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 201–225 of 1655 papers

TitleStatusHype
Transfer Learning for Covert Speech Classification Using EEG Hilbert Envelope and Temporal Fine Structure—0
SSRepL-ADHD: Adaptive Complex Representation Learning Framework for ADHD Detection from Visual Attention Tasks—0
Machine Learning Fairness for Depression Detection using EEG Data—0
Cueless EEG imagined speech for subject identification: dataset and benchmarksCode0
On the challenges of detecting MCI using EEG in the wildCode0
On Creating A Brain-To-Text Decoder—0
AADNet: Exploring EEG Spatiotemporal Information for Fast and Accurate Orientation and Timbre Detection of Auditory Attention Based on A Cue-Masked Paradigm—0
LG-Sleep: Local and Global Temporal Dependencies for Mice Sleep Scoring—0
Canine EEG Helps Human: Cross-Species and Cross-Modality Epileptic Seizure Detection via Multi-Space Alignment—0
A3E: Aligned and Augmented Adversarial Ensemble for Accurate, Robust and Privacy-Preserving EEG Decoding—0
SCFNet:A Transferable IIIC EEG Classification Network—0
EEG-GMACN: Interpretable EEG Graph Mutual Attention Convolutional Network—0
Adversarial Filtering Based Evasion and Backdoor Attacks to EEG-Based Brain-Computer InterfacesCode0
STEAM-EEG: Spatiotemporal EEG Analysis with Markov Transfer Fields and Attentive CNNs—0
Multi-Branch Mutual-Distillation Transformer for EEG-Based Seizure Subtype Classification—0
Effect of Simulated Space Conditions on functional Connectivity—0
Protecting Multiple Types of Privacy Simultaneously in EEG-based Brain-Computer Interfaces—0
Knowledge-Data Fusion Based Source-Free Semi-Supervised Domain Adaptation for Seizure Subtype Classification—0
Revisiting Your Memory: Reconstruction of Affect-Contextualized Memory via EEG-guided Audiovisual Generation—0
Implementation of tools for lessening the influence of artifacts in EEG signal analysis—0
Enhanced Cross-Dataset Electroencephalogram-based Emotion Recognition using Unsupervised Domain AdaptationCode0
Hierarchical Trait-State Model for Decoding Dyadic Social Interactions—0
Uncovering the role of semantic and acoustic cues in normal and dichotic listening—0
Towards Scalable Handwriting Communication via EEG Decoding and Latent Embedding Integration—0
Multi-class Decoding of Attended Speaker Direction Using Electroencephalogram and Audio Spatial Spectrum—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