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 626–650 of 1655 papers

TitleStatusHype
An Artificial Intelligence Browser Architecture (AIBA) For Our Kind and Others: A Voice Name System Speech implementation with two warrants, Wake Neutrality and Value Preservation of Personally Identifiable Information—0
Analysis of EEG frequency bands for Envisioned Speech RecognitionCode0
An EEG-Based Multi-Modal Emotion Database with Both Posed and Authentic Facial Actions for Emotion Analysis—0
MI-BMInet: An Efficient Convolutional Neural Network for Motor Imagery Brain--Machine Interfaces with EEG Channel Selection—0
A Cellular Automaton Model for the generation of Brainwaves—0
Towards physiology-informed data augmentation for EEG-based BCIs—0
StrokeSight: A Novel EEG-Based Diagnostic System for Strokes Using Spectral Analysis and Deep Learning—0
SSGCNet: A Sparse Spectra Graph Convolutional Network for Epileptic EEG Signal Classification—0
Analyzing EEG Data with Machine and Deep Learning: A Benchmark—0
EEG based Emotion Recognition: A Tutorial and Review—0
A Decomposition-Based Hybrid Ensemble CNN Framework for Driver Fatigue Recognition—0
Topological EEG Nonlinear Dynamics Analysis for Emotion Recognition—0
CNN-Aided Factor Graphs with Estimated Mutual Information Features for Seizure Detection—0
Ensemble plasticity and network adaptability in SNNs—0
Evaluation of Performance for Human In-Vivo Conductivity Estimation from EEG and sEEG Recorded in Simultaneous with Intracerebral Electrical Stimulation—0
EEG to fMRI Synthesis Benefits from Attentional Graphs of Electrode Relationships—0
NEMAR: An open access data, tools, and compute resource operating on NeuroElectroMagnetic data—0
A streamable large-scale clinical EEG dataset for Deep Learning—0
Benchmarking real-time algorithms for in-phase auditory stimulation of low amplitude slow waves with wearable EEG devices during sleep—0
DAGAM: A Domain Adversarial Graph Attention Model for Subject Independent EEG-Based Emotion Recognition—0
Mental State Classification Using Multi-graph Features—0
Novel techniques for improving NNetEn entropy calculation for short and noisy time series—0
Validating an SVM-based neonatal seizure detection algorithm for generalizability, non-inferiority and clinical efficacy—0
An Evaluation of the EEG alpha-to-theta and theta-to-alpha band Ratios as Indexes of Mental Workload—0
DGAFF: Deep Genetic Algorithm Fitness Formation for EEG Bio-Signal Channel Selection—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