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 1051–1075 of 1655 papers

TitleStatusHype
Emotion-robust EEG Classification for Motor Imagery—0
Feature selection for gesture recognition in Internet-of-Things for healthcare—0
Mu-suppression detection in motor imagery electroencephalographic signals using the generalized extreme value distribution—0
Attention Patterns Detection using Brain Computer Interfaces—0
Deep learning approaches for neural decoding: from CNNs to LSTMs and spikes to fMRI—0
Reconstructing ERP Signals Using Generative Adversarial Networks for Mobile Brain-Machine Interface—0
Predicting Video features from EEG and Vice versa—0
Classification of Visual Perception and Imagery based EEG Signals Using Convolutional Neural Networks—0
Epileptic Seizure Forecasting: Probabilistic seizure-risk assessment and data-fusion—0
Assessment of Unconsciousness for Memory Consolidation Using EEG Signals—0
Identifying trace alternant activity in neonatal EEG using an inter-burst detection approach—0
Grading the severity of hypoxic-ischemic encephalopathy in newborn EEG using a convolutional neural network—0
Early soft and flexible fusion of EEG and fMRI via tensor decompositions—0
A TSK-type Convolutional Recurrent Fuzzy Network for Predicting Driving Fatigue—0
Affective Brain-Computer Interfaces: A Tutorial to Choose Performance Measuring Metric—0
Prediction of Human Empathy based on EEG Cortical Asymmetry—0
Gradual Relation Network: Decoding Intuitive Upper Extremity Movement Imaginations Based on Few-Shot EEG Learning—0
Prediction of Memory Retrieval Performance Using Ear-EEG Signals—0
Deep Feature Mining via Attention-based BiLSTM-GCN for Human Motor Imagery Recognition—0
Towards Best Practices for Leveraging Human Language Processing Signals for Natural Language Processing—0
The Language of Brain Signals: Natural Language Processing of Electroencephalography Reports—0
The Little Prince in 26 Languages: Towards a Multilingual Neuro-Cognitive Corpus—0
Design of BCCWJ-EEG: Balanced Corpus with Human Electroencephalography—0
The Alice Datasets: fMRI \& EEG Observations of Natural Language Comprehension—0
Wireless User-Generic Ear 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