SOTAVerified

Electroencephalogram (EEG)

Electroencephalogram (EEG) is a method of recording brain activity using electrophysiological indexes. When the brain is active, a large number of postsynaptic potentials generated synchronously by neurons are formed after summation. It records the changes of electric waves during brain activity and is the overall reflection of the electrophysiological activities of brain nerve cells on the surface of cerebral cortex or scalp. Brain waves originate from the postsynaptic potential of the apical dendrites of pyramidal cells. The formation of synchronous rhythm of EEG is also related to the activity of nonspecific projection system of cortex and thalamus. EEG is the basic theoretical research of brain science. EEG monitoring is widely used in its clinical application.

Papers

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Showing 751–775 of 1655 papers

TitleStatusHype
Holistic Semi-Supervised Approaches for EEG Representation Learning—0
Improving the spectral resolution of fMRI signals through the temporal de-correlation approach—0
Predicting Stress in Remote Learning via Advanced Deep Learning Technologies—0
EEG Signal Processing using Wavelets for Accurate Seizure Detection through Cost Sensitive Data Mining—0
Why Don't You Click: Neural Correlates of Non-Click Behaviors in Web Search—0
Towards the Classification of Error-Related Potentials using Riemannian Geometry—0
Contrastive Learning of Subject-Invariant EEG Representations for Cross-Subject Emotion Recognition—0
Functional switching among dynamic neuronal hub-nodes in the brain induces transition of cognitive states—0
Challenges of Driver Drowsiness Prediction: The Remaining Steps to Implementation—0
Seizure pathways and seizure durations can vary independently within individual patients with focal epilepsy—0
SCORE-IT: A Machine Learning-based Tool for Automatic Standardization of EEG Reports—0
EEGDnet: Fusing Non-Local and Local Self-Similarity for 1-D EEG Signal Denoising with 2-D Transformer—0
GANSER: A Self-supervised Data Augmentation Framework for EEG-based Emotion Recognition—0
Detection of Epileptic Seizures on EEG Signals Using ANFIS Classifier, Autoencoders and Fuzzy Entropies—0
gen2Out: Detecting and Ranking Generalized AnomaliesCode0
FBDNN: Filter Banks and Deep Neural Networks for Portable and Fast Brain-Computer InterfacesCode0
Automatic Diagnosis of Schizophrenia in EEG Signals Using CNN-LSTM Models—0
Seizure Classification of EEG based on Wavelet Signal Denoising Using a Novel Channel Selection Algorithm—0
MutualGraphNet: A novel model for motor imagery classification—0
EEG-connectivity: A fundamental guide and checklist for optimal study design and evaluation—0
An Electroencephalography connectome predictive model of major depressive disorder severity—0
DeepSleepNet-Lite: A Simplified Automatic Sleep Stage Scoring Model with Uncertainty Estimates—0
EEG-based Classification of Drivers Attention using Convolutional Neural Network—0
Pediatric Automatic Sleep Staging: A comparative study of state-of-the-art deep learning methods—0
Electroencephalogram Signal Processing with Independent Component Analysis and Cognitive Stress Classification using Convolutional Neural Networks—0
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All datasetsSEED-IVHS-SSVEPSEED

Benchmark Results

#ModelMetricClaimedVerifiedStatus
1BiHDMAccuracy74.35—Unverified
2DGCNNAccuracy69.88—Unverified
3DBNAccuracy66.77—Unverified
#ModelMetricClaimedVerifiedStatus
1MultitaskSSVEPAccuracy (5-fold)92.2—Unverified
#ModelMetricClaimedVerifiedStatus
1DBNAccuracy86.08—Unverified