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 151–200 of 1655 papers

TitleStatusHype
Heart Rate Estimation from Face Videos for Student Assessment: Experiments on edBBCode1
EEG-TCNet: An Accurate Temporal Convolutional Network for Embedded Motor-Imagery Brain-Machine InterfacesCode1
RED: Deep Recurrent Neural Networks for Sleep EEG Event DetectionCode1
K-EmoCon, a multimodal sensor dataset for continuous emotion recognition in naturalistic conversationsCode1
Augmenting interictal mapping with neurovascular coupling biomarkers by structured factorization of epileptic EEG and fMRI dataCode1
Federated Transfer Learning for EEG Signal ClassificationCode1
TSception: A Deep Learning Framework for Emotion Detection Using EEGCode1
Ultra Efficient Transfer Learning with Meta Update for Cross Subject EEG ClassificationCode1
Machine-Learning-Based Diagnostics of EEG PathologyCode1
Tiny noise, big mistakes: Adversarial perturbations induce errors in Brain-Computer Interface spellersCode1
REST: Robust and Efficient Neural Networks for Sleep Monitoring in the WildCode1
edBB: Biometrics and Behavior for Assessing Remote EducationCode1
U-Time: A Fully Convolutional Network for Time Series Segmentation Applied to Sleep StagingCode1
A few filters are enough: Convolutional Neural Network for P300 DetectionCode1
Multi-task Generative Adversarial Learning on Geometrical Shape Reconstruction from EEG Brain SignalsCode1
EEG-Based Emotion Recognition Using Regularized Graph Neural NetworksCode1
EEG-based Emotional Video Classification via Learning Connectivity StructureCode1
Transfer Learning for Brain-Computer Interfaces: A Euclidean Space Data Alignment ApproachCode1
EEG-GAN: Generative adversarial networks for electroencephalograhic (EEG) brain signalsCode1
A deep learning architecture for temporal sleep stage classification using multivariate and multimodal time seriesCode1
Deep learning with convolutional neural networks for EEG decoding and visualizationCode1
DeepSleepNet: a Model for Automatic Sleep Stage Scoring based on Raw Single-Channel EEGCode1
An IoT Endpoint System-on-Chip for Secure and Energy-Efficient Near-Sensor AnalyticsCode1
EEGNet: A Compact Convolutional Network for EEG-based Brain-Computer InterfacesCode1
SGDR: Stochastic Gradient Descent with Warm RestartsCode1
Online SSVEP-based BCI using Riemannian geometryCode1
AFPM: Alignment-based Frame Patch Modeling for Cross-Dataset EEG Decoding—0
EEG Foundation Challenge: From Cross-Task to Cross-Subject EEG Decoding—0
Brain2Vec: A Deep Learning Framework for EEG-Based Stress Detection Using CNN-LSTM-Attention—0
Dataset combining EEG, eye-tracking, and high-speed video for ocular activity analysis across BCI paradigmsCode0
Channel-Imposed Fusion: A Simple yet Effective Method for Medical Time Series Classification—0
Advancing Brainwave Modeling with a Codebook-Based Foundation Model—0
EEG-Based Inter-Patient Epileptic Seizure Detection Combining Domain Adversarial Training with CNN-BiLSTM Network—0
Robust Emotion Recognition via Bi-Level Self-Supervised Continual Learning—0
Pretraining Large Brain Language Model for Active BCI: Silent Speech—0
A Simple Review of EEG Foundation Models: Datasets, Advancements and Future Perspectives—0
The use of Multi-domain Electroencephalogram Representations in the building of Models based on Convolutional and Recurrent Neural Networks for Epilepsy DetectionCode0
A Statistical Approach for Synthetic EEG Data GenerationCode0
Siamese Network with Dual Attention for EEG-Driven Social Learning: Bridging the Human-Robot Gap in Long-Tail Autonomous Driving—0
Artifact detection and localization in single-channel mobile EEG for sleep research using deep learning and attention mechanisms—0
Classification of ADHD and Healthy Children Using EEG Based Multi-Band Spatial Features Enhancement—0
Optimized Feature Selection and Neural Network-Based Classification of Motor Imagery Using EEG Signals—0
Chirp Localization via Fine-Tuned Transformer Model: A Proof-of-Concept Study—0
Insights into Schizophrenia: Leveraging Machine Learning for Early Identification via EEG, ERP, and Demographic Attributes—0
Cross-Subject Depression Level Classification Using EEG Signals with a Sample Confidence Method—0
Toward Scalable Access to Neurodevelopmental Screening: Insights, Implementation, and Challenges—0
Music Therapy based Stress Prediction using Homological Feature Analysis on EEG Signals—0
EEGM2: An Efficient Mamba-2-Based Self-Supervised Framework for Long-Sequence EEG Modeling—0
M2LADS Demo: A System for Generating Multimodal Learning Analytics Dashboards—0
Revisiting Euclidean Alignment for Transfer Learning in EEG-Based Brain-Computer Interfaces—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