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 501–525 of 1655 papers

TitleStatusHype
A statistical method for analyzing and comparing spatiotemporal cortical activation patterns—0
Deep Classification of Epileptic Signals—0
Contextual Minimum-Norm Estimates (CMNE): A Deep Learning Method for Source Estimation in Neuronal Networks—0
Constrained Variational Autoencoder for improving EEG based Speech Recognition Systems—0
Deep Convolutional Neural Network for Automated Detection of Mind Wandering using EEG Signals—0
Deep Convolutional Neural Networks for Interpretable Analysis of EEG Sleep Stage Scoring—0
Deep convolutional recurrent neural network for short-interval EEG motor imagery classification—0
Deep Correlation Analysis for Audio-EEG Decoding—0
Confidence-Aware Subject-to-Subject Transfer Learning for Brain-Computer Interface—0
Deep Feature Mining via Attention-based BiLSTM-GCN for Human Motor Imagery Recognition—0
A state-space model of cross-region dynamic connectivity in MEG/EEG—0
A Multi-objective Evolutionary Algorithm for EEG Inverse Problem—0
Advancing Speech Recognition With No Speech Or With Noisy Speech—0
Conex-Connect: Learning Patterns in Extremal Brain Connectivity From Multi-Channel EEG Data—0
Computing extracellular electric potentials from neuronal simulations—0
Assessment of Unconsciousness for Memory Consolidation Using EEG Signals—0
A Multimodal Perceived Stress Classification Framework using Wearable Physiological Sensors—0
Accurate and efficient Simulation of very high-dimensional Neural Mass Models with distributed-delay Connectome Tensors—0
Compressed Sensing of Multi-Channel EEG Signals: The Simultaneous Cosparsity and Low Rank Optimization—0
Compressed Sensing of EEG for Wireless Telemonitoring with Low Energy Consumption and Inexpensive Hardware—0
Compressed Sensing for Energy-Efficient Wireless Telemonitoring: Challenges and Opportunities—0
Assessment of Subjective Creativity Skill Using EEG Induced Capsule Network—0
A Multi-Modal Non-Invasive Deep Learning Framework for Progressive Prediction of Seizures—0
A computational investigation of the relationships between single-neuron and network dynamics in the cerebral cortex—0
Accelerating Reinforcement Learning Agent with EEG-based Implicit Human Feedback—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