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 1201–1225 of 1655 papers

TitleStatusHype
Adversarial Feature Learning in Brain Interfacing: An Experimental Study on Eliminating Drowsiness Effects—0
Synthetic Epileptic Brain Activities Using Generative Adversarial NetworksCode0
A-Phase classification using convolutional neural networks—0
EEG-Based Emotion Recognition Using Regularized Graph Neural NetworksCode1
An end-to-end (deep) neural network applied to raw EEG, fNIRs and body motion data for data fusion and BCI classification task without any pre-/post-processing—0
Deep Invertible Networks for EEG-based brain-signal decoding—0
Electroencephalography based Classification of Long-term Stress using Psychological Labeling—0
Machine learning without a feature set for detecting bursts in the EEG of preterm infants—0
Deep Learning with ConvNET Predicts Imagery Tasks Through EEG—0
Suitability of an inter-burst detection method for grading hypoxic-ischemic encephalopathy in newborn EEG—0
Protecting Privacy of Users in Brain-Computer Interface Applications—0
Applying Transfer Learning To Deep Learned Models For EEG Analysis—0
Tensor Decomposition for EEG Signal Retrieval—0
Electroencephalogram (EEG) for Delineating Objective Measure of Autism Spectrum Disorder (ASD) (Extended Version)—0
Visualizing High Dimensional Dynamical Processes—0
Predicting epileptic seizures using nonnegative matrix factorizationCode0
Cross-Subject Statistical Shift Estimation for Generalized Electroencephalography-based Mental Workload Assessment—0
Brain correlates of task-load and dementia elucidation with tensor machine learning using oddball BCI paradigm—0
Bayesian fusion and multimodal DCM for EEG and fMRI—0
Advancing Speech Recognition With No Speech Or With Noisy Speech—0
Robust End-to-End Speaker Verification Using EEG—0
Speech Recognition With No Speech Or With Noisy Speech Beyond English—0
Decoding P300 Variability using Convolutional Neural NetworksCode0
Modified swarm-based metaheuristics enhance Gradient Descent initialization performance: Application for EEG spatial filtering—0
Classification of EEG Signals using Genetic Programming for Feature Construction—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