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 1126–1150 of 1655 papers

TitleStatusHype
Continuous Speech Recognition using EEG and Video—0
A novel spike-and-wave automatic detection in EEG signals—0
Improved Explanatory Efficacy on Human Affect and Workload through Interactive Process in Artificial Intelligence—0
Seizure Prediction Using Bidirectional LSTM—0
Automated Pipeline for EEG Artifact Reduction (APPEAR) Recorded during fMRICode0
Analysis of Cardiovascular Changes Caused by Epileptic Seizures in Human Photoplethysmogram Signal—0
Semi-supervised Stacked Label Consistent Autoencoder for Reconstruction and Analysis of Biomedical Signals—0
Integration of Simultaneous Resting-State Electroencephalography, Functional Magnetic Resonance Imaging, and Eye-Tracker Methods to Determine and Verify Electroencephalography Vigilance Measure—0
Navigating in Virtual Reality using Thought: The Development and Assessment of a Motor Imagery based Brain-Computer Interface—0
edBB: Biometrics and Behavior for Assessing Remote EducationCode1
Neural Memory Networks for Seizure Type Classification—0
Classification of Brainwave Signals Based on Hybrid Deep Learning and an Evolutionary Algorithm—0
Phase/amplitude synchronization of brain signals during motor imagery BCI tasks—0
Hybrid multi-objective evolutionary algorithm based on Search Manager framework for big data optimization problemsCode0
Extreme Learning Machine design for dealing with unrepresentative featuresCode0
Universal Adversarial Perturbations for CNN Classifiers in EEG-Based BCIsCode0
A state-space model for inferring effective connectivity of latent neural dynamics from simultaneous EEG/fMRICode0
Multimodal Affective States Recognition Based on Multiscale CNNs and Biologically Inspired Decision Fusion Model—0
Universal EEG Encoder for Learning Diverse Intelligent Tasks—0
Improving EEG based Continuous Speech Recognition—0
Quantum calcium-ion interactions with EEG—0
Evaluation of techniques for predicting seizure Build up—0
A Recurrent Probabilistic Neural Network with Dimensionality Reduction Based on Time-series Discriminant Component Analysis—0
Deep Learning Decoding of Mental State in Non-invasive Brain Computer Interface—0
Modeling EEG data distribution with a Wasserstein Generative Adversarial Network to predict RSVP EventsCode0
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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