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 301–325 of 1655 papers

TitleStatusHype
A Wearable EEG System for Closed-Loop Neuromodulation of High-Frequency Sleep-Related Oscillations—0
Deep Riemannian Networks for End-to-End EEG DecodingCode0
Toward cross-subject and cross-session generalization in EEG-based emotion recognition: Systematic review, taxonomy, and methods—0
A unified information-theoretic model of EEG signatures of human language processing—0
Calibration-Free Driver Drowsiness Classification based on Manifold-Level AugmentationCode0
Hybrid Paradigm-based Brain-Computer Interface for Robotic Arm Control—0
CropCat: Data Augmentation for Smoothing the Feature Distribution of EEG Signals—0
Nonparametric Independent Component Analysis for the Sources with Mixed Spectra—0
Classification of Distraction Levels Using Hybrid Deep Neural Networks From EEG Signals—0
Overview of The MediaEval 2022 Predicting Video Memorability Task—0
Changes in Power and Information Flow in Resting-state EEG by Working Memory Process—0
Neural Underpinnings of Decoupled Ethical Behavior in Adolescents as an Interaction of Peer and Personal Values—0
A Hybrid Brain-Computer Interface Using Motor Imagery and SSVEP Based on Convolutional Neural Network—0
EEG Opto-processor: epileptic seizure detection using diffractive photonic computing units—0
EEG-NeXt: A Modernized ConvNet for The Classification of Cognitive Activity from EEG—0
Closed loop BCI System for Cybathlon 2020Code1
Enhancing Low-Density EEG-Based Brain-Computer Interfaces with Similarity-Keeping Knowledge DistillationCode1
Nonlinear and Machine Learning Analyses on High-Density EEG data of Math Experts and Novices—0
Adversarial Artifact Detection in EEG-Based Brain-Computer Interfaces—0
Inferring latent neural sources via deep transcoding of simultaneously acquired EEG and fMRI—0
Target-centered Subject Transfer Framework for EEG Data Augmentation—0
Tensor Decomposition of Large-scale Clinical EEGs Reveals Interpretable Patterns of Brain PhysiologyCode0
Power Spectral Density-Based Resting-State EEG Classification of First-Episode Psychosis—0
STILN: A Novel Spatial-Temporal Information Learning Network for EEG-based Emotion Recognition—0
Motor Imagery Decoding Using Ensemble Curriculum Learning and Collaborative TrainingCode1
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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