AIMC Topic: Electrooculography

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PSEENet: A Pseudo-Siamese Neural Network Incorporating Electroencephalography and Electrooculography Characteristics for Heterogeneous Sleep Staging.

IEEE journal of biomedical and health informatics Sep 5, 2024
Sleep staging plays a critical role in evaluating the quality of sleep. Currently, most studies are either suffering from dramatic performance drops when coping with varying input modalities or unable to handle heterogeneous signals. To handle hetero...
Young Adult Adult Male Algorithms Female Signal Processing, Computer-Assisted Electrooculography Sleep Stages Middle Aged Electroencephalography Humans Neural Networks, Computer
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SleepGCN: A transition rule learning model based on Graph Convolutional Network for sleep staging.

Computer methods and programs in biomedicine Sep 2, 2024
BACKGROUND AND OBJECTIVE: Automatic sleep staging is essential for assessing and diagnosing sleep disorders, serving millions of people who suffer from them. Numerous sleep staging models have been proposed recently, but most of them have not fully e...
Signal Processing, Computer-Assisted Electrooculography Humans Algorithms Sleep Stages Machine Learning Neural Networks, Computer Electroencephalography
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Comparison of automated deep neural network against manual sleep stage scoring in clinical data.

Computers in biology and medicine Jul 18, 2024
OBJECTIVE: To compare the accuracy and generalizability of an automated deep neural network and the Philip Sleepware G3™ Somnolyzer system (Somnolyzer) for sleep stage scoring using American Academy of Sleep Medicine (AASM) guidelines.
Aged Adult Male Neural Networks, Computer Female Polysomnography Electrooculography Sleep Stages Middle Aged Signal Processing, Computer-Assisted Humans
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Machine learning-empowered sleep staging classification using multi-modality signals.

BMC medical informatics and decision making May 6, 2024
The goal is to enhance an automated sleep staging system's performance by leveraging the diverse signals captured through multi-modal polysomnography recordings. Three modalities of PSG signals, namely electroencephalogram (EEG), electrooculogram (EO...
Electromyography Polysomnography Sleep Stages Electrooculography Male Electroencephalography Signal Processing, Computer-Assisted Female Adult Humans Machine Learning
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EOG Signal Classification with Wavelet and Supervised Learning Algorithms KNN, SVM and DT.

Sensors (Basel, Switzerland) May 7, 2023
The work carried out in this paper consists of the classification of the physiological signal generated by eye movement called Electrooculography (EOG). The human eye performs simultaneous movements, when focusing on an object, generating a potential...
Support Vector Machine Wavelet Analysis Humans Electrooculography Algorithms Eye Movements
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A novel approach for detection of dyslexia using convolutional neural network with EOG signals.

Medical & biological engineering & computing Sep 5, 2022
Dyslexia is a learning disability in acquiring reading skills, even though the individual has the appropriate learning opportunity, adequate education, and appropriate sociocultural environment. Dyslexia negatively affects children's educational deve...
Neural Networks, Computer Eye Movements Child Electroencephalography User-Computer Interface Humans Electrooculography Dyslexia
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eyeSay: Brain Visual Dynamics Decoding With Deep Learning & Edge Computing.

IEEE transactions on neural systems and rehabilitation engineering : a publication of the IEEE Engineering in Medicine and Biology Society Aug 11, 2022
Brain visual dynamics encode rich functional and biological patterns of the neural system, and if decoded, are of great promise for many applications such as intention understanding, cognitive load quantization and neural disorder measurement. We her...
Electrooculography Deep Learning Amyotrophic Lateral Sclerosis Humans Brain-Computer Interfaces Brain
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A multi-modal assessment of sleep stages using adaptive Fourier decomposition and machine learning.

Computers in biology and medicine Jul 14, 2022
Healthy sleep is essential for the rejuvenation of the body and helps in maintaining good health. Many people suffer from sleep disorders that are characterized by abnormal sleep patterns. Automated assessment of such disorders using biomedical signa...
Electrooculography Sleep Stages Signal Processing, Computer-Assisted Polysomnography Humans Machine Learning Electroencephalography
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Multimodal Vigilance Estimation Using Deep Learning.

IEEE transactions on cybernetics May 19, 2022
The phenomenon of increasing accidents caused by reduced vigilance does exist. In the future, the high accuracy of vigilance estimation will play a significant role in public transportation safety. We propose a multimodal regression network that cons...
Deep Learning Electroencephalography Wakefulness Electrooculography
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Sleep staging classification based on a new parallel fusion method of multiple sources signals.

Physiological measurement Apr 28, 2022
In the field of medical informatics, sleep staging is a challenging and time consuming task undertaken by sleep experts. The conventional method for sleep staging is to analyze Polysomnograms (PSGs) recorded in a sleep lab, but the sleep monitoring w...
Sleep Stages Sleep Electrooculography Humans Algorithms Support Vector Machine Electroencephalography
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