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 1076–1100 of 1655 papers

TitleStatusHype
Siamese Neural Networks for EEG-based Brain-computer Interfaces—0
Side-aware Meta-Learning for Cross-Dataset Listener Diagnosis with Subjective Tinnitus—0
Significant changes in EEG neural oscillations during different phases of three-dimensional multiple object tracking task (3D-MOT) imply different roles for attention and working memory—0
Significant Low-dimensional Spectral-temporal Features for Seizure Detection—0
Simulated Eyeblink Artifact Removal with ICA: Effect of Measurement Uncertainty—0
Simultaneous induction of SSMVEP and SMR Using a Gaiting video stimulus: a novel hybrid brain-computer interface—0
Simultaneous Skull Conductivity and Focal Source Imaging from EEG Recordings with the help of Bayesian Uncertainty Modelling—0
Sinc-based convolutional neural networks for EEG-BCI-based motor imagery classification—0
Single-Channel EEG Based Arousal Level Estimation Using Multitaper Spectrum Estimation at Low-Power Wearable Devices—0
Single-channel EEG completion using Cascade Transformer—0
Single-channel EEG features during n-back task correlate with working memory load—0
BCGGAN: Ballistocardiogram artifact removal in simultaneous EEG-fMRI using generative adversarial network—0
Single-trial P300 Classification using PCA with LDA, QDA and Neural Networks—0
Sleep Analytics and Online Selective Anomaly Detection—0
Sleep Model -- A Sequence Model for Predicting the Next Sleep Stage—0
SLEEPNET: Automated Sleep Staging System via Deep Learning—0
Sleep Stage Classification: Scalability Evaluations of Distributed Approaches—0
Sleep Stage Classification Using Bidirectional LSTM in Wearable Multi-sensor Systems—0
Sleep Stage Classification Using a Pre-trained Deep Learning Model—0
Sleep Staging Based on Multi Scale Dual Attention Network—0
SleepTransformer: Automatic Sleep Staging with Interpretability and Uncertainty Quantification—0
Sonic Entanglements with Electromyography: Between Bodies, Signals, and Representations—0
SOUL: An Energy-Efficient Unsupervised Online Learning Seizure Detection Classifier—0
Source Aware Deep Learning Framework for Hand Kinematic Reconstruction using EEG Signal—0
Sparse algorithms for EEG source localization—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