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 1051–1100 of 1655 papers

TitleStatusHype
The Little Prince in 26 Languages: Towards a Multilingual Neuro-Cognitive Corpus—0
Towards Best Practices for Leveraging Human Language Processing Signals for Natural Language Processing—0
Wireless User-Generic Ear EEG—0
Augmenting interictal mapping with neurovascular coupling biomarkers by structured factorization of epileptic EEG and fMRI dataCode1
Automatic Identification of Epileptic Seizures from EEG Signals using Sparse Representation-based Classification—0
Federated Transfer Learning for EEG Signal ClassificationCode1
Brain-based control of car infotainment—0
Q-EEGNet: an Energy-Efficient 8-bit Quantized Parallel EEGNet Implementation for Edge Motor-Imagery Brain--Machine InterfacesCode0
Postural control adaptation and habituation during vibratory proprioceptive stimulation: an HD-EEG investigation of cortical recruitment and kinematics—0
Multi-level Binarized LSTM in EEG Classification for Wearable Devices—0
MuBiNN: Multi-Level Binarized Recurrent Neural Network for EEG signal Classification—0
Detecting Driver's Distraction using Long-term Recurrent Convolutional Network—0
Transfer Learning for EEG-Based Brain-Computer Interfaces: A Review of Progress Made Since 2016—0
Local Model Feature Transformations—0
Deep transfer learning for improving single-EEG arousal detection—0
Object classification from randomized EEG trials—0
Advancing Speech Synthesis using EEG—0
Investigating EEG-Based Functional Connectivity Patterns for Multimodal Emotion Recognition—0
Binary and Multiclass Classifiers based on Multitaper Spectral Features for Epilepsy Detection—0
TSception: A Deep Learning Framework for Emotion Detection Using EEGCode1
Improving auditory attention decoding performance of linear and non-linear methods using state-space model—0
Stationarity of Time-Series on Graph via Bivariate Translation Invariance—0
An Accurate EEGNet-based Motor-Imagery Brain-Computer Interface for Low-Power Edge Computing—0
EEG Signal Classification using Variational Mode Decomposition—0
A Novel Deep Learning Architecture for Decoding Imagined Speech from EEG—0
Decoding Imagined Speech using Wavelet Features and Deep Neural Networks—0
Mindfulness Improves Brain Computer Interface Performance by Increasing Control over Neural Activity in the Alpha Band—0
An Improved EEG Acquisition Protocol Facilitates Localized Neural Activation—0
Ultra Efficient Transfer Learning with Meta Update for Cross Subject EEG ClassificationCode1
FuDGE: A Method to Estimate a Functional Differential Graph in a High-Dimensional Setting—0
Implementation of Deep Neural Networks to Classify EEG Signals using Gramian Angular Summation Field for Epilepsy Diagnosis—0
Speaker Identification using EEG—0
Few-Shot Relation Learning with Attention for EEG-based Motor Imagery Classification—0
Multi-Scale Neural network for EEG Representation Learning in BCI—0
Analysis of Gait-Event-related Brain Potentials During Instructed And Spontaneous Treadmill Walking -- Technical Affordances and used Methods—0
Generating EEG features from Acoustic features—0
Depression Detection using Resting State Three-channel EEG Signal—0
CLARA: Clinical Report Auto-completion—0
A study of resting-state EEG biomarkers for depression recognition—0
Speech Synthesis using EEG—0
Multimodal pathophysiological dataset of gradual cerebral ischemia in a cohort of juvenile pigs—0
MODMA dataset: a Multi-modal Open Dataset for Mental-disorder Analysis—0
Deep Learning of Movement Intent and Reaction Time for EEG-informed Adaptation of Rehabilitation Robots—0
Machine Learning for Motor Learning: EEG-based Continuous Assessment of Cognitive Engagement for Adaptive Rehabilitation Robots—0
Effective Correlates of Motor Imagery Performance based on Default Mode Network in Resting-State—0
Machine-Learning-Based Diagnostics of EEG PathologyCode1
Design and Implementation of Butterworth, Chebyshev-I and Elliptic Filter for Speech Signal Analysis—0
Continuous Silent Speech Recognition using EEG—0
DeepBrain: Towards Personalized EEG Interaction through Attentional and Embedded LSTM Learning—0
Machine Learning for Predicting Epileptic Seizures Using EEG Signals: A Review—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