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 1426–1450 of 1655 papers

TitleStatusHype
Improvement of Resting-state EEG Analysis Process with Spectrum Weight-Voting based on LES—0
Plasma Brain Dynamics (PBD): A Mechanism for EEG Waves Under Human Consciousness—0
An Automated System for Epilepsy Detection using EEG Brain Signals based on Deep Learning ApproachCode0
Time Series Segmentation through Automatic Feature Learning—0
Brain EEG Time Series Selection: A Novel Graph-Based Approach for Classification—0
Context tree selection for functional dataCode0
Deep Classification of Epileptic Signals—0
Optimizing Channel Selection for Seizure Detection—0
An Analysis of Two Common Reference Points for EEGs—0
Semi-automated Annotation of Signal Events in Clinical EEG Data—0
Gated Recurrent Networks for Seizure Detection—0
The Temple University Hospital Seizure Detection Corpus—0
Improved EEG Event Classification Using Differential Energy—0
Objective evaluation metrics for automatic classification of EEG events—0
Deep Architectures for Automated Seizure Detection in Scalp EEGs—0
Automatic Analysis of EEGs Using Big Data and Hybrid Deep Learning Architectures—0
Report: Dynamic Eye Movement Matching and Visualization Tool in Neuro GestureCode0
Towards Deep Modeling of Music Semantics using EEG Regularizers—0
Single-trial P300 Classification using PCA with LDA, QDA and Neural Networks—0
Targeting EEG/LFP Synchrony with Neural Nets—0
EEG-GRAPH: A Factor-Graph-Based Model for Capturing Spatial, Temporal, and Observational Relationships in Electroencephalograms—0
Subject Selection on a Riemannian Manifold for Unsupervised Cross-subject Seizure Detection—0
EEG-assisted Modulation of Sound Sources in the Auditory Scene—0
Riemannian tangent space mapping and elastic net regularization for cost-effective EEG markers of brain atrophy in Alzheimer's disease—0
Post-hoc labeling of arbitrary EEG recordings for data-efficient evaluation of neural decoding methods—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