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 226–250 of 1655 papers

TitleStatusHype
User-wise Perturbations for User Identity Protection in EEG-Based BCIs—0
Alignment-Based Adversarial Training (ABAT) for Improving the Robustness and Accuracy of EEG-Based BCIsCode0
Personalized Continual EEG Decoding: Retaining and Transferring Knowledge—0
Demo: Multi-Modal Seizure Prediction System—0
Feature Selection via Dynamic Graph-based Attention Block in MI-based EEG Signals—0
EEG-based Multimodal Representation Learning for Emotion Recognition—0
A Multi-Modal Non-Invasive Deep Learning Framework for Progressive Prediction of Seizures—0
A contrastive-learning approach for auditory attention detection—0
Real-time Sub-milliwatt Epilepsy Detection Implemented on a Spiking Neural Network Edge Inference Processor—0
EEGPT: Unleashing the Potential of EEG Generalist Foundation Model by Autoregressive Pre-training—0
SlimSeiz: Efficient Channel-Adaptive Seizure Prediction Using a Mamba-Enhanced NetworkCode0
EEG-based AI-BCI Wheelchair Advancement: A Brain-Computer Interfacing Wheelchair System Using Deep Learning Approach—0
Simulated Eyeblink Artifact Removal with ICA: Effect of Measurement Uncertainty—0
From Epilepsy Seizures Classification to Detection: A Deep Learning-based Approach for Raw EEG Signals—0
Sonic Entanglements with Electromyography: Between Bodies, Signals, and Representations—0
Multi-modal Cross-domain Self-supervised Pre-training for fMRI and EEG Fusion—0
Translating Mental Imaginations into Characters with Codebooks and Dynamics-Enhanced Decoding—0
Designing Pre-training Datasets from Unlabeled Data for EEG Classification with Transformers—0
BrainDreamer: Reasoning-Coherent and Controllable Image Generation from EEG Brain Signals via Language Guidance—0
Differentially Private Multimodal Laplacian Dropout (DP-MLD) for EEG Representative Learning—0
Optimizing food taste sensory evaluation through neural network-based taste electroencephalogram channel selection—0
Geometry-Constrained EEG Channel Selection for Brain-Assisted Speech Enhancement—0
Enhancing EEG Signal Generation through a Hybrid Approach Integrating Reinforcement Learning and Diffusion Models—0
A Comprehensive Comparison Between ANNs and KANs For Classifying EEG Alzheimer's Data—0
Complex Emotion Recognition System using basic emotions via Facial Expression, EEG, and ECG Signals: a review—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