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 401–425 of 1655 papers

TitleStatusHype
Novel Epileptic Seizure Detection Techniques and their Empirical Analysis—0
Temporal stability of intracranial EEG abnormality maps for localising epileptogenic tissue—0
Classification of BCI-EEG based on augmented covariance matrixCode0
Explainable Label-flipping Attacks on Human Emotion Assessment System—0
Data Poisoning Attacks on EEG Signal-based Risk Assessment Systems—0
First steps towards quantum machine learning applied to the classification of event-related potentials—0
Relating EEG to continuous speech using deep neural networks: a review—0
Biophysical aspects of neurocognitive modeling with long-term sustained temperature variations—0
The Past, Current, and Future of Neonatal Intensive Care Units with Artificial Intelligence—0
Variational Autoencoder Learns Better Feature Representations for EEG-based Obesity Classification—0
Approximating DTW with a convolutional neural network on EEG data—0
Cross-Subject Deep Transfer Models for Evoked Potentials in Brain-Computer Interface—0
Semantic-aware Contrastive Learning for Electroencephalography-to-Text Generation with Curriculum Learning—0
Interpretable Classification of Early Stage Parkinson's Disease from EEG—0
Self-Organization Towards 1/f Noise in Deep Neural NetworksCode0
Brain Model State Space Reconstruction Using an LSTM Neural Network—0
Deep Learning for scalp High Frequency Oscillations Identification—0
Subject-Independent Brain-Computer Interfaces with Open-Set Subject Recognition—0
Extracting continuous sleep depth from EEG data without machine learning—0
Explainable Data Poison Attacks on Human Emotion Evaluation Systems based on EEG SignalsCode0
Hearables: Ear EEG Based Driver Fatigue Detection—0
Machine learning techniques for the Schizophrenia diagnosis: A comprehensive review and future research directions—0
Interpretable and Scalable Graphical Models for Complex Spatio-temporal Processes—0
Functional Neural Networks: Shift invariant models for functional data with applications to EEG classification—0
Short-length SSVEP data extension by a novel generative adversarial networks based frameworkCode0
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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