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 776–800 of 1655 papers

TitleStatusHype
An Attention-Based Deep Learning Approach for Sleep Stage Classification With Single-Channel EEGCode1
Group Feature Learning and Domain Adversarial Neural Network for aMCI Diagnosis System Based on EEG—0
Neural Language Models with Distant Supervision to Identify Major Depressive Disorder from Clinical Notes—0
Algoritmos de minería de datos en la industria sanitaria—0
Self-Supervised Graph Neural Networks for Improved Electroencephalographic Seizure AnalysisCode1
Orthogonal Features Based EEG Signals Denoising Using Fractional and Compressed One-Dimensional CNN AutoEncoder—0
Identification of mental fatigue in language comprehension tasks based on EEG and deep learning—0
Decoding of the Walking States and Step Rates from Cortical Electrocorticogram Signals—0
Toward asynchronous EEG-based BCI: Detecting imagined words segments in continuous EEG signalsCode0
Temporal EigenPAC for dyslexia diagnosis—0
Modelling Brain Connectivity Networks by Graph Embedding for Dyslexia Diagnosis—0
SFE-Net: EEG-based Emotion Recognition with Symmetrical Spatial Feature Extraction—0
One-class Autoencoder Approach for Optimal Electrode Set-up Identification in Wearable EEG Event Monitoring—0
Multimodal Fusion of EMG and Vision for Human Grasp Intent Inference in Prosthetic Hand Control—0
Neurological Status Classification Using Convolutional Neural Network—0
Strengthening the Training of Convolutional Neural Networks By Using Walsh MatrixCode0
Does Double Biofeedback Affect Functional Hemispheric Asymmetry and Activity? A Pilot Study—0
Convolutional Neural Networks for Sleep Stage Scoring on a Two-Channel EEG Signal—0
Product semantics translation from brain activity via adversarial learning—0
Retrieving Event-related Human Brain Dynamics from Natural Sentence Reading—0
Verifying Design through Generative Visualization of Neural Activities—0
Online Learning Koopman operator for closed-loop electrical neurostimulation in epilepsy—0
Source Aware Deep Learning Framework for Hand Kinematic Reconstruction using EEG Signal—0
Review Dry and Non-Contact EEG Electrodes for 2010-2021 Years—0
Progress in neural networks for EEG signal recognition in 2021—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