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

Recently AddedMost HypedMost ActiveNeeds VerificationMost Verified

Showing 1376–1400 of 1655 papers

TitleStatusHype
An automated approach for task evaluation using EEG signals—0
An EEG-based approach for Parkinson's disease diagnosis using Capsule network—0
An EEG-based Image Annotation System—0
An EEG-Based Multi-Modal Emotion Database with Both Posed and Authentic Facial Actions for Emotion Analysis—0
An EEG-based Stereoscopic Research to Reveal the Brain's Response to What Happens Before and After Watching 2D and 3D Movies—0
An EEG Channel Selection Framework for Driver Drowsiness Detection via Interpretability Guidance—0
An EEG study of creativity in expert classical musicians—0
An Effective Entropy-assisted Mind-wandering Detection System with EEG Signals based on MM-SART Database—0
An Efficient Epileptic Seizure Detection Technique using Discrete Wavelet Transform and Machine Learning Classifiers—0
An Efficient Intelligent System for the Classification of Electroencephalography (EEG) Brain Signals using Nuclear Features for Human Cognitive Tasks—0
An Electroencephalography connectome predictive model of major depressive disorder severity—0
An embedding for EEG signals learned using a triplet loss—0
An End-to-End Deep Learning Approach for Epileptic Seizure Prediction—0
An end-to-end (deep) neural network applied to raw EEG, fNIRs and body motion data for data fusion and BCI classification task without any pre-/post-processing—0
An Ensemble Learning Based Classification of Individual Finger Movement from EEG—0
A Neural-Inspired Architecture for EEG-Based Auditory Attention Detection—0
An Evaluation of the EEG alpha-to-theta and theta-to-alpha band Ratios as Indexes of Mental Workload—0
An Evoked Potential-Guided Deep Learning Brain Representation For Visual Classification—0
A New Method for Epileptic Seizure Classification in EEG Using Adapted Wavelet Packets—0
A new model for the implementation of positive and negative emotion recognition—0
A New Neuromorphic Computing Approach for Epileptic Seizure Prediction—0
A New Statistical Model of Electroencephalogram Noise Spectra for Real-time Brain-Computer Interfaces—0
An Explainable Model for EEG Seizure Detection based on Connectivity Features—0
An Improved EEG Acquisition Protocol Facilitates Localized Neural Activation—0
An intertwined neural network model for EEG classification in brain-computer interfaces—0
Show:102550
← PrevPage 56 of 67Next →
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