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 926–950 of 1655 papers

TitleStatusHype
Optimized EEG based mood detection with signal processing and deep neural networks for brain-computer interface—0
Optimized Feature Selection and Neural Network-Based Classification of Motor Imagery Using EEG Signals—0
Optimized preprocessing and Tiny ML for Attention State Classification—0
Optimizing Brain-Computer Interface Performance: Advancing EEG Signals Channel Selection through Regularized CSP and SPEA II Multi-Objective Optimization—0
Optimizing Channel Selection for Seizure Detection—0
Optimizing food taste sensory evaluation through neural network-based taste electroencephalogram channel selection—0
Optimizing Multi-Class Spatio-Spectral Filters via Bayes Error Estimation for EEG Classification—0
Order patterns, their variation and change points in financial time series and Brownian motion—0
Organization and Independence or Interdependence? Study of the Neurophysiological Dynamics of Syntactic and Semantic Processing—0
Orthogonal Features-based EEG Signal Denoising using Fractionally Compressed AutoEncoder—0
Orthogonal Features Based EEG Signals Denoising Using Fractional and Compressed One-Dimensional CNN AutoEncoder—0
Overlapping neural representations for the position of visible and imagined objects—0
Overview of the EEG Pilot Subtask at MediaEval 2021: Predicting Media Memorability—0
Overview of The MediaEval 2021 Predicting Media Memorability Task—0
Overview of The MediaEval 2022 Predicting Video Memorability Task—0
Parametric Modeling of EEG Signals—0
Partial Least Square Regression via Three-factor SVD-type Manifold Optimization for EEG Decoding—0
Patient-independent Epileptic Seizure Prediction using Deep Learning Models—0
Patient Independent Interictal Epileptiform Discharge Detection—0
Patient-Specific Seizure Prediction Using Single Seizure Electroencephalography Recording—0
PDAML: A Pseudo Domain Adaptation Paradigm for Subject-independent EEG-based Emotion Recognition—0
Pediatric Automatic Sleep Staging: A comparative study of state-of-the-art deep learning methods—0
Performance and utility trade-off in interpretable sleep staging—0
Performance of Dual-Augmented Lagrangian Method and Common Spatial Patterns applied in classification of Motor-Imagery BCI—0
Periodic and non-periodic brainwaves emerging via random syncronization of closed loops of firing neurons—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