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 1176–1200 of 1655 papers

TitleStatusHype
Mutual Information-driven Subject-invariant and Class-relevant Deep Representation Learning in BCICode0
Ballistocardiogram artifact reduction in simultaneous EEG-fMRI using deep learning—0
Manifold Embedded Knowledge Transfer for Brain-Computer InterfacesCode0
Decoding Working Memory Load from EEG with LSTM Networks—0
Neural Memory Plasticity for Anomaly Detection—0
Increasing the Detectability of Phase-Amplitude Coupling—0
On the Effects of Pseudo and Quantum Random Number Generators in Soft Computing—0
Using Deep Learning and Machine Learning to Detect Epileptic Seizure with Electroencephalography (EEG) Data—0
MUTLA: A Large-Scale Dataset for Multimodal Teaching and Learning Analytics—0
Multi-subject MEG/EEG source imaging with sparse multi-task regression—0
Mental Task Classification Using Electroencephalogram SignalCode0
A Deep Cybersickness Predictor Based on Brain Signal Analysis for Virtual Reality Contents—0
Biomagnetic signals recorded during transcranial magnetic stimulation (TMS)-evoked peripheral muscular activity—0
EEG-Based Driver Drowsiness Estimation Using Feature Weighted Episodic Training—0
Manifold Oblique Random Forests: Towards Closing the Gap on Convolutional Deep NetworksCode0
Sleep Stage Classification Using Bidirectional LSTM in Wearable Multi-sensor Systems—0
CogniVal: A Framework for Cognitive Word Embedding EvaluationCode0
Adversarial Representation Learning for Robust Patient-Independent Epileptic Seizure DetectionCode0
Improved robust weighted averaging for event-related potentials in EEGCode0
Carbogen inhalation during Non-Convulsive Status Epilepticus: A quantitative analysis of EEG recordings—0
Spoken Speech Enhancement using EEG—0
HHHFL: Hierarchical Heterogeneous Horizontal Federated Learning for ElectroencephalographyCode0
EEG based Emotion Recognition of Image Stimuli—0
Unravelling the neural signatures of dream recall in EEG: a deep learning approach—0
Tracking momentary attention fluctuations with an EEG-based cognitive brain-machine interface—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