AIMC Topic: Sleep Apnea Syndromes
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A multimodal dataset for training deep learning models aimed at detecting and analyzing sleep apnea.
Scientific data
Jul 18, 2025
Sleep Apnea Syndrome (SAS) is a serious respiratory disorder that can lead to a range of complications, including hypertension, arrhythmias, cognitive impair- ment, and metabolic disturbances. Due to the insidious nature of its symptoms, patients oft...
ModelS4Apnea: leveraging structured state space models for efficient sleep apnea detection from ECG signals.
Physiological measurement
Jul 11, 2025
. Sleep apnea is a common sleep disorder associated with severe health risks, necessitating accurate and efficient detection methods.. This study proposes ModelS4Apnea, a deep learning framework for sleep apnea detection from electrocardiogram (ECG) ...
Robust performances of a nocturnal long-term ECG algorithm for the evaluation of sleep apnea syndrome: A pilot study.
PloS one
May 16, 2025
Obstructive sleep apnea-hypopnea syndrome (OSAHS) is one of the most common sleep disorders affecting nearly one billion of the global adult population, making it a major public health issue. Even if in-lab polysomnography (PSG) remains the gold stan...
Intermittent hypoxemia during hemodialysis: AI-based identification of arterial oxygen saturation saw-tooth pattern.
BMC nephrology
Apr 28, 2025
BACKGROUND: Maintenance hemodialysis patients experience high morbidity and mortality, primarily from cardiovascular and infectious diseases. It was discovered recently that low arterial oxygen saturation (SaO) is associated with a pro-inflammatory p...
Clinical-level screening of sleep apnea syndrome with single-lead ECG alone is achievable using machine learning with appropriate time windows.
Sleep & breathing = Schlaf & Atmung
Apr 11, 2025
PURPOSE: To establish a simple and noninvasive screening test for sleep apnea (SA) that imposes less burden on potential patients. The specific objective of this study was to verify the effectiveness of past and future single-lead electrocardiogram (...
Distinguishing severe sleep apnea from habitual snoring using a neck-wearable piezoelectric sensor and deep learning: A pilot study.
Computers in biology and medicine
Mar 26, 2025
This study explores the development of a deep learning model using a neck-wearable piezoelectric sensor to accurately distinguish severe sleep apnea syndrome (SAS) from habitual snoring, addressing the underdiagnosis of SAS in adults. From 2018 to 20...
Deep Learning-Based Event Counting for Apnea-Hypopnea Index Estimation Using Recursive Spiking Neural Networks.
IEEE transactions on bio-medical engineering
Mar 21, 2025
OBJECTIVE: To develop a novel method for improved screening of sleep apnea in home environments, focusing on reliable estimation of the Apnea-Hypopnea Index (AHI) without the need for highly precise event localization.
SleepECG-Net: Explainable Deep Learning Approach With ECG for Pediatric Sleep Apnea Diagnosis.
IEEE journal of biomedical and health informatics
Feb 10, 2025
Obstructive sleep apnea (OSA) in children is a prevalent and serious respiratory condition linked to cardiovascular morbidity. Polysomnography, the standard diagnostic approach, faces challenges in accessibility and complexity, leading to underdiagno...
Explainable AI-driven scalogram analysis and optimized transfer learning for sleep apnea detection with single-lead electrocardiograms.
Computers in biology and medicine
Feb 8, 2025
Sleep apnea, a fatal sleep disorder causing repetitive respiratory cessation, requires immediate intervention due to neuropsychological issues. However, existing approaches such as polysomnography, considered the most reliable and accurate test to de...
Detection of sleep apnea using only inertial measurement unit signals from apple watch: a pilot-study with machine learning approach.
Sleep & breathing = Schlaf & Atmung
Feb 1, 2025
PURPOSE: Despite increased awareness of sleep hygiene, over 80% of sleep apnea cases remain undiagnosed, underscoring the need for accessible screening methods. This study presents a method for detecting sleep apnea using data from the Apple Watch's ...
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