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 1326–1350 of 1655 papers

TitleStatusHype
AFPM: Alignment-based Frame Patch Modeling for Cross-Dataset EEG Decoding—0
A framework for seizure detection using effective connectivity, graph theory and deep modular neural networks—0
A framework to reconcile frequency scaling measurements, from intracellular recordings, local-field potentials, up to EEG and MEG signals—0
A GA-based feature selection of the EEG signals by classification evaluation: Application in BCI systems—0
A Generalised Seizure Prediction with Convolutional Neural Networks for Intracranial and Scalp Electroencephalogram Data Analysis—0
A Generative Model to Synthesize EEG Data for Epileptic Seizure Prediction—0
A Hierarchical Fuzzy System for an Advanced Driving Assistance System—0
A Hierarchical Graph Signal Processing Approach to Inference from Spatiotemporal Signals—0
A highly scalable repository of waveform and vital signs data from bedside monitoring devices—0
A Human-Machine Joint Learning Framework to Boost Endogenous BCI Training—0
A hybrid automated detection of epileptic seizures in EEG based on wavelet and machine learning techniques—0
A Hybrid Brain-Computer Interface Using Motor Imagery and SSVEP Based on Convolutional Neural Network—0
A Hybrid Complex-valued Neural Network Framework with Applications to Electroencephalogram (EEG)—0
A Hybrid Deep Spatio-Temporal Attention-Based Model for Parkinson's Disease Diagnosis Using Resting State EEG Signals—0
AI Neurotechnology for Aging Societies -- Task-load and Dementia EEG Digital Biomarker Development Using Information Geometry Machine Learning Methods—0
A Knowledge-Driven Cross-view Contrastive Learning for EEG Representation—0
A large-scale evaluation framework for EEG deep learning architectures—0
ALEBk: Feasibility Study of Attention Level Estimation via Blink Detection applied to e-Learning—0
Algoritmos de minería de datos en la industria sanitaria—0
A Lightweight Domain Adversarial Neural Network Based on Knowledge Distillation for EEG-based Cross-subject Emotion Recognition—0
A Locally Adaptive Normal Distribution—0
Alpha Wavelet Power as a Biomarker of Antidepressant Treatment Response in Bipolar Depression—0
Alzheimer's Disease Diagnosis Based on Cognitive Methods in Virtual Environments and Emotions Analysis—0
A Machine Learning Approach to Automatic Classification of Eight Sleep Disorders—0
A machine learning model for identifying cyclic alternating patterns in the sleeping brain—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