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 851–875 of 1655 papers

TitleStatusHype
Machine Learning Applications on Neuroimaging for Diagnosis and Prognosis of Epilepsy: A Review—0
FOIT: Fast Online Instance Transfer for Improved EEG Emotion RecognitionCode0
Probabilistic Learning Vector Quantization on Manifold of Symmetric Positive Definite Matrices—0
A Novel Use of Discrete Wavelet Transform Features in the Prediction of Epileptic Seizures from EEG DataCode0
Study on Compressed Sensing of Action Potential—0
Mining the Mind: Linear Discriminant Analysis of MEG source reconstruction time series supports dynamic changes in deep brain regions during meditation sessions—0
BENDR: using transformers and a contrastive self-supervised learning task to learn from massive amounts of EEG dataCode1
Efficient Video Summarization Framework using EEG and Eye-tracking Signals—0
EEG-Inception: An Accurate and Robust End-to-End Neural Network for EEG-based Motor Imagery ClassificationCode1
A Raspberry Pi-based Traumatic Brain Injury Detection System for Single-Channel Electroencephalogram—0
Online LDA based brain-computer interface system to aid disabled people—0
Analysis of Relation between Motor Activity and Imaginary EEG Records—0
Generative Autoencoder Kernels on Deep Learning for Brain Activity Analysis—0
Sinc-based convolutional neural networks for EEG-BCI-based motor imagery classification—0
HyperNTF: A Hypergraph Regularized Nonnegative Tensor Factorization for Dimensionality Reduction—0
Emotional EEG Classification using Connectivity Features and Convolutional Neural Networks—0
Motor-Imagery-Based Brain Computer Interface using Signal Derivation and Aggregation Functions—0
4D Attention-based Neural Network for EEG Emotion Recognition—0
Real or Virtual? Using Brain Activity Patterns to differentiate Attended Targets during Augmented Reality Scenarios—0
Deep Cellular Recurrent Network for Efficient Analysis of Time-Series Data with Spatial Information—0
MRNet: a Multi-scale Residual Network for EEG-based Sleep Staging—0
Assessment of Subjective Creativity Skill Using EEG Induced Capsule Network—0
Conex-Connect: Learning Patterns in Extremal Brain Connectivity From Multi-Channel EEG Data—0
Joint Learning of Full-structure Noise in Hierarchical Bayesian Regression ModelsCode0
Linking Attention-Based Multiscale CNN With Dynamical GCN for Driving Fatigue Detection—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