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 151–200 of 1655 papers

TitleStatusHype
Cross-Subject Data Splitting for Brain-to-Text Decoding—0
Study of cognitive component of auditory attention to natural speech events—0
Brain-scale Theta Band Functional Connectivity As A Signature of Slow Breathing and Breath-hold Phases—0
Decoding Envelope and Frequency-Following EEG Responses to Continuous Speech Using Deep Neural NetworksCode0
NiSNN-A: Non-iterative Spiking Neural Networks with Attention with Application to Motor Imagery EEG Classification—0
ProtoEEGNet: An Interpretable Approach for Detecting Interictal Epileptiform Discharges—0
EEG-Based Reaction Time Prediction with Fuzzy Common Spatial Patterns and Phase Cohesion using Deep Autoencoder Based Data Fusion—0
InfoFlowNet: A Multi-head Attention-based Self-supervised Learning Model with Surrogate Approach for Uncovering Brain Effective Connectivity—0
DTP-Net: Learning to Reconstruct EEG signals in Time-Frequency Domain by Multi-scale Feature ReuseCode1
Human-Machine Cooperative Multimodal Learning Method for Cross-subject Olfactory Preference Recognition—0
HypUC: Hyperfine Uncertainty Calibration with Gradient-boosted Corrections for Reliable Regression on Imbalanced Electrocardiograms—0
Sparsity-Driven EEG Channel Selection for Brain-Assisted Speech Enhancement—0
Neurophysiological Response Based on Auditory Sense for Brain Modulation Using Monaural Beat—0
Relationship Between Mood, Sleepiness, and EEG Functional Connectivity by 40 Hz Monaural Beats—0
Sample Dominance Aware Framework via Non-Parametric Estimation for Spontaneous Brain-Computer Interface—0
New Approach for an Affective Computing-Driven Quality of Experience (QoE) Prediction—0
Enhancing Motor Imagery Decoding in Brain Computer Interfaces using Riemann Tangent Space Mapping and Cross Frequency Coupling—0
Improved Motor Imagery Classification Using Adaptive Spatial Filters Based on Particle Swarm Optimization Algorithm—0
Reputation-Based Federated Learning Defense to Mitigate Threats in EEG Signal Classification—0
Stabilizing Subject Transfer in EEG Classification with Divergence Estimation—0
LGL-BCI: A Lightweight Geometric Learning Framework for Motor Imagery-Based Brain-Computer Interfaces—0
Hypercomplex Multimodal Emotion Recognition from EEG and Peripheral Physiological SignalsCode1
Multimodal Identification of Alzheimer's Disease: A Review—0
Artificial Intelligence for EEG Prediction: Applied Chaos TheoryCode1
Neuroadaptation in Physical Human-Robot Collaboration—0
A Multi-channel EEG Data Analysis for Poor Neuro-prognostication in Comatose Patients with Self and Cross-channel Attention Mechanism—0
A Knowledge-Driven Cross-view Contrastive Learning for EEG Representation—0
SCVCNet: Sliding cross-vector convolution network for cross-task and inter-individual-set EEG-based cognitive workload recognitionCode0
A Dynamic Domain Adaptation Deep Learning Network for EEG-based Motor Imagery Classification—0
A Multi Constrained Transformer-BiLSTM Guided Network for Automated Sleep Stage Classification from Single-Channel EEG—0
Electroencephalogram Sensor Data Compression Using An Asymmetrical Sparse Autoencoder With A Discrete Cosine Transform Layer—0
mEBAL2 Database and Benchmark: Image-based Multispectral Eyeblink DetectionCode0
Sleep Stage Classification Using a Pre-trained Deep Learning Model—0
Early warning indicators via latent stochastic dynamical systems—0
Real-Time Non-Invasive Imaging and Detection of Spreading Depolarizations through EEG: An Ultra-Light Explainable Deep Learning Approach—0
RoBoSS: A Robust, Bounded, Sparse, and Smooth Loss Function for Supervised LearningCode0
MASA-TCN: Multi-anchor Space-aware Temporal Convolutional Neural Networks for Continuous and Discrete EEG Emotion RecognitionCode1
A Human-Machine Joint Learning Framework to Boost Endogenous BCI Training—0
EOG Artifact Removal from Single and Multi-channel EEG Recordings through the combination of Long Short-Term Memory Networks and Independent Component Analysis—0
Decoding Natural Images from EEG for Object RecognitionCode1
State-transition dynamics of resting-state functional magnetic resonance imaging data: Model comparison and test-to-retest analysisCode0
Functional Graph Contrastive Learning of Hyperscanning EEG Reveals Emotional Contagion Evoked by Stereotype-Based Stressors—0
Large Transformers are Better EEG LearnersCode0
A Hybrid Deep Spatio-Temporal Attention-Based Model for Parkinson's Disease Diagnosis Using Resting State EEG Signals—0
Comparative Analysis of Epileptic Seizure Prediction: Exploring Diverse Pre-Processing Techniques and Machine Learning Models—0
EEG-based Cognitive Load Classification using Feature Masked Autoencoding and Emotion Transfer Learning—0
ViT2EEG: Leveraging Hybrid Pretrained Vision Transformers for EEG DataCode1
Concept-based explainability for an EEG transformer modelCode0
Mental Workload Estimation with Electroencephalogram Signals by Combining Multi-Space Deep Models—0
Perturbing a Neural Network to Infer Effective Connectivity: Evidence from Synthetic EEG Data—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