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 876–900 of 1655 papers

TitleStatusHype
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
Subject Selection on a Riemannian Manifold for Unsupervised Cross-subject Seizure Detection—0
Suitability of an inter-burst detection method for grading hypoxic-ischemic encephalopathy in newborn EEG—0
Supervised LogEuclidean Metric Learning for Symmetric Positive Definite Matrices—0
Switching EEG Headsets Made Easy: Reducing Offline Calibration Effort Using Active Weighted Adaptation Regularization—0
Symptoms of depersonalisation/derealisation disorder as measured by brain electrical activity: A systematic review—0
Synthesizing Affective Neurophysiological Signals Using Generative Models: A Review Paper—0
Target-centered Subject Transfer Framework for EEG Data Augmentation—0
Targeting EEG/LFP Synchrony with Neural Nets—0
Team Cogitat at NeurIPS 2021: Benchmarks for EEG Transfer Learning Competition—0
Temporal Analysis of Functional Brain Connectivity for EEG-based Emotion Recognition—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