AIMC Topic: Sleep Stages

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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 ...
Polysomnography Sleep Stages Graph Neural Networks Neural Networks, Computer Female Adult Male Middle Aged Sleep Apnea, Obstructive Humans
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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 Electroencephalography Adult Female Male Convolutional Neural Networks Polysomnography Sleep Stages
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Joint Driver State Classification Approach: Face Classification Model Development and Facial Feature Analysis Improvement.

Sensors (Basel, Switzerland) Feb 27, 2025
Driver drowsiness remains a critical factor in road safety, necessitating the development of robust detection methodologies. This study presents a dual-framework approach that integrates a convolutional neural network (CNN) and a facial landmark anal...
Sleep Stages Humans Accidents, Traffic Neural Networks, Computer Automobile Driving Algorithms Face Deep Learning Image Processing, Computer-Assisted
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Latent alignment in deep learning models for EEG decoding.

Journal of neural engineering Feb 17, 2025
. Brain-computer interfaces (BCIs) face a significant challenge due to variability in electroencephalography (EEG) signals across individuals. While recent approaches have focused on standardizing input signal distributions, we propose that aligning ...
Sleep Stages Imagination Brain-Computer Interfaces Event-Related Potentials, P300 Humans Male Female Deep Learning Adult Electroencephalography
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PhysioEx: a new Python library for explainable sleep staging through deep learning.

Physiological measurement Feb 10, 2025
Sleep staging is a crucial task in clinical and research contexts for diagnosing and understanding sleep disorders. This work introduces PhysioEx (Physiological Signal Explainer), a Python library designed to support the analysis of sleep stages usin...
Electroencephalography Signal Processing, Computer-Assisted Sleep Stages Humans Software Deep Learning
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WaveSleepNet: An Interpretable Network for Expert-Like Sleep Staging.

IEEE journal of biomedical and health informatics Feb 10, 2025
Although deep learning algorithms have proven their efficiency in automatic sleep staging, their "black-box" nature has limited their clinical adoption. In this study, we propose WaveSleepNet, an interpretable neural network for sleep staging that re...
Humans Neural Networks, Computer Algorithms Male Female Deep Learning Adult Electroencephalography Signal Processing, Computer-Assisted Polysomnography Sleep Stages
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A Multimodal Consistency-Based Self-Supervised Contrastive Learning Framework for Automated Sleep Staging in Patients With Disorders of Consciousness.

IEEE journal of biomedical and health informatics Feb 10, 2025
Sleep is a fundamental human activity, and automated sleep staging holds considerable investigational potential. Despite numerous deep learning methods proposed for sleep staging that exhibit notable performance, several challenges remain unresolved,...
Male Deep Learning Electroencephalography Humans Female Adult Sleep Stages Signal Processing, Computer-Assisted Consciousness Disorders Supervised Machine Learning Electrooculography
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S4Sleep: Elucidating the design space of deep-learning-based sleep stage classification models.

Computers in biology and medicine Feb 3, 2025
Machine-learning-based automatic sleep stage scoring is a promising approach to enhance the time-consuming manual annotation process of polysomnography recordings. Although numerous algorithms have been proposed for this purpose, systematic explorati...
Algorithms Databases, Factual Deep Learning Signal Processing, Computer-Assisted Polysomnography Sleep Stages Humans
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Real-Time Driver Drowsiness Detection Using Facial Analysis and Machine Learning Techniques.

Sensors (Basel, Switzerland) Jan 29, 2025
Drowsy driving poses a significant challenge to road safety worldwide, contributing to thousands of accidents and fatalities annually. Despite advancements in driver drowsiness detection (DDD) systems, many existing methods face limitations such as i...
Accidents, Traffic Machine Learning Sleep Stages Humans Algorithms Automobile Driving Neural Networks, Computer Support Vector Machine Face
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Deep Learning for Pediatric Sleep Staging From Photoplethysmography: A Transfer Learning Approach From Adults to Children.

IEEE transactions on bio-medical engineering Jan 21, 2025
BACKGROUND: Sleep staging is critical for diagnosing sleep disorders. Traditional methods in clinical settings involve time-intensive scoring procedures. Recent advancements in data-driven algorithms using photoplethysmogram (PPG) time series have sh...
Deep Learning Sleep Stages Photoplethysmography Child, Preschool Humans Female Child Signal Processing, Computer-Assisted Algorithms Adult Polysomnography Male
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