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

Showing 126150 of 1655 papers

TitleStatusHype
SGDR: Stochastic Gradient Descent with Warm RestartsCode1
Artificial Intelligence for EEG Prediction: Applied Chaos TheoryCode1
Real-time noise cancellation with Deep LearningCode1
Evaluating Latent Space Robustness and Uncertainty of EEG-ML Models under Realistic Distribution ShiftsCode1
Automated Parkinson's Disease Detection and Affective Analysis from Emotional EEG SignalsCode1
Self-Supervised Graph Neural Networks for Improved Electroencephalographic Seizure AnalysisCode1
Automatic detection of microsleep episodes with deep learningCode1
BENDR: using transformers and a contrastive self-supervised learning task to learn from massive amounts of EEG dataCode1
CwA-T: A Channelwise AutoEncoder with Transformer for EEG Abnormality DetectionCode1
An electronic neuromorphic system for real-time detection of High Frequency Oscillations (HFOs) in intracranial EEGCode1
Causal Recurrent Variational Autoencoder for Medical Time Series GenerationCode1
Can Brain Signals Reveal Inner Alignment with Human Languages?Code1
Closed loop BCI System for Cybathlon 2020Code1
Deep learning with convolutional neural networks for EEG decoding and visualizationCode1
Cross Task Neural Architecture Search for EEG Signal ClassificationsCode1
Decoding Covert Speech from EEG Using a Functional Areas Spatio-Temporal TransformerCode1
Decoding Human Attentive States from Spatial-temporal EEG Patches Using TransformersCode1
EEG-GCNN: Augmenting Electroencephalogram-based Neurological Disease Diagnosis using a Domain-guided Graph Convolutional Neural NetworkCode1
Deep Multi-Task Learning for SSVEP Detection and Visual Response MappingCode1
Device JNEEG to convert Jetson Nano to brain-Computer interfaces. Short reportCode1
Disguising Personal Identity Information in EEG SignalsCode1
Dreamento: an open-source dream engineering toolbox for sleep EEG wearablesCode1
DTP-Net: Learning to Reconstruct EEG signals in Time-Frequency Domain by Multi-scale Feature ReuseCode1
EEG2Mel: Reconstructing Sound from Brain Responses to MusicCode1
Subject-Aware Contrastive Learning for BiosignalsCode1
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Benchmark Results

#ModelMetricClaimedVerifiedStatus
1BiHDMAccuracy74.35Unverified
2DGCNNAccuracy69.88Unverified
3DBNAccuracy66.77Unverified
#ModelMetricClaimedVerifiedStatus
1MultitaskSSVEPAccuracy (5-fold)92.2Unverified
#ModelMetricClaimedVerifiedStatus
1DBNAccuracy86.08Unverified