obstructive Sleep Polysomnography Humans
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Wavelet transform and deep learning-based obstructive sleep apnea detection from single-lead ECG signals.

Physical and engineering sciences in medicine Nov 20, 2023
Sleep apnea is a common sleep disorder. Traditional testing and diagnosis heavily rely on the expertise of physicians, as well as analysis and statistical interpretation of extensive sleep testing data, resulting in time-consuming and labor-intensive...
Electrocardiography Sleep Apnea Syndromes Humans Deep Learning Sleep Apnea, Obstructive Wavelet Analysis
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Sleep Apnea Prediction Using Deep Learning.

IEEE journal of biomedical and health informatics Nov 7, 2023
Obstructive sleep apnea (OSA) is a sleep disorder that causes partial or complete cessation of breathing during an individual's sleep. Various methods have been proposed to automatically detect OSA events, but little work has focused on predicting su...
Humans Deep Learning Sleep Apnea Syndromes Sleep Apnea, Obstructive Respiration Sleep
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Deep learning technique to detect craniofacial anatomical abnormalities concentrated on middle and anterior of face in patients with sleep apnea.

Sleep medicine Sep 24, 2023
OBJECTIVES: The aim of this study is to propose a deep learning-based model using craniofacial photographs for automatic obstructive sleep apnea (OSA) detection and to perform design explainability tests to investigate important craniofacial regions ...
Face Craniofacial Abnormalities Humans Reproducibility of Results Sleep Apnea Syndromes Deep Learning Sleep Apnea, Obstructive
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SelANet: decision-assisting selective sleep apnea detection based on confidence score.

BMC medical informatics and decision making Sep 21, 2023
BACKGROUND: One of the most common sleep disorders is sleep apnea syndrome. To diagnose sleep apnea syndrome, polysomnography is typically used, but it has limitations in terms of labor, cost, and time. Therefore, studies have been conducted to devel...
Algorithms Electrocardiography Sleep Apnea Syndromes Benchmarking Humans Artificial Intelligence
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An explainable deep-learning model to stage sleep states in children and propose novel EEG-related patterns in sleep apnea.

Computers in biology and medicine Aug 31, 2023
Automatic deep-learning models used for sleep scoring in children with obstructive sleep apnea (OSA) are perceived as black boxes, limiting their implementation in clinical settings. Accordingly, we aimed to develop an accurate and interpretable deep...
Humans Sleep Apnea Syndromes Child Artificial Intelligence Sleep Electroencephalography Deep Learning
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A systematic review of deep learning methods for modeling electrocardiograms during sleep.

Physiological measurement Aug 12, 2022
Sleep is one of the most important human physiological activities, and plays an essential role in human health. Polysomnography (PSG) is the gold standard for measuring sleep quality and disorders, but it is time-consuming, labor-intensive, and prone...
Humans Polysomnography Deep Learning Electrocardiography Sleep Apnea Syndromes Sleep
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Accurate contactless sleep apnea detection framework with signal processing and machine learning methods.

Methods (San Diego, Calif.) Jul 1, 2022
The detection of sleep apnea is critical for assessing sleep quality. It is also a proven biometric in diagnosing cardiovascular and other diseases. Recent studies have shown that radar-based non-contact vital sign monitoring system can effectively d...
Humans Sleep Apnea Syndromes Machine Learning Polysomnography Signal Processing, Computer-Assisted
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