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 1601–1650 of 1655 papers

TitleStatusHype
Spatiotemporal Emotion Recognition using Deep CNN Based on EEG during Music ListeningCode0
CogAlign: Learning to Align Textual Neural Representations to Cognitive Language Processing SignalsCode0
Synthetic Epileptic Brain Activities Using Generative Adversarial NetworksCode0
Deep Convolutional Neural Network Applied to Electroencephalography: Raw Data vs Spectral FeaturesCode0
EnK: Encoding time-information in convolutionCode0
Applying advanced machine learning models to classify electro-physiological activity of human brain for use in biometric identificationCode0
Large Transformers are Better EEG LearnersCode0
Neuroadaptive electroencephalography: a proof-of-principle study in infantsCode0
Enhancing Affective Representations of Music-Induced EEG through Multimodal Supervision and latent Domain AdaptationCode0
Decoding P300 Variability using Convolutional Neural NetworksCode0
ToFFi -- Toolbox for Frequency-based Fingerprinting of Brain SignalsCode0
RIGOLETTO -- RIemannian GeOmetry LEarning: applicaTion To cOnnectivity. A contribution to the Clinical BCI Challenge -- WCCI2020Code0
Learning from imperfect training data using a robust loss function: application to brain image segmentationCode0
Refining ADHD diagnosis with EEG: The impact of preprocessing and temporal segmentation on classification accuracyCode0
CARE-rCortex: a Matlab toolbox for the analysis of CArdio-REspiratory-related activity in the CortexCode0
Learning Representations from EEG with Deep Recurrent-Convolutional Neural NetworksCode0
Learning Robust Features using Deep Learning for Automatic Seizure DetectionCode0
Decoding kinetic features of hand motor preparation from single‐trial EEG using convolutional neural networksCode0
Q-EEGNet: an Energy-Efficient 8-bit Quantized Parallel EEGNet Implementation for Edge Motor-Imagery Brain--Machine InterfacesCode0
SeizureNet: Multi-Spectral Deep Feature Learning for Seizure Type ClassificationCode0
Decoding Envelope and Frequency-Following EEG Responses to Continuous Speech Using Deep Neural NetworksCode0
Semi-Supervised Learning for Sparsely-Labeled Sequential Data: Application to Healthcare Video ProcessingCode0
Enhanced Cross-Dataset Electroencephalogram-based Emotion Recognition using Unsupervised Domain AdaptationCode0
End-to-end Sleep Staging with Raw Single Channel EEG using Deep Residual ConvNetsCode0
A Statistical Approach for Synthetic EEG Data GenerationCode0
Towards a Better Understanding Human Reading Comprehension with Brain SignalsCode0
Too Fine or Too Coarse? The Goldilocks Composition of Data Complexity for Robust Left-Right Eye-Tracking ClassifiersCode0
Random Convolution Kernels with Multi-Scale Decomposition for Preterm EEG Inter-burst DetectionCode0
Node-wise Domain Adaptation Based on Transferable Attention for Recognizing Road Rage via EEGCode0
Localization of Brain Activity from EEG/MEG Using MV-PURE FrameworkCode0
Noise-based cyberattacks generating fake P300 waves in brain–computer interfacesCode0
Self-Organization Towards 1/f Noise in Deep Neural NetworksCode0
Converting Your Thoughts to Texts: Enabling Brain Typing via Deep Feature Learning of EEG SignalsCode0
Classification of multivariate weakly-labelled time-series with attentionCode0
EMMT: A simultaneous eye-tracking, 4-electrode EEG and audio corpus for multi-modal reading and translation scenariosCode0
Reading Task Classification Using EEG and Eye-Tracking DataCode0
Embedding neurophysiological signalsCode0
Classification of Motor Imagery EEG Signals by Using a Divergence Based Convolutional Neural NetworkCode0
Real-time EEG-based Emotion Recognition Model using Principal Component Analysis and Tree-based Models for NeurohumanitiesCode0
Nonparametric Modeling of Dynamic Functional Connectivity in fMRI DataCode0
Classification of High-Dimensional Motor Imagery Tasks based on An End-to-end role assigned convolutional neural networkCode0
Mutual Information-driven Subject-invariant and Class-relevant Deep Representation Learning in BCICode0
Efficient Hierarchical Bayesian Inference for Spatio-temporal Regression Models in NeuroimagingCode0
Context tree selection for functional dataCode0
Classification of epileptic seizures in EEG data based on iterative gated graph convolution networkCode0
Using Explainable AI for EEG-based Reduced Montage Neonatal Seizure DetectionCode0
Classification of BCI-EEG based on augmented covariance matrixCode0
Conditional canonical correlation estimation based on covariates with random forestsCode0
Real-Time Sleep Staging using Deep Learning on a Smartphone for a Wearable EEGCode0
Seizure Type Classification using EEG signals and Machine Learning: Setting a benchmarkCode0
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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