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 676–700 of 1655 papers

TitleStatusHype
Deep convolutional recurrent neural network for short-interval EEG motor imagery classification—0
Variational Component Decoder for Source Extraction from Nonlinear Mixture—0
PDAML: A Pseudo Domain Adaptation Paradigm for Subject-independent EEG-based Emotion Recognition—0
TIME-LAPSE: Learning to say “I don't know” through spatio-temporal uncertainty scoring—0
Practical Adversarial Attacks on Brain--Computer Interfaces—0
Low-cost brain computer interface for everyday useCode1
EEG based stress analysis using rhythm specific spectral feature for video gameplay—0
An Efficient Epileptic Seizure Detection Technique using Discrete Wavelet Transform and Machine Learning Classifiers—0
Improving the spectral resolution of fMRI signals through the temporal de-correlation approach—0
Holistic Semi-Supervised Approaches for EEG Representation Learning—0
EEG Signal Processing using Wavelets for Accurate Seizure Detection through Cost Sensitive Data Mining—0
Predicting Stress in Remote Learning via Advanced Deep Learning Technologies—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
Self-supervised Contrastive Learning for EEG-based Sleep StagingCode1
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
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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