AIMC Topic: Sleep Stages

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The utility of automated measures of ocular metrics for detecting driver drowsiness during extended wakefulness.

Accident; analysis and prevention Dec 10, 2015
Slowed eyelid closure coupled with increased duration and frequency of closure is associated with drowsiness. This study assessed the utility of two devices for automated measurement of slow eyelid closure in a standard poor performance condition (al...
Sleep Stages Blinking Electrooculography Young Adult Wakefulness Sleep Deprivation Adolescent Adult Alcohol Drinking Signal Processing, Computer-Assisted Humans Male Attention Reaction Time Computer Simulation Automobile Driving Female
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Validation of non-REM sleep stage decoding from resting state fMRI using linear support vector machines.

NeuroImage Oct 24, 2015
A growing body of literature suggests that changes in consciousness are reflected in specific connectivity patterns of the brain as obtained from resting state fMRI (rs-fMRI). As simultaneous electroencephalography (EEG) is often unavailable, decodin...
Wakefulness Rest Sleep Stages Magnetic Resonance Imaging Brain Brain Mapping Female Electroencephalography Humans Young Adult Male Support Vector Machine
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Automatic Sleep Stage Scoring Using Time-Frequency Analysis and Stacked Sparse Autoencoders.

Annals of biomedical engineering Oct 13, 2015
We developed a machine learning methodology for automatic sleep stage scoring. Our time-frequency analysis-based feature extraction is fine-tuned to capture sleep stage-specific signal features as described in the American Academy of Sleep Medicine m...
Signal Processing, Computer-Assisted Sleep Stages Adult Male Electroencephalography Databases, Factual Female Humans Machine Learning
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Sleep stage classification with ECG and respiratory effort.

Physiological measurement Aug 19, 2015
Automatic sleep stage classification with cardiorespiratory signals has attracted increasing attention. In contrast to the traditional manual scoring based on polysomnography, these signals can be measured using advanced unobtrusive techniques that a...
Signal Processing, Computer-Assisted Respiration Sleep Stages Adult Male Autonomic Nervous System Humans Electrocardiography Machine Learning Female
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Multi-channel EEG-based sleep stage classification with joint collaborative representation and multiple kernel learning.

Journal of neuroscience methods Jul 17, 2015
BACKGROUND: Electroencephalography (EEG) based sleep staging is commonly used in clinical routine. Feature extraction and representation plays a crucial role in EEG-based automatic classification of sleep stages. Sparse representation (SR) is a state...
Machine Learning Brain Sensitivity and Specificity Polysomnography Sleep Stages Electroencephalography Sleep Apnea Syndromes Humans
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Learning machines and sleeping brains: Automatic sleep stage classification using decision-tree multi-class support vector machines.

Journal of neuroscience methods Jan 25, 2015
BACKGROUND: Sleep staging is a critical step in a range of electrophysiological signal processing pipelines used in clinical routine as well as in sleep research. Although the results currently achievable with automatic sleep staging methods are prom...
Humans Electrooculography Brain Cluster Analysis Sleep Stages Decision Trees Electromyography Adult Discriminant Analysis Linear Models Sensitivity and Specificity Electroencephalography Polysomnography Support Vector Machine
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Artificial intelligence or sleep experts: comparing polysomnographic sleep staging in children and adolescents.

Sleep Jul 11, 2025
STUDY OBJECTIVES: The manual annotation of polysomnography (PSG) hypnograms is difficult and time-consuming. U-Sleep is an alternative, fast, and publicly available, automated sleep staging system evaluated in adult PSGs. In this study, we compare th...
Humans Adolescent Child Polysomnography Artificial Intelligence Sleep Stages Female Male
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Mobile Sleep Stage Analysis Using Multichannel Wearable Devices Integrated with Stretchable Transparent Electrodes.

ACS sensors Jun 27, 2025
The prevalence of sleep disorders in the aging population and the importance of sleep quality for health have emphasized the need for accurate and accessible sleep monitoring solutions. Polysomnography (PSG) remains the clinical gold standard for dia...
Electrooculography Humans Sleep Stages Electromyography Artificial Intelligence Wearable Electronic Devices Adult Electrodes Electroencephalography Male Polysomnography
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Deep-ATM DL-LSTM: A novel adaptive thresholding model with dual-layer LSTM architecture for real-time driver drowsiness detection using skin conductance signals.

Computers in biology and medicine Jun 1, 2025
Driver drowsiness detection systems are crucial for road safety. However, existing machine learning models struggle to adjust thresholds for Skin Conductance (SC) adaptively signals due to insufficient feature extraction of tonic and phasic responses...
Humans Neural Networks, Computer Female Galvanic Skin Response Signal Processing, Computer-Assisted Adult Automobile Driving Male Sleep Stages Deep Learning
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Real-time driver drowsiness detection using transformer architectures: a novel deep learning approach.

Scientific reports May 20, 2025
Driver drowsiness is a leading cause of road accidents, resulting in significant societal, economic, and emotional losses. This paper introduces a novel and robust deep learning-based framework for real-time driver drowsiness detection, leveraging st...
Humans Sleep Stages Deep Learning Accidents, Traffic Automobile Driving
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