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 1001–1025 of 1655 papers

TitleStatusHype
Real-time Sub-milliwatt Epilepsy Detection Implemented on a Spiking Neural Network Edge Inference Processor—0
Real Time Vigilance Detection using Frontal EEG—0
Recognition of Advertisement Emotions with Application to Computational Advertising—0
Reconfiguration of Brain Network between Resting-state and Oddball Paradigm—0
Reconsidering Spatial Priors In EEG Source Estimation: Does White Matter Contribute to EEG Rhythms?—0
Reconstructing ERP Signals Using Generative Adversarial Networks for Mobile Brain-Machine Interface—0
Reconstructing Visual Stimulus Images from EEG Signals Based on Deep Visual Representation Model—0
Recovering Arrhythmic EEG Transients from Their Stochastic Interference—0
Reduced integration and improved segregation of functional brain networks in Alzheimer's disease—0
Reduced neural activity during volatile anesthesia compared to TIVA: evidence from a novel EEG signal processing analysis—0
Reducing training requirements through evolutionary based dimension reduction and subject transfer—0
Relate auditory speech to EEG by shallow-deep attention-based network—0
Relating EEG recordings to speech using envelope tracking and the speech-FFR—0
Relating EEG to continuous speech using deep neural networks: a review—0
Relating the fundamental frequency of speech with EEG using a dilated convolutional network—0
Relationship Between Mood, Sleepiness, and EEG Functional Connectivity by 40 Hz Monaural Beats—0
Reliability and validity of TMS-EEG biomarkers—0
Removal of Ocular Artifacts in EEG Using Deep Learning—0
REPAC: Reliable estimation of phase-amplitude coupling in brain networks—0
EPOC Emotiv EEG Basics—0
Representation learning for improved interpretability and classification accuracy of clinical factors from EEG—0
Reputation-Based Federated Learning Defense to Mitigate Threats in EEG Signal Classification—0
Residual Deep Convolutional Neural Network for EEG Signal Classification in Epilepsy—0
ResOT: Resource-Efficient Oblique Trees for Neural Signal Classification—0
Resting state brain networks from EEG: Hidden Markov states vs. classical microstates—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