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 76–100 of 1655 papers

TitleStatusHype
clusterBMA: Bayesian model averaging for clusteringCode1
Correct block-design experiments mitigate temporal correlation bias in EEG classificationCode1
Cross Task Neural Architecture Search for EEG Signal ClassificationsCode1
2021 BEETL Competition: Advancing Transfer Learning for Subject Independence & Heterogenous EEG Data SetsCode1
A Transformer-based deep neural network model for SSVEP classificationCode1
A Knowledge Distillation Framework For Enhancing Ear-EEG Based Sleep Staging With Scalp-EEG DataCode1
Deep learning with convolutional neural networks for EEG decoding and visualizationCode1
A Compact and Interpretable Convolutional Neural Network for Cross-Subject Driver Drowsiness Detection from Single-Channel EEGCode1
Device JNEEG to convert Jetson Nano to brain-Computer interfaces. Short reportCode1
Domain-Invariant Representation Learning from EEG with Private EncodersCode1
Augmenting interictal mapping with neurovascular coupling biomarkers by structured factorization of epileptic EEG and fMRI dataCode1
A Deep Knowledge Distillation framework for EEG assisted enhancement of single-lead ECG based sleep stagingCode1
EEG2Mel: Reconstructing Sound from Brain Responses to MusicCode1
A Deep Learning Approach for the Segmentation of Electroencephalography Data in Eye Tracking ApplicationsCode1
EEG-based Cross-Subject Driver Drowsiness Recognition with an Interpretable Convolutional Neural NetworkCode1
A deep learning architecture for temporal sleep stage classification using multivariate and multimodal time seriesCode1
EEG Channel Interpolation Using Deep Encoder-decoder NetwoksCode1
EEG-ConvTransformer for Single-Trial EEG based Visual Stimuli ClassificationCode1
BEATS: An Open-Source, High-Precision, Multi-Channel EEG Acquisition Tool SystemCode1
Real-time noise cancellation with Deep LearningCode1
EEG-ITNet: An Explainable Inception Temporal Convolutional Network for Motor Imagery ClassificationCode1
Spatiotemporal patterns of adaptation-induced slow oscillations in a whole-brain model of slow-wave sleepCode1
EEG Synthetic Data Generation Using Probabilistic Diffusion ModelsCode1
ADformer: A Multi-Granularity Transformer for EEG-Based Alzheimer's Disease AssessmentCode1
An IoT Endpoint System-on-Chip for Secure and Energy-Efficient Near-Sensor AnalyticsCode1
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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