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 1251–1275 of 1655 papers

TitleStatusHype
Explore intrinsic geometry of sleep dynamics and predict sleep stage by unsupervised learning techniques—0
Neural Causal Discovery with Learnable Input Noise—0
Mental Fatigue Monitoring using Brain Dynamics Preferences—0
A new model for the implementation of positive and negative emotion recognition—0
An Efficient Intelligent System for the Classification of Electroencephalography (EEG) Brain Signals using Nuclear Features for Human Cognitive Tasks—0
Automatic Emotion Recognition (AER) System based on Two-Level Ensemble of Lightweight Deep CNN Models—0
Universal Joint Feature Extraction for P300 EEG Classification using Multi-task Autoencoder—0
A Review on understanding Brain, and Memory Retention and Recall Processes using EEG and fMRI techniques—0
Towards a Passive BCI to Induce Lucid Dream—0
Attention-based Transfer Learning for Brain-computer Interface—0
End-to-end Sleep Staging with Raw Single Channel EEG using Deep Residual ConvNetsCode0
A Novel Task-Oriented Text Corpus in Silent Speech Recognition and its Natural Language Generation Construction Method—0
Signal2Image Modules in Deep Neural Networks for EEG ClassificationCode0
Classification of Two-channel Signals by Means of Genetic Programming—0
Hierarchical Deep Feature Learning For Decoding Imagined Speech From EEG—0
Deep Learning the EEG Manifold for Phonological Categorization from Active Thoughts—0
Human Intracranial EEG Quantitative Analysis and Automatic Feature Learning for Epileptic Seizure Prediction—0
Advancing NLP with Cognitive Language Processing SignalsCode0
A Many Objective Optimization Approach for Transfer Learning in EEG Classification—0
Recognition of Advertisement Emotions with Application to Computational Advertising—0
Understanding language-elicited EEG data by predicting it from a fine-tuned language model—0
On the Vulnerability of CNN Classifiers in EEG-Based BCIs—0
Information Theoretic Feature Transformation Learning for Brain Interfaces—0
Cortical Mirror-System Activation During Real-Life Game Playing: An Intracranial Electroencephalography (EEG) Study—0
Adversarial Deep Learning in EEG Biometrics—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