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 501–525 of 1655 papers

TitleStatusHype
Changepoint Detection in Noisy Data Using a Novel Residuals Permutation-Based Method (RESPERM): Benchmarking and Application to Single Trial ERPsCode0
Multi-Tier Platform for Cognizing Massive Electroencephalogram—0
Neuro-BERT: Rethinking Masked Autoencoding for Self-supervised Neurological PretrainingCode1
Unsupervised Motor Imagery Saliency Detection Based on Self-Attention Mechanism—0
Energy-Efficient Tree-Based EEG Artifact Detection—0
Is the Contralateral Delay Activity (CDA) a robust neural correlate for Visual Working Memory (VWM) tasks? A reproducibility study—0
Benchmarking Domain Generalization on EEG-based Emotion Recognition—0
An Adaptive Task-Related Component Analysis Method for SSVEP recognition—0
Intracranial EEG structure-function coupling predicts surgical outcomes in focal epilepsy—0
FKreg: A MATLAB toolbox for fast Multivariate Kernel Regression—0
Exploiting Multiple EEG Data Domains with Adversarial LearningCode0
Prototype-based Domain Generalization Framework for Subject-Independent Brain-Computer Interfaces—0
Decoding Neural Correlation of Language-Specific Imagined Speech using EEG Signals—0
EEG-ITNet: An Explainable Inception Temporal Convolutional Network for Motor Imagery ClassificationCode1
A Machine Learning Approach to Automatic Classification of Eight Sleep Disorders—0
GMSS: Graph-Based Multi-Task Self-Supervised Learning for EEG Emotion RecognitionCode1
Epileptic Seizure Risk Assessment by Multi-Channel Imaging of the EEG—0
A self-paced BCI system with low latency for motor imagery onset detection based on time series prediction paradigm—0
Ensemble learning using individual neonatal data for seizure detectionCode0
Comparison of EEG based epilepsy diagnosis using neural networks and wavelet transform—0
Motion Artifacts Correction from Single-Channel EEG and fNIRS Signals using Novel Wavelet Packet Decomposition in Combination with Canonical Correlation Analysis—0
Fuzzy temporal convolutional neural networks in P300-based Brain-computer interface for smart home interaction—0
mulEEG: A Multi-View Representation Learning on EEG SignalsCode1
Automated Sleep Staging via Parallel Frequency-Cut Attention—0
EMMT: A simultaneous eye-tracking, 4-electrode EEG and audio corpus for multi-modal reading and translation scenariosCode0
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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