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 251–275 of 1655 papers

TitleStatusHype
Classification of epileptic seizures in EEG data based on iterative gated graph convolution networkCode0
On-device Learning of EEGNet-based Network For Wearable Motor Imagery Brain-Computer Interface—0
Decoding Human Emotions: Analyzing Multi-Channel EEG Data using LSTM Networks—0
A Comprehensive Survey on EEG-Based Emotion Recognition: A Graph-Based Perspective—0
Towards Linguistic Neural Representation Learning and Sentence Retrieval from Electroencephalogram Recordings—0
Exploration of LLMs, EEG, and behavioral data to measure and support attention and sleep—0
A Tale of Single-channel Electroencephalogram: Devices, Datasets, Signal Processing, Applications, and Future Directions—0
Improving EEG Classification Through Randomly Reassembling Original and Generated Data with Transformer-based Diffusion Models—0
Preictal Period Optimization for Deep Learning-Based Epileptic Seizure Prediction—0
EEGMamba: Bidirectional State Space Model with Mixture of Experts for EEG Multi-task Classification—0
How Homogenizing the Channel-wise Magnitude Can Enhance EEG Classification Model?—0
Topological Analysis of Seizure-Induced Changes in Brain Hierarchy Through Effective Connectivity—0
Transcranial low-level laser stimulation in near infrared-II region for brain safety and protection—0
Refining ADHD diagnosis with EEG: The impact of preprocessing and temporal segmentation on classification accuracyCode0
Generative AI Enables EEG Super-Resolution via Spatio-Temporal Adaptive Diffusion Learning—0
Adaptive Modality Balanced Online Knowledge Distillation for Brain-Eye-Computer based Dim Object DetectionCode0
Dynamical Embedding of Single Channel Electroencephalogram for Artifact Subspace ReconstructionCode0
Stationary and Sparse Denoising Approach for Corticomuscular Causality Estimation—0
Multimodal Physiological Signals Representation Learning via Multiscale Contrasting for Depression Recognition—0
You Only Acquire Sparse-channel (YOAS): A Unified Framework for Dense-channel EEG Generation—0
ESI-GAL: EEG Source Imaging-based Trajectory Estimation for Grasp and Lift Task—0
Wearable Device-Based Real-Time Monitoring of Physiological Signals: Evaluating Cognitive Load Across Different Tasks—0
Deep Jansen-Rit Parameter Inference for Model-Driven Analysis of Brain ActivityCode0
Using Explainable AI for EEG-based Reduced Montage Neonatal Seizure DetectionCode0
Speech Imagery BCI Training Using Game with a PurposeCode0
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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