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 1601–1650 of 1655 papers

TitleStatusHype
Common Spatial Generative Adversarial Networks based EEG Data Augmentation for Cross-Subject Brain-Computer Interface—0
Community Detection in Multi-frequency EEG Networks—0
Comparative Analysis of Epileptic Seizure Prediction: Exploring Diverse Pre-Processing Techniques and Machine Learning Models—0
Comparison of Attention-based Deep Learning Models for EEG Classification—0
Comparison of EEG based epilepsy diagnosis using neural networks and wavelet transform—0
Comparison of inverse problem linear and non-linear methods for localization source: a combined TMS-EEG study—0
Comparison of the P300 detection accuracy related to the BCI speller and image recognition scenarios—0
Compensated Integrated Gradients to Reliably Interpret EEG Classification—0
Complex Emotion Recognition System using basic emotions via Facial Expression, EEG, and ECG Signals: a review—0
Complexity Measures for Quantifying Changes in Electroencephalogram in Alzheimers Disease—0
Compressed Sensing for Energy-Efficient Wireless Telemonitoring: Challenges and Opportunities—0
Compressed Sensing of EEG for Wireless Telemonitoring with Low Energy Consumption and Inexpensive Hardware—0
Compressed Sensing of Multi-Channel EEG Signals: The Simultaneous Cosparsity and Low Rank Optimization—0
Accurate and efficient Simulation of very high-dimensional Neural Mass Models with distributed-delay Connectome Tensors—0
Computing extracellular electric potentials from neuronal simulations—0
Conex-Connect: Learning Patterns in Extremal Brain Connectivity From Multi-Channel EEG Data—0
Confidence-Aware Subject-to-Subject Transfer Learning for Brain-Computer Interface—0
Constrained Variational Autoencoder for improving EEG based Speech Recognition Systems—0
Contextual Minimum-Norm Estimates (CMNE): A Deep Learning Method for Source Estimation in Neuronal Networks—0
Continuous ErrP detections during multimodal human-robot interaction—0
Continuous monitoring of cognitive load using advanced computerized analysis of brain signals during virtual simulator training for laparoscopic surgery, reflects laparoscopic dexterity. A comparative study using a novel wireless device—0
Continuous Speech Recognition using EEG and Video—0
ConTraNet: A single end-to-end hybrid network for EEG-based and EMG-based human machine interfaces—0
Contrastive Learning of Shared Spatiotemporal EEG Representations Across Individuals for Naturalistic Neuroscience—0
Contrastive Learning of Subject-Invariant EEG Representations for Cross-Subject Emotion Recognition—0
Convolutional Neural Network Approach for EEG-based Emotion Recognition using Brain Connectivity and its Spatial Information—0
Convolutional Neural Networks for Automatic Detection of Artifacts from Independent Components Represented in Scalp Topographies of EEG Signals—0
Convolutional Neural Networks for Sleep Stage Scoring on a Two-Channel EEG Signal—0
Convolutional Neural Networks with A Topographic Representation Module for EEG-Based Brain-Computer Interfaces—0
Convolutional Spiking Neural Networks for Detecting Anticipatory Brain Potentials Using Electroencephalogram—0
Correlation based Multi-phasal models for improved imagined speech EEG recognition—0
Correntropy-Based Logistic Regression with Automatic Relevance Determination for Robust Sparse Brain Activity Decoding—0
Cortical Mirror-System Activation During Real-Life Game Playing: An Intracranial Electroencephalography (EEG) Study—0
Cortical recruitment and functional dynamics in postural control adaptation and habituation during vibratory proprioceptive stimulation—0
Cortical representations of Auditory Perception using Graph Independent Component on EEG—0
Cortical Xi-Alpha model for resting state electric neuronal activity—0
Covariance shrinkage for autocorrelated data—0
Covariate Shift Estimation based Adaptive Ensemble Learning for Handling Non-Stationarity in Motor Imagery related EEG-based Brain-Computer Interface—0
CropCat: Data Augmentation for Smoothing the Feature Distribution of EEG Signals—0
Cross-Correlation Based Discriminant Criterion for Channel Selection in Motor Imagery BCI Systems—0
Cross-individual Recognition of Emotions by a Dynamic Entropy based on Pattern Learning with EEG features—0
Cross-paradigm pretraining of convolutional networks improves intracranial EEG decoding—0
Canine EEG Helps Human: Cross-Species and Cross-Modality Epileptic Seizure Detection via Multi-Space Alignment—0
Cross-Subject Deep Transfer Models for Evoked Potentials in Brain-Computer Interface—0
Cross-Subject Depression Level Classification Using EEG Signals with a Sample Confidence Method—0
Cross-Subject Domain Adaptation for Classifying Working Memory Load with Multi-Frame EEG Images—0
Cross-Subject Statistical Shift Estimation for Generalized Electroencephalography-based Mental Workload Assessment—0
DAGAM: A Domain Adversarial Graph Attention Model for Subject Independent EEG-Based Emotion Recognition—0
DAL: Feature Learning from Overt Speech to Decode Imagined Speech-based EEG Signals with Convolutional Autoencoder—0
DASPS: A Database for Anxious States based on a Psychological Stimulation—0
Show:102550
← PrevPage 33 of 34Next →
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