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 501–550 of 1655 papers

TitleStatusHype
Calibration of off-the-shelf low-cost wearable EEG headset for application in field studies—0
Removal of Ocular Artifacts in EEG Using Deep Learning—0
Avoiding Post-Processing with Event-Based Detection in Biomedical SignalsCode0
Modeling cognitive load as a self-supervised brain rate with electroencephalography and deep learning—0
U-Sleep's resilience to AASM guidelines—0
EEG-Based Epileptic Seizure Prediction Using Temporal Multi-Channel Transformers—0
Weight-based Channel-model Matrix Framework provides a reasonable solution for EEG-based cross-dataset emotion recognition—0
Identification of Cognitive Workload during Surgical Tasks with Multimodal Deep Learning—0
Examining Uniqueness and Permanence of the WAY EEG GAL dataset toward User Authentication—0
Studying Drowsiness Detection Performance while Driving through Scalable Machine Learning Models using Electroencephalography—0
Machine Learning For Classification Of Antithetical Emotional States—0
Subject-independent trajectory prediction using pre-movement EEG during grasp and lift task—0
SaleNet: A low-power end-to-end CNN accelerator for sustained attention level evaluation using EEG—0
EEG-based Emotion Recognition via Efficient Convolutional Neural Network and Contrastive Learning—0
Classification of eye-state using EEG recordings: speed-up gains using signal epochs and mutual information measure—0
Classification of Electroencephalograms during Mathematical Calculations Using Deep Learning—0
Finding neural signatures for obesity through feature selection on source-localized EEG—0
Periodic and non-periodic brainwaves emerging via random syncronization of closed loops of firing neurons—0
Development of Sleep State Trend (SST), a bedside measure of neonatal sleep state fluctuations based on single EEG channels—0
EEG4Students: An Experimental Design for EEG Data Collection and Machine Learning AnalysisCode0
Too Fine or Too Coarse? The Goldilocks Composition of Data Complexity for Robust Left-Right Eye-Tracking ClassifiersCode0
Convolutional Neural Networks with A Topographic Representation Module for EEG-Based Brain-Computer Interfaces—0
Locally temporal-spatial pattern learning with graph attention mechanism for EEG-based emotion recognition—0
EEG-BBNet: a Hybrid Framework for Brain Biometric using Graph Connectivity—0
KAM -- a Kernel Attention Module for Emotion Classification with EEG DataCode0
A Monotonicity Constrained Attention Module for Emotion Classification with Limited EEG DataCode0
Convolutional Spiking Neural Networks for Detecting Anticipatory Brain Potentials Using Electroencephalogram—0
Machine Learning-based EEG Applications and Markets—0
Classifier Transfer with Data Selection Strategies for Online Support Vector Machine Classification with Class Imbalance—0
EEG Machine Learning for Analysis of Mild Traumatic Brain Injury: A survey—0
Partial Least Square Regression via Three-factor SVD-type Manifold Optimization for EEG Decoding—0
Learning from imperfect training data using a robust loss function: application to brain image segmentationCode0
See What You See: Self-supervised Cross-modal Retrieval of Visual Stimuli from Brain Activity—0
Granger Causality using Neural NetworksCode0
On the relation between EEG microstates and cross-spectra—0
Decision SincNet: Neurocognitive models of decision making that predict cognitive processes from neural signalsCode0
Transformer Convolutional Neural Networks for Automated Artifact Detection in Scalp EEG—0
An intertwined neural network model for EEG classification in brain-computer interfaces—0
Neural Correlates of Face Familiarity Perception—0
Vector-Based Data Improves Left-Right Eye-Tracking Classifier Performance After a Covariate Distributional ShiftCode0
Six-center Assessment of CNN-Transformer with Belief Matching Loss for Patient-independent Seizure Detection in EEG—0
Significant changes in EEG neural oscillations during different phases of three-dimensional multiple object tracking task (3D-MOT) imply different roles for attention and working memory—0
A Hybrid Complex-valued Neural Network Framework with Applications to Electroencephalogram (EEG)—0
Time Majority Voting, a PC-based EEG Classifier for Non-expert UsersCode0
A Two-Stage Efficient 3-D CNN Framework for EEG Based Emotion Recognition—0
Continuous ErrP detections during multimodal human-robot interaction—0
LETS-GZSL: A Latent Embedding Model for Time Series Generalized Zero Shot Learning—0
Comment on "On the Extraction of Purely Motor EEG Neural Correlates during an Upper Limb Visuomotor Task"—0
TRUST-LAPSE: An Explainable and Actionable Mistrust Scoring Framework for Model MonitoringCode0
Correntropy-Based Logistic Regression with Automatic Relevance Determination for Robust Sparse Brain Activity Decoding—0
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Benchmark Results

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