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 1401–1450 of 1655 papers

TitleStatusHype
Residual Deep Convolutional Neural Network for EEG Signal Classification in Epilepsy—0
ResOT: Resource-Efficient Oblique Trees for Neural Signal Classification—0
Resting state brain networks from EEG: Hidden Markov states vs. classical microstates—0
Resting-state EEG sex classification using selected brain connectivity representation—0
Re-thinking EEG-based non-invasive brain interfaces: modeling and analysis—0
Rethinking Saliency Map: An Context-aware Perturbation Method to Explain EEG-based Deep Learning Model—0
Retrieving Event-related Human Brain Dynamics from Natural Sentence Reading—0
Review Dry and Non-Contact EEG Electrodes for 2010-2021 Years—0
Review of algorithms for predicting fatigue using EEG—0
Review of analytical instruments for EEG analysis—0
Review of Deep Representation Learning Techniques for Brain-Computer Interfaces and Recommendations—0
Review of Machine Learning Algorithms for Brain Stroke Diagnosis and Prognosis by EEG Analysis—0
Review of medical data analysis based on spiking neural networks—0
Review of Neural Networks in the EEG Signal Recognition—0
Review of the State-of-the-art on Bio-signal-based Brain-controlled Vehicles—0
Review on Classification Techniques used in Biophysiological Stress Monitoring—0
Revisiting Euclidean Alignment for Transfer Learning in EEG-Based Brain-Computer Interfaces—0
Revisiting the Application of Feature Selection Methods to Speech Imagery BCI Datasets—0
Revisiting Your Memory: Reconstruction of Affect-Contextualized Memory via EEG-guided Audiovisual Generation—0
Riemannian classification of EEG signals with missing values—0
Riemannian tangent space mapping and elastic net regularization for cost-effective EEG markers of brain atrophy in Alzheimer's disease—0
Ripple oscillations in the left temporal neocortex are associated with impaired verbal episodic memory encoding—0
Robust EEG-based Emotion Recognition Using an Inception and Two-sided Perturbation Model—0
Robust End-to-End Speaker Verification Using EEG—0
Robust Spatial Filtering with Beta Divergence—0
Robust Time-Series Retrieval Using Probabilistic Adaptive Segmental Alignment—0
ROS-Neuro Integration of Deep Convolutional Autoencoders for EEG Signal Compression in Real-time BCIs—0
SaleNet: A low-power end-to-end CNN accelerator for sustained attention level evaluation using EEG—0
Sample Dominance Aware Framework via Non-Parametric Estimation for Spontaneous Brain-Computer Interface—0
ScalingNet: extracting features from raw EEG data for emotion recognition—0
Scatter-based common spatial patterns -- a unified spatial filtering framework—0
SCFNet:A Transferable IIIC EEG Classification Network—0
Schizophrenia detection based on EEG using Recurrent Auto-Encoder framework—0
SCORE-IT: A Machine Learning-based Tool for Automatic Standardization of EEG Reports—0
SCRIB: Set-classifier with Class-specific Risk Bounds for Blackbox Models—0
Second Order Bilinear Discriminant Analysis for single trial EEG analysis—0
See What You See: Self-supervised Cross-modal Retrieval of Visual Stimuli from Brain Activity—0
Seizure Classification of EEG based on Wavelet Signal Denoising Using a Novel Channel Selection Algorithm—0
Epileptic Seizure Classification Using Combined Labels and a Genetic Algorithm—0
Seizure Detection using Least EEG Channels by Deep Convolutional Neural Network—0
Seizure pathways and seizure durations can vary independently within individual patients with focal epilepsy—0
Seizure Prediction Using Bidirectional LSTM—0
Selection of Proper EEG Channels for Subject Intention Classification Using Deep Learning—0
CLASH: Contrastive learning through alignment shifting to extract stimulus information from EEG—0
Self-supervised Learning for Electroencephalogram: A Systematic Survey—0
Semantic-aware Contrastive Learning for Electroencephalography-to-Text Generation with Curriculum Learning—0
Semi-automated Annotation of Signal Events in Clinical EEG Data—0
Semi-supervised Seizure Prediction with Generative Adversarial Networks—0
Semi-supervised Stacked Label Consistent Autoencoder for Reconstruction and Analysis of Biomedical Signals—0
Sensoring and Application of Multimodal Data for the Detection of Freezing of Gait in Parkinson's Disease—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