AIMC Topic: Electrooculography
Clear Filters Showing 41 to 50 of 56 articles
Mixed Neural Network Approach for Temporal Sleep Stage Classification.
IEEE transactions on neural systems and rehabilitation engineering : a publication of the IEEE Engineering in Medicine and Biology Society
Jul 28, 2017
This paper proposes a practical approach to addressing limitations posed by using of single-channel electroencephalography (EEG) for sleep stage classification. EEG-based characterizations of sleep stage progression contribute the diagnosis and monit...
Diagnostic value of sleep stage dissociation as visualized on a 2-dimensional sleep state space in human narcolepsy.
Journal of neuroscience methods
Feb 20, 2017
BACKGROUND: Type 1 narcolepsy (NT1) is characterized by symptoms believed to represent Rapid Eye Movement (REM) sleep stage dissociations, occurrences where features of wake and REM sleep are intermingled, resulting in a mixed state. We hypothesized ...
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...
Automatic detection of rapid eye movements (REMs): A machine learning approach.
Journal of neuroscience methods
Nov 28, 2015
BACKGROUND: Rapid eye movements (REMs) are a defining feature of REM sleep. The number of discrete REMs over time, or REM density, has been investigated as a marker of clinical psychopathology and memory consolidation. However, human detection of REM...
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...
A novel EOG/EEG hybrid human-machine interface adopting eye movements and ERPs: application to robot control.
IEEE transactions on bio-medical engineering
Nov 12, 2014
This study presents a novel human-machine interface (HMI) based on both electrooculography (EOG) and electroencephalography (EEG). This hybrid interface works in two modes: an EOG mode recognizes eye movements such as blinks, and an EEG mode detects ...
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...
Investigating the Use of Electrooculography Sensors to Detect Stress During Working Activities.
Sensors (Basel, Switzerland)
May 10, 2025
To tackle work-related stress in the evolving landscape of Industry 5.0, organizations need to prioritize employee well-being through a comprehensive strategy. While electrocardiograms (ECGs) and electrodermal activity (EDA) are widely adopted physio...
An exploratory analysis of longitudinal artificial intelligence for cognitive fatigue detection using neurophysiological based biosignal data.
Scientific reports
May 6, 2025
Cognitive fatigue is a psychological condition characterized by opinions of fatigue and weakened cognitive functioning owing to constant stress. Cognitive fatigue is a critical condition that can significantly impair attention and performance, among ...
Mortality risk assessment using deep learning-based frequency analysis of electroencephalography and electrooculography in sleep.
Sleep
Feb 10, 2025
STUDY OBJECTIVES: To assess whether the frequency content of electroencephalography (EEG) and electrooculography (EOG) during nocturnal polysomnography (PSG) can predict all-cause mortality.
Stay Ahead of Medical AI
Join thousands of healthcare professionals staying informed about the latest AI breakthroughs in medicine. Get curated insights delivered to your inbox.
Subscribe NowPopular Topics
- Machine Learning 30978
- Neural Networks, Computer 29696
- Algorithms 26813
- Deep Learning 26324
- Artificial Intelligence 24267
- Robotics 13307
- Image Processing, Computer-Assisted 9512
- Retrospective Studies 9097
- Magnetic Resonance Imaging 6173
- Reproducibility of Results 5589
- Tomography, X-Ray Computed 4765
- Support Vector Machine 4678
- Computational Biology 4229
- Brain 4045
- Computer Simulation 3877
Recent Journals
- Scientific reports 5865
- Sensors (Basel, Switzerland) 4794
- PloS one 4011
- Neural networks : the official journal of the International Neural Network Society 2928
- Computational intelligence and neuroscience 1931
- Computers in biology and medicine 1839
- Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference 1686
- Studies in health technology and informatics 1278
- IEEE journal of biomedical and health informatics 1129
- Journal of chemical information and modeling 994
- Nature communications 938
- Computer methods and programs in biomedicine 883
- Bioinformatics (Oxford, England) 861
- Briefings in bioinformatics 850
- IEEE transactions on neural networks and learning systems 823