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 1401–1425 of 1655 papers

TitleStatusHype
An Investigation on Non-Invasive Brain-Computer Interfaces: Emotiv Epoc+ Neuroheadset and Its Effectiveness—0
An Olfactory EEG Signal Classification Network Based on Frequency Band Feature Extraction—0
Anomaly Detection and Removal Using Non-Stationary Gaussian Processes—0
A Novel Bi-hemispheric Discrepancy Model for EEG Emotion Recognition—0
A novel convolutional neural network model to remove muscle artifacts from EEG—0
A Novel Deep Learning Architecture for Decoding Imagined Speech from EEG—0
A Novel Independent RNN Approach to Classification of Seizures against Non-seizures—0
A Novel Method for Epileptic Seizure Detection Using Coupled Hidden Markov Models—0
A Novel Multi-scale Dilated 3D CNN for Epileptic Seizure Prediction—0
A Novel RL-assisted Deep Learning Framework for Task-informative Signals Selection and Classification for Spontaneous BCIs—0
A novel spike-and-wave automatic detection in EEG signals—0
A Novel Transferability Attention Neural Network Model for EEG Emotion Recognition—0
A Novel TSK Fuzzy System Incorporating Multi-view Collaborative Transfer Learning for Personalized Epileptic EEG Detection—0
Anticipated synchronization in human EEG data: unidirectional causality with negative phase-lag—0
Anticipating epileptic seizures through the analysis of EEG synchronization as a data classification problem—0
A Parametric Time Frequency-Conditional Granger Causality Method Using Ultra-regularized Orthogonal Least Squares and Multiwavelets for Dynamic Connectivity Analysis in EEGs—0
A penalized likelihood method for classification with matrix-valued predictors—0
A-Phase classification using convolutional neural networks—0
A Pilot Study on Visually Stimulated Cognitive Tasks for EEG-Based Dementia Recognition—0
Application of Common Spatial Patterns in Gravitational Waves Detection—0
Application of Dictionary Learning in Alleviating Computational Burden of EEG Source Localization—0
Application of Machine Learning to Sleep Stage Classification—0
Application of statistical analysis to working memory problem—0
Application of Topological Data Analysis to Delirium Detection—0
Applying Transfer Learning To Deep Learned Models For EEG Analysis—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