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 51–75 of 1655 papers

TitleStatusHype
edBB: Biometrics and Behavior for Assessing Remote EducationCode1
EEG2Mel: Reconstructing Sound from Brain Responses to MusicCode1
EEG-based Cross-Subject Driver Drowsiness Recognition with an Interpretable Convolutional Neural NetworkCode1
EEG-Based Emotion Recognition Using Regularized Graph Neural NetworksCode1
Device JNEEG to convert Jetson Nano to brain-Computer interfaces. Short reportCode1
EEG-ConvTransformer for Single-Trial EEG based Visual Stimuli ClassificationCode1
EEGdenoiseNet: A benchmark dataset for end-to-end deep learning solutions of EEG denoisingCode1
EEGEyeNet: a Simultaneous Electroencephalography and Eye-tracking Dataset and Benchmark for Eye Movement PredictionCode1
clusterBMA: Bayesian model averaging for clusteringCode1
EEG-ITNet: An Explainable Inception Temporal Convolutional Network for Motor Imagery ClassificationCode1
A few filters are enough: Convolutional Neural Network for P300 DetectionCode1
EEG Synthetic Data Generation Using Probabilistic Diffusion ModelsCode1
Closed loop BCI System for Cybathlon 2020Code1
CognitionCapturer: Decoding Visual Stimuli From Human EEG Signal With Multimodal InformationCode1
Causal Recurrent Variational Autoencoder for Medical Time Series GenerationCode1
EEG-based Emotional Video Classification via Learning Connectivity StructureCode1
Classification of Hand-Grasp Movements of Stroke Patients using EEG DataCode1
Correct block-design experiments mitigate temporal correlation bias in EEG classificationCode1
Self-Supervised Graph Neural Networks for Improved Electroencephalographic Seizure AnalysisCode1
Automated Parkinson's Disease Detection and Affective Analysis from Emotional EEG SignalsCode1
A 1D CNN for high accuracy classification and transfer learning in motor imagery EEG-based brain-computer interfaceCode1
Automatic detection of microsleep episodes with deep learningCode1
Brain Topography Adaptive Network for Satisfaction Modeling in Interactive Information Access SystemCode1
CwA-T: A Channelwise AutoEncoder with Transformer for EEG Abnormality DetectionCode1
A Transformer-based deep neural network model for SSVEP classificationCode1
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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