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 851875 of 1655 papers

TitleStatusHype
Spatial-Temporal Recurrent Neural Network for Emotion Recognition0
Generative AI Enables EEG Super-Resolution via Spatio-Temporal Adaptive Diffusion Learning0
Spatio-Temporal Analysis of Transformer based Architecture for Attention Estimation from EEG0
Spatiotemporal Sparse Bayesian Learning with Applications to Compressed Sensing of Multichannel Physiological Signals0
Spatio-temporal Spike and Slab Priors for Multiple Measurement Vector Problems0
Spatio-Temporal Structured Sparse Regression with Hierarchical Gaussian Process Priors0
Speaker Identification using EEG0
Spectral independent component analysis with noise modeling for M/EEG source separation0
Spectrally Adaptive Common Spatial Patterns0
Spectro Temporal EEG Biomarkers For Binary Emotion Classification0
Speech Artifact Removal from EEG Recordings of Spoken Word Production with Tensor Decomposition0
Speech Recognition using EEG signals recorded using dry electrodes0
Speech Recognition with no speech or with noisy speech0
Speech Recognition With No Speech Or With Noisy Speech Beyond English0
Speech Synthesis using EEG0
SPLICE: Fully Tractable Hierarchical Extension of ICA with Pooling0
Spoken Speech Enhancement using EEG0
SSGCNet: A Sparse Spectra Graph Convolutional Network for Epileptic EEG Signal Classification0
SSRepL-ADHD: Adaptive Complex Representation Learning Framework for ADHD Detection from Visual Attention Tasks0
Stabilizing Subject Transfer in EEG Classification with Divergence Estimation0
Staging Epileptogenesis with Deep Neural Networks0
Stance leg and surface stability modulate cortical activity during human single leg stance0
Stationarity of Time-Series on Graph via Bivariate Translation Invariance0
Stationary and Sparse Denoising Approach for Corticomuscular Causality Estimation0
StationPlot: A New Non-stationarity Quantification Tool for Detection of Epileptic Seizures0
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Benchmark Results

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