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 1301–1325 of 1655 papers

TitleStatusHype
Deep learning-based electroencephalography analysis: a systematic reviewCode0
Spatial Filtering Pipeline Evaluation of Cortically Coupled Computer Vision System for Rapid Serial Visual Presentation—0
Seizure Detection using Least EEG Channels by Deep Convolutional Neural Network—0
Automated Brain Disorders Diagnosis Through Deep Neural NetworksCode0
DASPS: A Database for Anxious States based on a Psychological Stimulation—0
Real-Time EEG Classification via Coresets for BCI Applications—0
Features and Machine Learning for Correlating and Classifying between Brain Areas and Dyslexia—0
Certainty based Reduced Sparse Solution for Dense Array EEG Source Localization—0
Parametric Modeling of EEG Signals—0
Training on the test set? An analysis of Spampinato et al. [arXiv:1609.00344]—0
A Robust Deep Learning Approach for Automatic Classification of Seizures Against Non-seizures—0
Transfer Learning in Brain-Computer Interfaces with Adversarial Variational Autoencoders—0
Integrating Artificial Intelligence with Real-time Intracranial EEG Monitoring to Automate Interictal Identification of Seizure Onset Zones in Focal Epilepsy—0
EEG-based Communication with a Predictive Text Algorithm—0
Exploring Embedding Methods in Binary Hyperdimensional Computing: A Case Study for Motor-Imagery based Brain-Computer InterfacesCode0
Bayesian deep neural networks for low-cost neurophysiological markers of Alzheimer's disease severity—0
DOSED: a deep learning approach to detect multiple sleep micro-events in EEG signalCode0
Data-driven cortical clustering to provide a family of plausible solutions to M/EEG inverse problem—0
EEG Classification based on Image Configuration in Social Anxiety Disorder—0
AI Neurotechnology for Aging Societies -- Task-load and Dementia EEG Digital Biomarker Development Using Information Geometry Machine Learning Methods—0
Real-Time Sleep Staging using Deep Learning on a Smartphone for a Wearable EEGCode0
Compensated Integrated Gradients to Reliably Interpret EEG Classification—0
Unsupervised Learning in Reservoir Computing for EEG-based Emotion Recognition—0
Electrophysiological indicators of gesture perception—0
Detection of REM Sleep Behaviour Disorder by Automated Polysomnography AnalysisCode0
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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