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 1326–1350 of 1655 papers

TitleStatusHype
EEG Classification based on Image Configuration in Social Anxiety Disorder—0
DOSED: a deep learning approach to detect multiple sleep micro-events in EEG signalCode0
Data-driven cortical clustering to provide a family of plausible solutions to M/EEG inverse problem—0
AI Neurotechnology for Aging Societies -- Task-load and Dementia EEG Digital Biomarker Development Using Information Geometry Machine Learning Methods—0
Real-Time Sleep Staging using Deep Learning on a Smartphone for a Wearable EEGCode0
Compensated Integrated Gradients to Reliably Interpret EEG Classification—0
Unsupervised Learning in Reservoir Computing for EEG-based Emotion Recognition—0
Electrophysiological indicators of gesture perception—0
Detection of REM Sleep Behaviour Disorder by Automated Polysomnography AnalysisCode0
Nonlinear analysis of EEG complexity in episode and remission phase of recurrent depression—0
StationPlot: A New Non-stationarity Quantification Tool for Detection of Epileptic Seizures—0
An amplitudes-perturbation data augmentation method in convolutional neural networks for EEG decoding—0
Cogni-Net: Cognitive Feature Learning through Deep Visual PerceptionCode0
Decoding Brain Representations by Multimodal Learning of Neural Activity and Visual Features—0
Evaluation of algorithms for correction of transcranial magnetic stimulation induced artifacts in electroencephalograms—0
Alzheimer's Disease Diagnosis Based on Cognitive Methods in Virtual Environments and Emotions Analysis—0
Boosted Convolutional Neural Networks for Motor Imagery EEG Decoding with Multiwavelet-based Time-Frequency Conditional Granger Causality Analysis—0
A Parametric Time Frequency-Conditional Granger Causality Method Using Ultra-regularized Orthogonal Least Squares and Multiwavelets for Dynamic Connectivity Analysis in EEGs—0
CARE-rCortex: a Matlab toolbox for the analysis of CArdio-REspiratory-related activity in the CortexCode0
Automatic Detection of Arousals during Sleep using Multiple Physiological Signals—0
Entropy-Assisted Multi-Modal Emotion Recognition Framework Based on Physiological Signals—0
Automated Classification of Sleep Stages and EEG Artifacts in Mice with Deep Learning—0
A unifying Bayesian approach for preterm brain-age prediction that models EEG sleep transitions over age—0
Identifying Ketamine Responses in Treatment-Resistant Depression Using a Wearable Forehead EEG—0
Reconfiguration of Brain Network between Resting-state and Oddball Paradigm—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