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 701–750 of 1655 papers

TitleStatusHype
MutualGraphNet: A novel model for motor imagery classification—0
Automatic Diagnosis of Schizophrenia in EEG Signals Using CNN-LSTM Models—0
Seizure Classification of EEG based on Wavelet Signal Denoising Using a Novel Channel Selection Algorithm—0
EEG-connectivity: A fundamental guide and checklist for optimal study design and evaluation—0
An Electroencephalography connectome predictive model of major depressive disorder severity—0
DeepSleepNet-Lite: A Simplified Automatic Sleep Stage Scoring Model with Uncertainty Estimates—0
EEG-based Classification of Drivers Attention using Convolutional Neural Network—0
Pediatric Automatic Sleep Staging: A comparative study of state-of-the-art deep learning methods—0
Electroencephalogram Signal Processing with Independent Component Analysis and Cognitive Stress Classification using Convolutional Neural Networks—0
Using growth transform dynamical systems for spatio-temporal data sonification—0
An End-to-End Deep Learning Approach for Epileptic Seizure Prediction—0
Multiscale Wavelet Transfer Entropy with Application to Corticomuscular Coupling Analysis—0
Random Convolution Kernels with Multi-Scale Decomposition for Preterm EEG Inter-burst DetectionCode0
Towards a Better Understanding Human Reading Comprehension with Brain SignalsCode0
Open and free EEG datasets for epilepsy diagnosisCode0
Single-Channel EEG Based Arousal Level Estimation Using Multitaper Spectrum Estimation at Low-Power Wearable Devices—0
On the interpretation of linear Riemannian tangent space model parameters in M/EEGCode0
A SPA-based Manifold Learning Framework for Motor Imagery EEG Data Classification—0
EEG multipurpose eye blink detector using convolutional neural network—0
OpenSync: An opensource platform for synchronizing multiple measures in neuroscience experimentsCode0
The Portiloop: a deep learning-based open science tool for closed-loop brain stimulationCode0
Deep Recurrent Semi-Supervised EEG Representation Learning for Emotion Recognition—0
A Multi-objective Evolutionary Algorithm for EEG Inverse Problem—0
High Frequency EEG Artifact Detection with Uncertainty via Early Exit Paradigm—0
Interpretable SincNet-based Deep Learning for Emotion Recognition from EEG brain activityCode1
Sleep Staging Based on Multi Scale Dual Attention Network—0
Classification of Upper Arm Movements from EEG signals using Machine Learning with ICA Analysis—0
MS-MDA: Multisource Marginal Distribution Adaptation for Cross-subject and Cross-session EEG Emotion RecognitionCode1
Motor Imagery Classification based on CNN-GRU Network with Spatio-Temporal Feature Representation—0
DAL: Feature Learning from Overt Speech to Decode Imagined Speech-based EEG Signals with Convolutional Autoencoder—0
Noise-based cyberattacks generating fake P300 waves in brain–computer interfacesCode0
EEG-ConvTransformer for Single-Trial EEG based Visual Stimuli ClassificationCode1
Sleep syndromes onset detection based on automatic sleep staging algorithmCode0
Complex common spatial patterns on time-frequency decomposed EEG for brain-computer interfaceCode0
Complex network modelling of EEG band coupling in dyslexia: an exploratory analysis of auditory processing and diagnosis—0
Towards Natural Brain-Machine Interaction using Endogenous Potentials based on Deep Neural Networks—0
CADDA: Class-wise Automatic Differentiable Data Augmentation for EEG Signals—0
Learning Signal Representations for EEG Cross-Subject Channel Selection and Trial Classification—0
Extracting Different Levels of Speech Information from EEG Using an LSTM-Based ModelCode1
EEG-GNN: Graph Neural Networks for Classification of Electroencephalogram (EEG) Signals—0
Towards Long-term Non-invasive Monitoring for Epilepsy via Wearable EEG Devices—0
Cross-Subject Domain Adaptation for Classifying Working Memory Load with Multi-Frame EEG Images—0
BRAIN2DEPTH: Lightweight CNN Model for Classification of Cognitive States from EEG Recordings—0
Transformer-based Spatial-Temporal Feature Learning for EEG DecodingCode1
Artifact Detection and Correction in EEG data: A Review—0
Wheelchair automation by a hybrid BCI system using SSVEP and eye blinks—0
CogAlign: Learning to Align Textual Neural Representations to Cognitive Language Processing SignalsCode0
Neuroadaptive electroencephalography: a proof-of-principle study in infantsCode0
Subject-Independent Brain-Computer Interface for Decoding High-Level Visual Imagery Tasks—0
A highly scalable repository of waveform and vital signs data from bedside monitoring devices—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