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 601–650 of 1655 papers

TitleStatusHype
Brain-Supervised Image Editing—0
Brain Signals Analysis Based Deep Learning Methods: Recent advances in the study of non-invasive brain signals—0
Feature matching as improved transfer learning technique for wearable EEG—0
Uncertainty Detection and Reduction in Neural Decoding of EEG SignalsCode0
An EEG-based approach for Parkinson's disease diagnosis using Capsule network—0
Temporal Analysis of Functional Brain Connectivity for EEG-based Emotion Recognition—0
Multiple Time Series Fusion Based on LSTM An Application to CAP A Phase Classification Using EEGCode0
Sub-100uW Multispectral Riemannian Classification for EEG-based Brain--Machine Interfaces—0
AutoTransfer: Subject Transfer Learning with Censored Representations on Biosignals Data—0
Benchmarking Uncertainty Quantification on Biosignal Classification Tasks under Dataset Shift—0
ALEBk: Feasibility Study of Attention Level Estimation via Blink Detection applied to e-Learning—0
Confidence-Aware Subject-to-Subject Transfer Learning for Brain-Computer Interface—0
Overview of the EEG Pilot Subtask at MediaEval 2021: Predicting Media Memorability—0
Progressive Graph Convolution Network for EEG Emotion Recognition—0
Interpretable Convolutional Neural Networks for Subject-Independent Motor Imagery Classification—0
A Deep Knowledge Distillation framework for EEG assisted enhancement of single-lead ECG based sleep stagingCode1
Differential EEG Characteristics during Working Memory Encoding and Re-encoding—0
Reading Task Classification Using EEG and Eye-Tracking DataCode0
Overview of The MediaEval 2021 Predicting Media Memorability Task—0
Toward Open-World Electroencephalogram Decoding Via Deep Learning: A Comprehensive Survey—0
DriPP: Driven Point Processes to Model Stimuli Induced Patterns in M/EEG Signals—0
Open Vocabulary Electroencephalography-To-Text Decoding and Zero-shot Sentiment ClassificationCode1
Extracting seizure onset from surface EEG with Independent Component Analysis: insights from simultaneous scalp and intracerebral EEG—0
Embedding Decomposition for Artifacts Removal in EEG SignalsCode1
Comparison of inverse problem linear and non-linear methods for localization source: a combined TMS-EEG study—0
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