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 251–275 of 1655 papers

TitleStatusHype
Automatic Diagnosis of Schizophrenia in EEG Signals Using CNN-LSTM Models—0
Automatic Electrodes Detection during simultaneous EEG/fMRI acquisition—0
Automatic Emotion Recognition (AER) System based on Two-Level Ensemble of Lightweight Deep CNN Models—0
Automatic Identification of Epileptic Seizures from EEG Signals using Sparse Representation-based Classification—0
Assessment of Unconsciousness for Memory Consolidation Using EEG Signals—0
A computational investigation of the relationships between single-neuron and network dynamics in the cerebral cortex—0
Assessment of Subjective Creativity Skill Using EEG Induced Capsule Network—0
A Multi-Modal Non-Invasive Deep Learning Framework for Progressive Prediction of Seizures—0
Robust Emotion Recognition via Bi-Level Self-Supervised Continual Learning—0
Biomagnetic signals recorded during transcranial magnetic stimulation (TMS)-evoked peripheral muscular activity—0
Biophysical aspects of neurocognitive modeling with long-term sustained temperature variations—0
Assessing Rate limits Using Behavioral and Neural Responses of Interaural-Time-Difference Cues in Fine-Structure and Envelope—0
Assessing learned features of Deep Learning applied to EEG—0
A multi-level interpretable sleep stage scoring system by infusing experts' knowledge into a deep network architecture—0
A Multi-Context Character Prediction Model for a Brain-Computer Interface—0
Assessing Functional Neural Connectivity as an Indicator of Cognitive Performance—0
Advancing Brainwave Modeling with a Codebook-Based Foundation Model—0
A Comprehensive Survey on EEG-Based Emotion Recognition: A Graph-Based Perspective—0
A SPA-based Manifold Learning Framework for Motor Imagery EEG Data Classification—0
A single channel sleep-spindle detector based on multivariate classification of EEG epochs: MUSSDET.—0
A Multi Constrained Transformer-BiLSTM Guided Network for Automated Sleep Stage Classification from Single-Channel EEG—0
A Simple Review of EEG Foundation Models: Datasets, Advancements and Future Perspectives—0
A simple EEG-based decision tool for neonatal therapeutic hypothermia in hypoxic-ischemic encephalopathy—0
A Multi-channel EEG Data Analysis for Poor Neuro-prognostication in Comatose Patients with Self and Cross-channel Attention Mechanism—0
Emotion Classification in Response to Tactile Enhanced Multimedia using Frequency Domain Features of Brain Signals—0
Show:102550
← PrevPage 11 of 67Next →
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