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 676–700 of 1655 papers

TitleStatusHype
EEGminer: Discovering Interpretable Features of Brain Activity with Learnable Filters—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-NeXt: A Modernized ConvNet for The Classification of Cognitive Activity from EEG—0
EEG Opto-processor: epileptic seizure detection using diffractive photonic computing units—0
EEGPT: Unleashing the Potential of EEG Generalist Foundation Model by Autoregressive Pre-training—0
EEG Representation Using Multi-instance Framework on The Manifold of Symmetric Positive Definite Matrices for EEG-based Computer Aided Diagnosis—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
EEG Signal Classification using Variational Mode Decomposition—0
EEG Signal Dimensionality Reduction and Classification using Tensor Decomposition and Deep Convolutional Neural Networks—0
A Novel RL-assisted Deep Learning Framework for Task-informative Signals Selection and Classification for Spontaneous BCIs—0
EEG-connectivity: A fundamental guide and checklist for optimal study design and evaluation—0
EEG classifier cross-task transfer to avoid training sessions in robot-assisted rehabilitation—0
EEG to fMRI Synthesis Benefits from Attentional Graphs of Electrode Relationships—0
EEG to fMRI Synthesis: Is Deep Learning a candidate?—0
CADDA: Class-wise Automatic Differentiable Data Augmentation for EEG Signals—0
Effective and Extensible Feature Extraction Method Using Genetic Algorithm-Based Frequency-Domain Feature Search for Epileptic EEG Multi-classification—0
Effective Correlates of Motor Imagery Performance based on Default Mode Network in Resting-State—0
A Novel Multi-scale Dilated 3D CNN for Epileptic Seizure Prediction—0
Effects of Images with Different Levels of Familiarity on EEG—0
EEG Classification based on Image Configuration in Social Anxiety Disorder—0
Effects of Stimulus Type and of Error-Correcting Code Design on BCI Speller Performance—0
Efficacy of Transformer Networks for Classification of Raw EEG Data—0
Brain waves are a repetition of a pause and an activity—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