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

Recently AddedMost HypedMost ActiveNeeds VerificationMost Verified

Showing 1101–1150 of 1655 papers

TitleStatusHype
Sparse Bayesian Learning for EEG Source Localization—0
Sparse Dynamical Features generation, application to Parkinson's Disease diagnosis—0
Sparsity-based Correction of Exponential Artifacts—0
Sparsity-Driven EEG Channel Selection for Brain-Assisted Speech Enhancement—0
Sparsity Enables Estimation of both Subcortical and Cortical Activity from MEG and EEG—0
Spatial Filtering for Brain Computer Interfaces: A Comparison between the Common Spatial Pattern and Its Variant—0
Spatial Filtering for EEG-Based Regression Problems in Brain-Computer Interface (BCI)—0
Spatial Filtering Pipeline Evaluation of Cortically Coupled Computer Vision System for Rapid Serial Visual Presentation—0
Spatial Neural Networks and their Functional Samples: Similarities and Differences—0
Spatial-Spectral Boosting Analysis for Stroke Patients' Motor Imagery EEG in Rehabilitation Training—0
Spatial-Temporal Recurrent Neural Network for Emotion Recognition—0
Generative AI Enables EEG Super-Resolution via Spatio-Temporal Adaptive Diffusion Learning—0
Spatio-Temporal Analysis of Transformer based Architecture for Attention Estimation from EEG—0
Spatiotemporal Sparse Bayesian Learning with Applications to Compressed Sensing of Multichannel Physiological Signals—0
Spatio-temporal Spike and Slab Priors for Multiple Measurement Vector Problems—0
Spatio-Temporal Structured Sparse Regression with Hierarchical Gaussian Process Priors—0
Speaker Identification using EEG—0
Spectral independent component analysis with noise modeling for M/EEG source separation—0
Spectrally Adaptive Common Spatial Patterns—0
Spectro Temporal EEG Biomarkers For Binary Emotion Classification—0
Speech Artifact Removal from EEG Recordings of Spoken Word Production with Tensor Decomposition—0
Speech Recognition using EEG signals recorded using dry electrodes—0
Speech Recognition with no speech or with noisy speech—0
Speech Recognition With No Speech Or With Noisy Speech Beyond English—0
Speech Synthesis using EEG—0
SPLICE: Fully Tractable Hierarchical Extension of ICA with Pooling—0
Spoken Speech Enhancement using EEG—0
SSGCNet: A Sparse Spectra Graph Convolutional Network for Epileptic EEG Signal Classification—0
SSRepL-ADHD: Adaptive Complex Representation Learning Framework for ADHD Detection from Visual Attention Tasks—0
Stabilizing Subject Transfer in EEG Classification with Divergence Estimation—0
Staging Epileptogenesis with Deep Neural Networks—0
Stance leg and surface stability modulate cortical activity during human single leg stance—0
Stationarity of Time-Series on Graph via Bivariate Translation Invariance—0
Stationary and Sparse Denoising Approach for Corticomuscular Causality Estimation—0
StationPlot: A New Non-stationarity Quantification Tool for Detection of Epileptic Seizures—0
Statistical control for spatio-temporal MEG/EEG source imaging with desparsified mutli-task Lasso—0
STEAM-EEG: Spatiotemporal EEG Analysis with Markov Transfer Fields and Attentive CNNs—0
STILN: A Novel Spatial-Temporal Information Learning Network for EEG-based Emotion Recognition—0
StrokeSight: A Novel EEG-Based Diagnostic System for Strokes Using Spectral Analysis and Deep Learning—0
Structure-Preserving Graph Kernel for Brain Network Classification—0
Studying Drowsiness Detection Performance while Driving through Scalable Machine Learning Models using Electroencephalography—0
Study of cognitive component of auditory attention to natural speech events—0
Study on Compressed Sensing of Action Potential—0
Sub-100uW Multispectral Riemannian Classification for EEG-based Brain--Machine Interfaces—0
Subject-independent trajectory prediction using pre-movement EEG during grasp and lift task—0
Subject-Independent Brain-Computer Interface for Decoding High-Level Visual Imagery Tasks—0
Subject-Independent Brain-Computer Interfaces with Open-Set Subject Recognition—0
Subject-Independent Deep Architecture for EEG-based Motor Imagery Classification—0
Subject independent EEG-based BCI decoding—0
Subject Independent Emotion Recognition using EEG Signals Employing Attention Driven Neural Networks—0
Show:102550
← PrevPage 23 of 34Next →
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