AIMC Topic: Sleep Stages

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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 Signal Processing, Computer-Assisted Polysomnography Sleep Stages
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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...
Sensitivity and Specificity Male Middle Aged Algorithms Female Adult Plethysmography Arousal Sleep Stages Deep Learning Sleep Polysomnography Humans
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Enhancing convolutional neural networks in electroencephalogram driver drowsiness detection using human inspired optimizers.

Scientific reports Mar 29, 2025
Driver drowsiness is a significant safety concern, contributing to numerous traffic accidents. To address this issue, researchers have explored electroencephalogram (EEG)-based detection systems. Due to the high-dimensional nature of EEG signals and ...
Sleep Stages Adult Male Deep Learning Electroencephalography Humans Accidents, Traffic Neural Networks, Computer Automobile Driving Algorithms
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Multi-body sensor based drowsiness detection using convolutional programmed transfer VGG-16 neural network with automatic driving mode conversion.

Scientific reports Mar 14, 2025
Many traffic accidents occur nowadays as a result of drivers not paying enough attention or being vigilant. We call this driver sleepiness. This results in numerous unfavourable circumstances that negatively impact people's life. The identification o...
Accidents, Traffic Automobile Driving Sleepiness Sleep Stages Neural Networks, Computer Machine Learning Electroencephalography Humans
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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 ...
Middle Aged Sleep Apnea, Obstructive Polysomnography Female Adult Male Sleep Stages Graph Neural Networks Humans Neural Networks, Computer
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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...
Neural Networks, Computer Female Adult Humans Electroencephalography Male Polysomnography Convolutional Neural Networks 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...
Algorithms Sleep Stages Humans Accidents, Traffic Deep Learning Neural Networks, Computer Image Processing, Computer-Assisted Automobile Driving Face
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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 ...
Event-Related Potentials, P300 Sleep Stages Imagination Humans Female Deep Learning Electroencephalography Adult Brain-Computer Interfaces Male
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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...
Humans Software Deep Learning Electroencephalography Signal Processing, Computer-Assisted Sleep Stages
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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...
Adult Male Deep Learning Algorithms Humans Electroencephalography Sleep Stages Female Neural Networks, Computer Signal Processing, Computer-Assisted Polysomnography
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