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

Recently AddedMost HypedMost ActiveNeeds VerificationMost Verified

Showing 951–975 of 1655 papers

TitleStatusHype
Towards Scalable Handwriting Communication via EEG Decoding and Latent Embedding Integration—0
Towards the bio-personalization of music recommendation systems: A single-sensor EEG biomarker of subjective music preference—0
Towards the Classification of Error-Related Potentials using Riemannian Geometry—0
Towards Using EEG to Improve ASR Accuracy—0
Toward the application of XAI methods in EEG-based systems—0
Tracé alternant detector for grading hypoxic-ischemic encephalopathy in neonatal EEG—0
Tracking momentary attention fluctuations with an EEG-based cognitive brain-machine interface—0
Training on the test set? An analysis of Spampinato et al. [arXiv:1609.00344]—0
Traitement audiovisuel lors d'une t\^ache de discrimination syllabique : une \'etude EEG/IRMf simultan\'ee (Audiovisual processing in syllabic discrimination task: a simultaneous fMRI-EEG study) [in French]—0
Transcranial low-level laser stimulation in near infrared-II region for brain safety and protection—0
Transfer entropy applied on EEG in depression reveals aberrated dynamics—0
Transfer Learning and SpecAugment applied to SSVEP Based BCI Classification—0
Transfer Learning Enhanced Common Spatial Pattern Filtering for Brain Computer Interfaces (BCIs): Overview and a New Approach—0
Transfer Learning for Covert Speech Classification Using EEG Hilbert Envelope and Temporal Fine Structure—0
Transfer Learning for EEG-Based Brain-Computer Interfaces: A Review of Progress Made Since 2016—0
Transfer Learning in Brain-Computer Interfaces with Adversarial Variational Autoencoders—0
Transferring Subspaces Between Subjects in Brain-Computer Interfacing—0
Transformer Convolutional Neural Networks for Automated Artifact Detection in Scalp EEG—0
Translating Mental Imaginations into Characters with Codebooks and Dynamics-Enhanced Decoding—0
Transmodal Analysis of Neural Signals—0
Trends in Machine Learning and Electroencephalogram (EEG): A Review for Undergraduate Researchers—0
TRIER: Template-Guided Neural Networks for Robust and Interpretable Sleep Stage Identification from EEG Recordings—0
Tuning to non-veridical features in attention and perceptual decision-making—0
Two-step Input Spatial Auditory BCI for Japanese Kana Characters—0
Uncovering the role of semantic and acoustic cues in normal and dichotic listening—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