AIMC Topic: Sleep Apnea Syndromes
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Automatic detection of sleep apnea based on EEG detrended fluctuation analysis and support vector machine.
Journal of clinical monitoring and computing
Feb 8, 2015
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 polysomnography. However, not much work has been done on using nonlinear behavior of ...
Diagnostic accuracy of machine learning algorithms in electrocardiogram-based sleep apnea detection: A systematic review and meta-analysis.
Sleep medicine reviews
Jun 1, 2025
Sleep apnea is a prevalent disorder affecting 10 % of middle-aged individuals, yet it remains underdiagnosed due to the limitations of polysomnography (PSG), the current diagnostic gold standard. Single-lead electrocardiography (ECG) has been propose...
Wearable Sensors and Artificial Intelligence for Sleep Apnea Detection: A Systematic Review.
Journal of medical systems
May 19, 2025
Sleep apnea, a prevalent disorder affecting millions of people worldwide, has attracted increasing attention in recent years due to its significant impact on public health and quality of life. The integration of wearable devices and artificial intell...
Validation of a fingertip home sleep apnea testing system using deep learning AI and a temporal event localization analysis.
Sleep
May 12, 2025
STUDY OBJECTIVES: This paper validates TipTraQ, a compact home sleep apnea testing (HSAT) system. TipTraQ comprises a fingertip-worn device, a mobile application, and a cloud-based deep learning artificial intelligence (AI) system. The device utilize...
What radio waves tell us about sleep!
Sleep
Jan 13, 2025
The ability to assess sleep at home, capture sleep stages, and detect the occurrence of apnea (without on-body sensors) simply by analyzing the radio waves bouncing off people's bodies while they sleep is quite powerful. Such a capability would allow...
A deep learning model based on the combination of convolutional and recurrent neural networks to enhance pulse oximetry ability to classify sleep stages in children with sleep apnea.
Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference
Jul 1, 2023
Characterization of sleep stages is essential in the diagnosis of sleep-related disorders but relies on manual scoring of overnight polysomnography (PSG) recordings, which is onerous and labor-intensive. Accordingly, we aimed to develop an accurate d...
Deep-Learning based Sleep Apnea Detection using SpO2 and Pulse Rate.
Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference
Jul 1, 2022
This work presents automated apnea event de-tection using blood oxygen saturation (SpO2) and pulse rate (PR), conveniently recorded with a pulse oximeter. A large, diverse cohort of patients (n=8068, age≥40 years) from the sleep heart health study da...
Deep-Learning Model Based on Convolutional Neural Networks to Classify Apnea-Hypopnea Events from the Oximetry Signal.
Advances in experimental medicine and biology
Jan 1, 2022
Automated analysis of the blood oxygen saturation (SpO) signal from nocturnal oximetry has shown usefulness to simplify the diagnosis of obstructive sleep apnea (OSA), including the detection of respiratory events. However, the few preceding studies ...
Machine Learning-based Sleep Staging in Patients with Sleep Apnea Using a Single Mandibular Movement Signal.
American journal of respiratory and critical care medicine
Nov 15, 2021
SomnNET: An SpO2 Based Deep Learning Network for Sleep Apnea Detection in Smartwatches.
Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference
Nov 1, 2021
The abnormal pause or rate reduction in breathing is known as the sleep-apnea hypopnea syndrome and affects the quality of sleep of an individual. A novel method for the detection of sleep apnea events (pause in breathing) from peripheral oxygen satu...
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