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 1576–1600 of 1655 papers

TitleStatusHype
Classification of Epileptic EEG Signals by Wavelet based CFC—0
Classification of eye-state using EEG recordings: speed-up gains using signal epochs and mutual information measure—0
Classification of grasping tasks based on EEG-EMG coherence—0
Classification of Hand Movements from EEG using a Deep Attention-based LSTM Network—0
Classification of Imagined Speech Using Siamese Neural Network—0
Classification of Perceived Human Stress using Physiological Signals—0
Classification of sleep stages from EEG, EOG and EMG signals by SSNet—0
Classification of Two-channel Signals by Means of Genetic Programming—0
Classification of Upper Arm Movements from EEG signals using Machine Learning with ICA Analysis—0
Classification of Visual Perception and Imagery based EEG Signals Using Convolutional Neural Networks—0
Classification of weak multi-view signals by sharing factors in a mixture of Bayesian group factor analyzers—0
Classifier Transfer with Data Selection Strategies for Online Support Vector Machine Classification with Class Imbalance—0
Classifying Single-Trial EEG during Motor Imagery with a Small Training Set—0
Classifying sleep-wake stages through recurrent neural networks using pulse oximetry signals—0
Classifying Songs with EEG—0
CLEEGN: A Convolutional Neural Network for Plug-and-Play Automatic EEG Reconstruction—0
Clinical translation of machine learning algorithms for seizure detection in scalp electroencephalography: systematic review—0
Cloud-based Deep Learning of Big EEG Data for Epileptic Seizure Prediction—0
CLPVG: Circular limited penetrable visibility graph as a new network model for time series—0
CNN-Aided Factor Graphs with Estimated Mutual Information Features for Seizure Detection—0
CogniFNN: A Fuzzy Neural Network Framework for Cognitive Word Embedding Evaluation—0
Coherence of Working Memory Study Between Deep Neural Network and Neurophysiology—0
Combining Euclidean Alignment and Data Augmentation for BCI decoding—0
Combining Generative and Discriminative Neural Networks for Sleep Stages Classification—0
Comment on "On the Extraction of Purely Motor EEG Neural Correlates during an Upper Limb Visuomotor Task"—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