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 1376–1400 of 1655 papers

TitleStatusHype
A deep learning architecture to detect events in EEG signals during sleepCode0
Affective EEG-Based Person Identification Using the Deep Learning Approach—0
Addressing Class Imbalance in Classification Problems of Noisy Signals by using Fourier Transform Surrogates—0
Semi-supervised Seizure Prediction with Generative Adversarial Networks—0
Improving brain computer interface performance by data augmentation with conditional Deep Convolutional Generative Adversarial Networks—0
Fast and Accurate Multiclass Inference for MI-BCIs Using Large Multiscale Temporal and Spectral FeaturesCode0
A large-scale evaluation framework for EEG deep learning architectures—0
Denoising Time Series Data Using Asymmetric Generative Adversarial Networks—0
Brain-Computer Interface with Corrupted EEG Data: A Tensor Completion Approach—0
Early Seizure Detection with an Energy-Efficient Convolutional Neural Network on an Implantable Microcontroller—0
Neonatal EEG Interpretation and Decision Support Framework for Mobile Platforms—0
Investigating the Impact of CNN Depth on Neonatal Seizure Detection Performance—0
Robustifying Independent Component Analysis by Adjusting for Group-Wise Stationary NoiseCode0
A Hierarchical Fuzzy System for an Advanced Driving Assistance System—0
A Multi-Context Character Prediction Model for a Brain-Computer Interface—0
Deep Semantic Architecture with discriminative feature visualization for neuroimage analysis—0
Focal onset seizure prediction using convolutional networks—0
Adaptive neural network classifier for decoding MEG signals—0
Multivariate Convolutional Sparse Coding for Electromagnetic Brain SignalsCode0
Multitaper Spectral Estimation HDP-HMMs for EEG Sleep Inference—0
Brain Age from the Electroencephalogram of Sleep—0
Lehmer Transform and its Theoretical Properties—0
Active Semi-supervised Transfer Learning (ASTL) for Offline BCI Calibration—0
A New Method for Epileptic Seizure Classification in EEG Using Adapted Wavelet Packets—0
Offline EEG-Based Driver Drowsiness Estimation Using Enhanced Batch-Mode Active Learning (EBMAL) for Regression—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