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 751–800 of 1655 papers

TitleStatusHype
A Novel Multi-scale Dilated 3D CNN for Epileptic Seizure Prediction—0
Epileptic seizure classification using statistical sampling and a novel feature selection algorithm—0
Epileptic Seizure Detection: A Deep Learning Approach—0
Epileptic Seizure Detection and Classification using Time-Frequency Features in EEG Signals—0
EEG Classification based on Image Configuration in Social Anxiety Disorder—0
Epileptic Seizure Forecasting: Probabilistic seizure-risk assessment and data-fusion—0
Epileptic Seizure Prediction: A Semi-Dilated Convolutional Neural Network Architecture—0
Epileptic seizure prediction using Pearson's product-moment correlation coefficient of a linear classifier from generalized Gaussian modeling—0
Epileptic Seizure Risk Assessment by Multi-Channel Imaging of the EEG—0
EpilNet: A Novel Approach to IoT based Epileptic Seizure Prediction and Diagnosis System using Artificial Intelligence—0
ESI-GAL: EEG Source Imaging-based Trajectory Estimation for Grasp and Lift Task—0
Estimating direction in brain-behavior interactions: Proactive and reactive brain states in driving—0
Estimating the Location and Orientation of Complex, Correlated Neural Activity using MEG—0
Estimating vector fields using sparse basis field expansions—0
Evaluation of algorithms for correction of transcranial magnetic stimulation induced artifacts in electroencephalograms—0
Brain waves are a repetition of a pause and an activity—0
EEG changes and motor deficits in Parkinson's disease patients: Correlation of motor scales and EEG power bands—0
Evaluation of Preference of Multimedia Content using Deep Neural Networks for Electroencephalography—0
Evaluation of techniques for predicting seizure Build up—0
EEG-BBNet: a Hybrid Framework for Brain Biometric using Graph Connectivity—0
A Novel Method for Epileptic Seizure Detection Using Coupled Hidden Markov Models—0
Examining Uniqueness and Permanence of the WAY EEG GAL dataset toward User Authentication—0
EEG-based video identification using graph signal modeling and graph convolutional neural network—0
EEG-Based User Reaction Time Estimation Using Riemannian Geometry Features—0
Brain-Supervised Image Editing—0
EEG-based Texture Roughness Classification in Active Tactile Exploration with Invariant Representation Learning Networks—0
EEG-based Subjects Identification based on Biometrics of Imagined Speech using EMD—0
Exploration of LLMs, EEG, and behavioral data to measure and support attention and sleep—0
Explore intrinsic geometry of sleep dynamics and predict sleep stage by unsupervised learning techniques—0
Complex network modelling of EEG band coupling in dyslexia: an exploratory analysis of auditory processing and diagnosis—0
Brain Source Localization by Alternating Projection—0
A Novel Independent RNN Approach to Classification of Seizures against Non-seizures—0
AI Neurotechnology for Aging Societies -- Task-load and Dementia EEG Digital Biomarker Development Using Information Geometry Machine Learning Methods—0
Extension of the non-parametric cluster-based time-frequency statistics to the full time windows and to single condition tests—0
Addressing Class Imbalance in Classification Problems of Noisy Signals by using Fourier Transform Surrogates—0
A CNN-Transformer Deep Learning Model for Real-time Sleep Stage Classification in an Energy-Constrained Wireless Device—0
AADNet: Exploring EEG Spatiotemporal Information for Fast and Accurate Orientation and Timbre Detection of Auditory Attention Based on A Cue-Masked Paradigm—0
EEG based stress analysis using rhythm specific spectral feature for video gameplay—0
EEG-based Sleep Staging with Hybrid Attention—0
Brain Signals to Rescue Aphasia, Apraxia and Dysarthria Speech Recognition—0
EEG-Based Reaction Time Prediction with Fuzzy Common Spatial Patterns and Phase Cohesion using Deep Autoencoder Based Data Fusion—0
EEG-based Multimodal Representation Learning for Emotion Recognition—0
Localization of MEG and EEG Brain Signals by Alternating Projection—0
A Novel Deep Learning Architecture for Decoding Imagined Speech from EEG—0
EEG-Based Inter-Patient Epileptic Seizure Detection Combining Domain Adversarial Training with CNN-BiLSTM Network—0
EEG-based Image Feature Extraction for Visual Classification using Deep Learning—0
Brain Signals Analysis Based Deep Learning Methods: Recent advances in the study of non-invasive brain signals—0
Feature Learning from Incomplete EEG with Denoising Autoencoder—0
EEG-Based Epileptic Seizure Prediction Using Temporal Multi-Channel Transformers—0
EEG Based Emotion Sensing using convolutional neural networks—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