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 451–475 of 1655 papers

TitleStatusHype
Global dynamics of neural mass models—0
A library of quantitative markers of seizure severityCode0
Data augmentation for learning predictive models on EEG: a systematic comparisonCode1
Imaging the time series of one single referenced EEG electrode for Epileptic Seizures Risk Analysis—0
Improving self-supervised pretraining models for epileptic seizure detection from EEG data—0
An Investigation on Non-Invasive Brain-Computer Interfaces: Emotiv Epoc+ Neuroheadset and Its Effectiveness—0
A Multimodal Perceived Stress Classification Framework using Wearable Physiological Sensors—0
ConTraNet: A single end-to-end hybrid network for EEG-based and EMG-based human machine interfaces—0
Deep representation of EEG data from Spatio-Spectral Feature Images—0
Seizure Detection and Prediction by Parallel Memristive Convolutional Neural NetworksCode1
EPOC Emotiv EEG Basics—0
Self-Supervised Contrastive Pre-Training For Time Series via Time-Frequency ConsistencyCode2
Factorization Approach for Sparse Spatio-Temporal Brain-Computer Interface—0
A Deep Learning Approach for the Segmentation of Electroencephalography Data in Eye Tracking ApplicationsCode1
Bispectrum-based Cross-frequency Functional Connectivity: Classification of Alzheimer's disease—0
Neonatal EEG graded for severity of background abnormalities in hypoxic-ischaemic encephalopathyCode0
HDTorch: Accelerating Hyperdimensional Computing with GP-GPUs for Design Space Exploration—0
Binary Single-dimensional Convolutional Neural Network for Seizure Prediction—0
Motiflets -- Simple and Accurate Detection of Motifs in Time SeriesCode1
MICAL: Mutual Information-Based CNN-Aided Learned FactorCode0
Learning Generative Factors of EEG Data with Variational auto-encodersCode1
Classification at the Accuracy Limit -- Facing the Problem of Data Ambiguity—0
Investigating Brain Connectivity with Graph Neural Networks and GNNExplainerCode1
Functional Connectivity Methods for EEG-based Biometrics on a Large, Heterogeneous Dataset—0
SPD domain-specific batch normalization to crack interpretable unsupervised domain adaptation in EEGCode1
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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