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 1551–1575 of 1655 papers

TitleStatusHype
Causal interpretation rules for encoding and decoding models in neuroimaging—0
Certainty based Reduced Sparse Solution for Dense Array EEG Source Localization—0
Challenges of Driver Drowsiness Prediction: The Remaining Steps to Implementation—0
Changes in Power and Information Flow in Resting-state EEG by Working Memory Process—0
Channel-Imposed Fusion: A Simple yet Effective Method for Medical Time Series Classification—0
Characterizing functional brain networks and emotional centers based on Rasa theory of Indian aesthetics—0
Characterizing TMS-EEG perturbation indexes using signal energy: initial study on Alzheimer's Disease classification—0
Chirp Localization via Fine-Tuned Transformer Model: A Proof-of-Concept Study—0
Choosing Wavelet Methods, Filters, and Lengths for Functional Brain Network Construction—0
Chronic iEEG recordings and interictal spike rate reveal multiscale temporal modulations in seizure states—0
CIT-EmotionNet: CNN Interactive Transformer Network for EEG Emotion Recognition—0
CLARA: Clinical Report Auto-completion—0
CLARE: Cognitive Load Assessment in REaltime with Multimodal Data—0
Classification and Recognition of Encrypted EEG Data Neural Network—0
Classification at the Accuracy Limit -- Facing the Problem of Data Ambiguity—0
Classification of ADHD and Healthy Children Using EEG Based Multi-Band Spatial Features Enhancement—0
Classification of auditory stimuli from EEG signals with a regulated recurrent neural network reservoir—0
Classification of Autism Spectrum Disorder Using Supervised Learning of Brain Connectivity Measures Extracted from Synchrostates—0
Classification of Brainwave Signals Based on Hybrid Deep Learning and an Evolutionary Algorithm—0
Classification of Distraction Levels Using Hybrid Deep Neural Networks From EEG Signals—0
Classification of EEG-Based Brain Connectivity Networks in Schizophrenia Using a Multi-Domain Connectome Convolutional Neural Network—0
Classification of EEG Motor Imagery Using Deep Learning for Brain-Computer Interface Systems—0
Classification of EEG Signal based on non-Gaussian Neutral Vector—0
Classification of EEG Signals using Genetic Programming for Feature Construction—0
Classification of Electroencephalograms during Mathematical Calculations Using Deep Learning—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