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 751–775 of 1655 papers

TitleStatusHype
Subject Independent Emotion Recognition using EEG Signals Employing Attention Driven Neural Networks—0
Classification of Hand-Grasp Movements of Stroke Patients using EEG DataCode1
EEG changes and motor deficits in Parkinson's disease patients: Correlation of motor scales and EEG power bands—0
Random Forest classifier for EEG-based seizure prediction—0
Tracé alternant detector for grading hypoxic-ischemic encephalopathy in neonatal EEG—0
EEG-based Cross-Subject Driver Drowsiness Recognition with an Interpretable Convolutional Neural NetworkCode1
A Compact and Interpretable Convolutional Neural Network for Cross-Subject Driver Drowsiness Detection from Single-Channel EEGCode1
Bioelectrical brain activity can predict prosocial behavior—0
Generating Ten BCI Commands Using Four Simple Motor Imageries—0
Deep Learning for EEG Seizure Detection in Preterm Infants—0
Neonatal seizure detection from raw multi-channel EEG using a fully convolutional architecture—0
Robust learning from corrupted EEG with dynamic spatial filteringCode1
SleepTransformer: Automatic Sleep Staging with Interpretability and Uncertainty Quantification—0
Automated Detection of Abnormalities from an EEG Recording of Epilepsy Patients With a Compact Convolutional Neural Network—0
Deep Correlation Analysis for Audio-EEG Decoding—0
Predicting speech intelligibility from EEG in a non-linear classification paradigm—0
Dyadic aggregated autoregressive (DASAR) model for time-frequency representation of biomedical signals—0
Deep Convolutional Neural Network Applied to Electroencephalography: Raw Data vs Spectral FeaturesCode0
Normative brain mapping of interictal intracranial EEG to localise epileptogenic tissue—0
Long-term changes in functional connectivity predict responses to intracranial stimulation of the human brain—0
High-dimensional Functional Graphical Model Structure Learning via Neighborhood Selection ApproachCode0
LGGNet: Learning from Local-Global-Graph Representations for Brain-Computer InterfaceCode1
A Novel Multi-scale Dilated 3D CNN for Epileptic Seizure Prediction—0
Distilling EEG Representations via Capsules for Affective Computing—0
PSEUDo: Interactive Pattern Search in Multivariate Time Series with Locality-Sensitive Hashing and Relevance Feedback—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