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 426–450 of 1655 papers

TitleStatusHype
BiCurNet: Pre-Movement EEG based Neural Decoder for Biceps Curl Trajectory Estimation—0
CLASH: Contrastive learning through alignment shifting to extract stimulus information from EEG—0
Shorter Latency of Real-time Epileptic Seizure Detection via Probabilistic Prediction—0
Detecting Information Relays in Deep Neural Networks—0
Understanding EEG signals for subject-wise Definition of Armoni Activities—0
Neural criticality from effective latent variables—0
RaspberryPi to measure EEG, ECG, EMG and EOG with Shield PiEEG—0
Cortical Xi-Alpha model for resting state electric neuronal activity—0
MindBigData 2022 A Large Dataset of Brain Signals—0
AMDET: Attention based Multiple Dimensions EEG Transformer for Emotion Recognition—0
A Wearable EEG System for Closed-Loop Neuromodulation of High-Frequency Sleep-Related Oscillations—0
Deep Riemannian Networks for End-to-End EEG DecodingCode0
A unified information-theoretic model of EEG signatures of human language processing—0
Toward cross-subject and cross-session generalization in EEG-based emotion recognition: Systematic review, taxonomy, and methods—0
Hybrid Paradigm-based Brain-Computer Interface for Robotic Arm Control—0
Calibration-Free Driver Drowsiness Classification based on Manifold-Level AugmentationCode0
CropCat: Data Augmentation for Smoothing the Feature Distribution of EEG Signals—0
Classification of Distraction Levels Using Hybrid Deep Neural Networks From EEG Signals—0
Nonparametric Independent Component Analysis for the Sources with Mixed Spectra—0
Overview of The MediaEval 2022 Predicting Video Memorability Task—0
Changes in Power and Information Flow in Resting-state EEG by Working Memory Process—0
A Hybrid Brain-Computer Interface Using Motor Imagery and SSVEP Based on Convolutional Neural Network—0
Neural Underpinnings of Decoupled Ethical Behavior in Adolescents as an Interaction of Peer and Personal Values—0
EEG Opto-processor: epileptic seizure detection using diffractive photonic computing units—0
EEG-NeXt: A Modernized ConvNet for The Classification of Cognitive Activity from EEG—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