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 1601–1625 of 1655 papers

TitleStatusHype
Backward Renormalization Priors and the Cortical Source Localization Problem with EEG or MEG—0
Difficulties applying recent blind source separation techniques to EEG and MEG—0
Sparse Bayesian Learning for EEG Source Localization—0
Using Riemannian geometry for SSVEP-based Brain Computer InterfaceCode0
Detecting Epileptic Seizures from EEG Data using Neural Networks—0
Imagined speech classification using EEGCode0
Covariance shrinkage for autocorrelated data—0
Using Convolutional Neural Networks to Recognize Rhythm Stimuli from Electroencephalography Recordings—0
Canonical Polyadic Decomposition with Auxiliary Information for Brain Computer Interface—0
Prediction of Synchrostate Transitions in EEG Signals Using Markov Chain Models—0
Classification of Autism Spectrum Disorder Using Supervised Learning of Brain Connectivity Measures Extracted from Synchrostates—0
Artifact reduction in multichannel pervasive EEG using hybrid WPT-ICA and WPT-EMD signal decomposition techniques—0
Feature Learning from Incomplete EEG with Denoising Autoencoder—0
Identification of Dynamic functional brain network states Through Tensor Decomposition—0
An Open-source Toolbox for Analysing and Processing PhysioNet Databases in MATLAB and OctaveCode0
Object Segmentation in Images using EEG Signals—0
New crossover operators for multiple subset selection tasks—0
Subspace metrics for multivariate dictionaries and application to EEGCode0
Dimensionality reduction for time series data—0
Spatial Neural Networks and their Functional Samples: Similarities and Differences—0
New functions for a multipurpose multimodal tool for phonetic and linguistic analysis of very large speech corpora—0
Spatiotemporal Sparse Bayesian Learning with Applications to Compressed Sensing of Multichannel Physiological Signals—0
Human brain distinctiveness based on EEG spectral coherence connectivity—0
Sleep Analytics and Online Selective Anomaly Detection—0
Modeling the Complex Dynamics and Changing Correlations of Epileptic Events—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