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 651–675 of 1655 papers

TitleStatusHype
Causal interpretation rules for encoding and decoding models in neuroimaging—0
A Novel TSK Fuzzy System Incorporating Multi-view Collaborative Transfer Learning for Personalized Epileptic EEG Detection—0
A Knowledge-Driven Cross-view Contrastive Learning for EEG Representation—0
EEG functional connectivity and deep learning for automatic diagnosis of brain disorders: Alzheimer's disease and schizophrenia—0
Carbogen inhalation during Non-Convulsive Status Epilepticus: A quantitative analysis of EEG recordings—0
EEG Foundation Challenge: From Cross-Task to Cross-Subject EEG Decoding—0
EEG fingerprinting: subject specific signature based on the aperiodic component of power spectrum—0
Capsule Attention for Multimodal EEG-EOG Representation Learning with Application to Driver Vigilance Estimation—0
A Novel Transferability Attention Neural Network Model for EEG Emotion Recognition—0
EEG-Fest: Few-shot based Attention Network for Driver's Vigilance Estimation with EEG Signals—0
Canonical Polyadic Decomposition with Auxiliary Information for Brain Computer Interface—0
EEGFuseNet: Hybrid Unsupervised Deep Feature Characterization and Fusion for High-Dimensional EEG with An Application to Emotion Recognition—0
EEG emotion recognition using dynamical graph convolutional neural networks—0
EEGDnet: Fusing Non-Local and Local Self-Similarity for 1-D EEG Signal Denoising with 2-D Transformer—0
EEG-GMACN: Interpretable EEG Graph Mutual Attention Convolutional Network—0
EEG-GNN: Graph Neural Networks for Classification of Electroencephalogram (EEG) Signals—0
Can Musical Emotion Be Quantified With Neural Jitter Or Shimmer? A Novel EEG Based Study With Hindustani Classical Music—0
A novel spike-and-wave automatic detection in EEG signals—0
A Decomposition-Based Hybrid Ensemble CNN Framework for Driver Fatigue Recognition—0
EEG in the classroom: Synchronised neural recordings during video presentation—0
Calibration of off-the-shelf low-cost wearable EEG headset for application in field studies—0
EEG Cortical Source Feature based Hand Kinematics Decoding using Residual CNN-LSTM Neural Network—0
A Novel RL-assisted Deep Learning Framework for Task-informative Signals Selection and Classification for Spontaneous BCIs—0
EEG machine learning with Higuchi fractal dimension and Sample Entropy as features for successful detection of depression—0
EEG-connectivity: A fundamental guide and checklist for optimal study design and evaluation—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