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 551–600 of 1655 papers

TitleStatusHype
Boosted Convolutional Neural Networks for Motor Imagery EEG Decoding with Multiwavelet-based Time-Frequency Conditional Granger Causality Analysis—0
A highly scalable repository of waveform and vital signs data from bedside monitoring devices—0
Adaptive neural network classifier for decoding MEG signals—0
Blink Rate Variability during resting and reading sessions—0
A New Neuromorphic Computing Approach for Epileptic Seizure Prediction—0
A Hierarchical Graph Signal Processing Approach to Inference from Spatiotemporal Signals—0
Biophysical aspects of neurocognitive modeling with long-term sustained temperature variations—0
Disruption of the prefrontal cortex improves implicit contextual memory-guided attention: combined behavioural and electrophysiological evidence—0
Biomagnetic signals recorded during transcranial magnetic stimulation (TMS)-evoked peripheral muscular activity—0
A new model for the implementation of positive and negative emotion recognition—0
Bioelectrical brain activity can predict prosocial behavior—0
Binary Single-dimensional Convolutional Neural Network for Seizure Prediction—0
A New Method for Epileptic Seizure Classification in EEG Using Adapted Wavelet Packets—0
Binary and Multiclass Classifiers based on Multitaper Spectral Features for Epilepsy Detection—0
Differentially Private Multimodal Laplacian Dropout (DP-MLD) for EEG Representative Learning—0
An Evoked Potential-Guided Deep Learning Brain Representation For Visual Classification—0
A Hierarchical Fuzzy System for an Advanced Driving Assistance System—0
EEG2Vec: Learning Affective EEG Representations via Variational Autoencoders—0
EEG and EMG dataset for the detection of errors introduced by an active orthosis device—0
EEG-assisted Modulation of Sound Sources in the Auditory Scene—0
Differential EEG Characteristics during Working Memory Encoding and Re-encoding—0
Differences in MEG and EEG power-law scaling explained by a coupling between spatial coherence and frequency: a simulation study—0
Bidirectional Inference Networks: A Class of Deep Bayesian Networks for Health Profiling—0
DGAFF: Deep Genetic Algorithm Fitness Formation for EEG Bio-Signal Channel Selection—0
DF-SSmVEP: Dual Frequency Aggregated Steady-State Motion Visual Evoked Potential Design with Bifold Canonical Correlation Analysis—0
Difficulties applying recent blind source separation techniques to EEG and MEG—0
Dimensionality reduction for time series data—0
Binary classification of multi-channel EEG records based on the ε-complexity of continuous vector functions—0
Directional and Causal Information Flow in EEG for Assessing Perceived Audio Quality—0
Discriminative Sleep Patterns of Alzheimer's Disease via Tensor Factorization—0
Disentangled and Side-aware Unsupervised Domain Adaptation for Cross-dataset Subjective Tinnitus Diagnosis—0
BiCurNet: Pre-Movement EEG based Neural Decoder for Biceps Curl Trajectory Estimation—0
An Evaluation of the EEG alpha-to-theta and theta-to-alpha band Ratios as Indexes of Mental Workload—0
Distilling EEG Representations via Capsules for Affective Computing—0
DM algorithms in healthindustry—0
Development of Sleep State Trend (SST), a bedside measure of neonatal sleep state fluctuations based on single EEG channels—0
Bispectrum-based Cross-frequency Functional Connectivity: Classification of Alzheimer's disease—0
Downsampling and geometric feature methods for EEG classification tasks with CNNs—0
Beware of Overestimated Decoding Performance Arising from Temporal Autocorrelations in Electroencephalogram Signals—0
Detection of Sleep Oxygen Desaturations from Electroencephalogram Signals—0
Benefit-aware Early Prediction of Health Outcomes on Multivariate EEG Time Series—0
Driver Drowsiness Estimation from EEG Signals Using Online Weighted Adaptation Regularization for Regression (OwARR)—0
Dropping Activation Outputs with Localized First-layer Deep Network for Enhancing User Privacy and Data Security—0
A Neural-Inspired Architecture for EEG-Based Auditory Attention Detection—0
Dyadic aggregated autoregressive (DASAR) model for time-frequency representation of biomedical signals—0
Dynamical Component Analysis (DyCA): Dimensionality Reduction For High-Dimensional Deterministic Time-Series—0
Dynamical Component Analysis (DyCA) and its application on epileptic EEG—0
BRAIN2DEPTH: Lightweight CNN Model for Classification of Cognitive States from EEG Recordings—0
Dynamic Graph Modeling of Simultaneous EEG and Eye-tracking Data for Reading Task Identification—0
A Generative Model to Synthesize EEG Data for Epileptic Seizure Prediction—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