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 1226–1250 of 1655 papers

TitleStatusHype
The Dreem Headband as an Alternative to Polysomnography for EEG Signal Acquisition and Sleep Staging—0
Automated Classification of Seizures against Nonseizures: A Deep Learning Approach—0
Brain-Network Clustering via Kernel-ARMA Modeling and the Grassmannian—0
On the use of Pairwise Distance Learning for Brain Signal Classification with Limited ObservationsCode0
Probabilistic Structure Learning for EEG/MEG Source Imaging with Hierarchical Graph Prior—0
Amplifying the Neural Power Spectrum—0
Manifold-regression to predict from MEG/EEG brain signals without source modelingCode0
Simultaneous induction of SSMVEP and SMR Using a Gaiting video stimulus: a novel hybrid brain-computer interface—0
EEG-based Emotional Video Classification via Learning Connectivity StructureCode1
Adaptive Subspace Sampling for Class Imbalance Processing-Some clarifications, algorithm, and further investigation including applications to Brain Computer Interface—0
EEG Classification by factoring in Sensor Configuration—0
Utilizing Deep Learning Towards Multi-modal Bio-sensing and Vision-based Affective Computing—0
Discriminative Sleep Patterns of Alzheimer's Disease via Tensor Factorization—0
Emotion Classification in Response to Tactile Enhanced Multimedia using Frequency Domain Features of Brain Signals—0
Classification of Perceived Human Stress using Physiological Signals—0
Explore intrinsic geometry of sleep dynamics and predict sleep stage by unsupervised learning techniques—0
A Novel Bi-hemispheric Discrepancy Model for EEG Emotion Recognition—0
A new model for the implementation of positive and negative emotion recognition—0
Mental Fatigue Monitoring using Brain Dynamics Preferences—0
Neural Causal Discovery with Learnable Input Noise—0
A Review on understanding Brain, and Memory Retention and Recall Processes using EEG and fMRI techniques—0
Universal Joint Feature Extraction for P300 EEG Classification using Multi-task Autoencoder—0
An Efficient Intelligent System for the Classification of Electroencephalography (EEG) Brain Signals using Nuclear Features for Human Cognitive Tasks—0
Automatic Emotion Recognition (AER) System based on Two-Level Ensemble of Lightweight Deep CNN Models—0
Towards a Passive BCI to Induce Lucid Dream—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