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 551–575 of 1655 papers

TitleStatusHype
Human Brains Can't Detect Fake News: A Neuro-Cognitive Study of Textual Disinformation Susceptibility—0
Reliability and validity of TMS-EEG biomarkers—0
Upper Limb Movement Recognition utilising EEG and EMG Signals for Rehabilitative RoboticsCode0
EEG2Vec: Learning Affective EEG Representations via Variational Autoencoders—0
A multi-level interpretable sleep stage scoring system by infusing experts' knowledge into a deep network architecture—0
Schizophrenia detection based on EEG using Recurrent Auto-Encoder framework—0
Relating the fundamental frequency of speech with EEG using a dilated convolutional network—0
Learning Subject-Invariant Representations from Speech-Evoked EEG Using Variational Autoencoders—0
Automatic Sleep Scoring from Large-scale Multi-channel Pediatric EEGCode0
Global dynamics of neural mass models—0
A library of quantitative markers of seizure severityCode0
Imaging the time series of one single referenced EEG electrode for Epileptic Seizures Risk Analysis—0
Improving self-supervised pretraining models for epileptic seizure detection from EEG data—0
An Investigation on Non-Invasive Brain-Computer Interfaces: Emotiv Epoc+ Neuroheadset and Its Effectiveness—0
A Multimodal Perceived Stress Classification Framework using Wearable Physiological Sensors—0
ConTraNet: A single end-to-end hybrid network for EEG-based and EMG-based human machine interfaces—0
Deep representation of EEG data from Spatio-Spectral Feature Images—0
EPOC Emotiv EEG Basics—0
Factorization Approach for Sparse Spatio-Temporal Brain-Computer Interface—0
Bispectrum-based Cross-frequency Functional Connectivity: Classification of Alzheimer's disease—0
Neonatal EEG graded for severity of background abnormalities in hypoxic-ischaemic encephalopathyCode0
HDTorch: Accelerating Hyperdimensional Computing with GP-GPUs for Design Space Exploration—0
Binary Single-dimensional Convolutional Neural Network for Seizure Prediction—0
MICAL: Mutual Information-Based CNN-Aided Learned FactorCode0
Classification at the Accuracy Limit -- Facing the Problem of Data Ambiguity—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