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Motor Imagery

Classification of examples recorded under the Motor Imagery paradigm, as part of Brain-Computer Interfaces (BCI).

A number of motor imagery datasets can be downloaded using the MOABB library: motor imagery datasets list

Papers

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Showing 126–150 of 252 papers

TitleStatusHype
Deep learning for ECoG brain-computer interface: end-to-end vs. hand-crafted features—0
Cross Task Neural Architecture Search for EEG Signal ClassificationsCode1
Impact of dataset size and long-term ECoG-based BCI usage on deep learning decoders performance—0
Classification of eye-state using EEG recordings: speed-up gains using signal epochs and mutual information measure—0
Partial Least Square Regression via Three-factor SVD-type Manifold Optimization for EEG Decoding—0
An intertwined neural network model for EEG classification in brain-computer interfaces—0
Physics-inform attention temporal convolutional network for EEG-based motor imagery classificationCode2
Improving Motor Imagery EEG Classification Based on Channel Selection Using a Deep Learning ArchitectureCode0
Data augmentation for learning predictive models on EEG: a systematic comparisonCode1
Factorization Approach for Sparse Spatio-Temporal Brain-Computer Interface—0
Classification of EEG Motor Imagery Using Deep Learning for Brain-Computer Interface Systems—0
Unsupervised Motor Imagery Saliency Detection Based on Self-Attention Mechanism—0
A Subject-Independent Brain-Computer Interface Framework Based on Supervised Autoencoder—0
EEG-ITNet: An Explainable Inception Temporal Convolutional Network for Motor Imagery ClassificationCode1
A self-paced BCI system with low latency for motor imagery onset detection based on time series prediction paradigm—0
MI-BMInet: An Efficient Convolutional Neural Network for Motor Imagery Brain--Machine Interfaces with EEG Channel Selection—0
Towards physiology-informed data augmentation for EEG-based BCIs—0
DGAFF: Deep Genetic Algorithm Fitness Formation for EEG Bio-Signal Channel Selection—0
Priming Cross-Session Motor Imagery Classification with A Universal Deep Domain Adaptation FrameworkCode1
2021 BEETL Competition: Advancing Transfer Learning for Subject Independence & Heterogenous EEG Data SetsCode1
Spectrally Adaptive Common Spatial Patterns—0
Tensor-CSPNet: A Novel Geometric Deep Learning Framework for Motor Imagery ClassificationCode1
Team Cogitat at NeurIPS 2021: Benchmarks for EEG Transfer Learning Competition—0
Enhanced motor imagery-based EEG classification using a discriminative graph Fourier subspace—0
ExBrainable: An Open-Source GUI for CNN-based EEG Decoding and Model InterpretationCode1
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