AIMC Topic: Polysomnography

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Artificial intelligence in obstructive sleep apnea: Transforming diagnosis and management.

Respiratory medicine Apr 15, 2025
Obstructive Sleep Apnea (OSA) is a common disorder characterized by repeated airway collapse during sleep, leading to significant health risks. The traditional diagnosis of OSA through polysomnography is resource-intensive, leading to delays in diagn...
Polysomnography Humans Artificial Intelligence Sleep Apnea, Obstructive
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Towards interpretable sleep stage classification with a multi-stream fusion network.

BMC medical informatics and decision making Apr 14, 2025
Sleep stage classification is a significant measure in assessing sleep quality and diagnosing sleep disorders. Many researchers have investigated automatic sleep stage classification methods and achieved promising results. However, these methods igno...
Humans Neural Networks, Computer Sleep Stages Signal Processing, Computer-Assisted Polysomnography
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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 (...
Electrocardiography Sleep Apnea Syndromes Polysomnography Sensitivity and Specificity Male Middle Aged Machine Learning Female Adult Humans
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Detecting arousals and sleep from respiratory inductance plethysmography.

Sleep & breathing = Schlaf & Atmung Apr 11, 2025
PURPOSE: Accurately identifying sleep states (REM, NREM, and Wake) and brief awakenings (arousals) is essential for diagnosing sleep disorders. Polysomnography (PSG) is the gold standard for such assessments but is costly and requires overnight monit...
Middle Aged Deep Learning Sleep Adult Sensitivity and Specificity Male Sleep Stages Polysomnography Plethysmography Arousal Humans Algorithms Female
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CHMMConvScaleNet: a hybrid convolutional neural network and continuous hidden Markov model with multi-scale features for sleep posture detection.

Scientific reports Apr 10, 2025
Sleep posture, a vital aspect of sleep wellness, has become a crucial focus in sleep medicine. Studies show that supine posture can lead to a higher occurrence of obstructive sleep apnea, while lateral posture might reduce it. For bedridden patients,...
Humans Neural Networks, Computer Sleep Polysomnography Hidden Markov Models Convolutional Neural Networks Posture Markov Chains Female Adult Male
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Separating obstructive and central respiratory events during sleep using breathing sounds: Utilizing transfer learning on deep convolutional networks.

Sleep medicine Mar 29, 2025
Sleep apnea diagnosis relies on polysomnography (PSG), which is resource-intensive and requires manual analysis to differentiate obstructive sleep apnea (OSA) from central sleep apnea (CSA). Existing portable devices, while valuable in detecting slee...
Female Adult Sensitivity and Specificity Humans Neural Networks, Computer Sleep Apnea, Obstructive Polysomnography Male Middle Aged Deep Learning Respiratory Sounds Sleep Apnea, Central
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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...
Polysomnography Deep Learning Adult Pilot Projects Humans Neck Male Wearable Electronic Devices Female Sleep Apnea Syndromes Middle Aged Aged Snoring
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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.
Algorithms Female Adult Humans Neural Networks, Computer Male Signal Processing, Computer-Assisted Middle Aged Sleep Apnea Syndromes Deep Learning Polysomnography
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GraphSleepFormer: a multi-modal graph neural network for sleep staging in OSA patients.

Journal of neural engineering Mar 11, 2025
Obstructive sleep apnea (OSA) is a prevalent sleep disorder. Accurate sleep staging is one of the prerequisites in the study of sleep-related disorders and the evaluation of sleep quality. We introduce a novel GraphSleepFormer (GSF) network designed ...
Sleep Apnea, Obstructive Polysomnography Sleep Stages Graph Neural Networks Adult Male Middle Aged Humans Neural Networks, Computer Female
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Explainable multiscale temporal convolutional neural network model for sleep stage detection based on electroencephalogram activities.

Journal of neural engineering Mar 7, 2025
Humans spend a significant portion of their lives in sleep (an essential driver of body metabolism). Moreover, as sleep deprivation could cause various health complications, it is crucial to develop an automatic sleep stage detection model to facilit...
Humans Neural Networks, Computer Sleep Stages Convolutional Neural Networks Electroencephalography Polysomnography Female Adult Male
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