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 601–625 of 1655 papers

TitleStatusHype
Dyslexia detection from EEG signals using SSA component correlation and Convolutional Neural Networks—0
Early Detection of Mental Stress Using Advanced Neuroimaging and Artificial Intelligence—0
Early Seizure Detection with an Energy-Efficient Convolutional Neural Network on an Implantable Microcontroller—0
Early soft and flexible fusion of EEG and fMRI via tensor decompositions—0
Detection of Sleep Oxygen Desaturations from Electroencephalogram Signals—0
Benefit-aware Early Prediction of Health Outcomes on Multivariate EEG Time Series—0
Edge Deep Learning for Neural Implants—0
Edge Sparse Basis Network: A Deep Learning Framework for EEG Source Localization—0
A Neural-Inspired Architecture for EEG-Based Auditory Attention Detection—0
EEG2Vec: Learning Affective EEG Representations via Variational Autoencoders—0
A Generative Model to Synthesize EEG Data for Epileptic Seizure Prediction—0
A Change Dynamic Model for the Online Detection of Gradual Change—0
EEG and EMG dataset for the detection of errors introduced by an active orthosis device—0
EEG-assisted Modulation of Sound Sources in the Auditory Scene—0
EEG-based AI-BCI Wheelchair Advancement: A Brain-Computer Interfacing Wheelchair System Using Deep Learning Approach—0
EEG-Based Brain-Computer Interaction: Improved Accuracy by Automatic Single-Trial Error Detection—0
EEG-Based Brain-Computer Interfaces Are Vulnerable to Backdoor Attacks—0
EEG-based Brain-Computer Interfaces (BCIs): A Survey of Recent Studies on Signal Sensing Technologies and Computational Intelligence Approaches and their Applications—0
EEG-based Classification of Drivers Attention using Convolutional Neural Network—0
EEG-based Cognitive Load Classification using Feature Masked Autoencoding and Emotion Transfer Learning—0
EEG-based Communication with a Predictive Text Algorithm—0
EEG based Continuous Speech Recognition using Transformers—0
Detection of Epileptic Seizures on EEG Signals Using ANFIS Classifier, Autoencoders and Fuzzy Entropies—0
EEG-Based Driver Drowsiness Estimation Using Feature Weighted Episodic Training—0
Detection of epileptic seizure in EEG signals using linear least squares preprocessing—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