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 626–650 of 1655 papers

TitleStatusHype
Scalable Machine Learning Architecture for Neonatal Seizure Detection on Ultra-Edge DevicesCode1
Automated Detection of Patients in Hospital Video Recordings—0
Evaluation of Interpretability for Deep Learning algorithms in EEG Emotion Recognition: A case study in AutismCode1
Are Brain-Computer Interfaces Feasible with Integrated Photonic Chips?—0
Subject-Independent Drowsiness Recognition from Single-Channel EEG with an Interpretable CNN-LSTM modelCode1
Structure-Preserving Graph Kernel for Brain Network Classification—0
Novel EEG based Schizophrenia Detection with IoMT Framework for Smart Healthcare—0
IC-U-Net: A U-Net-based Denoising Autoencoder Using Mixtures of Independent Components for Automatic EEG Artifact RemovalCode1
Reconsidering Spatial Priors In EEG Source Estimation: Does White Matter Contribute to EEG Rhythms?—0
Multi-Centroid Hyperdimensional Computing Approach for Epileptic Seizure DetectionCode0
A Time-Series Scale Mixture Model of EEG with a Hidden Markov Structure for Epileptic Seizure Detection—0
A Novel TSK Fuzzy System Incorporating Multi-view Collaborative Transfer Learning for Personalized Epileptic EEG Detection—0
Symptoms of depersonalisation/derealisation disorder as measured by brain electrical activity: A systematic review—0
Benefit-aware Early Prediction of Health Outcomes on Multivariate EEG Time Series—0
Assessing learned features of Deep Learning applied to EEG—0
EEGEyeNet: a Simultaneous Electroencephalography and Eye-tracking Dataset and Benchmark for Eye Movement PredictionCode1
Automated Human Mind Reading Using EEG Signals for Seizure Detection—0
EpilNet: A Novel Approach to IoT based Epileptic Seizure Prediction and Diagnosis System using Artificial Intelligence—0
Neural Network Based Epileptic EEG Detection and Classification—0
EEG-Based Emotion Recognition Using Genetic Algorithm Optimized Multi-Layer PerceptronCode1
Application of Machine Learning to Sleep Stage Classification—0
Automatic Sleep Staging of EEG Signals: Recent Development, Challenges, and Future Directions—0
Synthesizing Speech from Intracranial Depth Electrodes using an Encoder-Decoder FrameworkCode1
Efficient Hierarchical Bayesian Inference for Spatio-temporal Regression Models in NeuroimagingCode0
Self-supervised EEG Representation Learning for Automatic Sleep StagingCode1
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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