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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 176–200 of 252 papers

TitleStatusHype
MutualGraphNet: A novel model for motor imagery classification—0
A SPA-based Manifold Learning Framework for Motor Imagery EEG Data Classification—0
Classification of Upper Arm Movements from EEG signals using Machine Learning with ICA Analysis—0
Motor Imagery Classification based on CNN-GRU Network with Spatio-Temporal Feature Representation—0
Complex common spatial patterns on time-frequency decomposed EEG for brain-computer interfaceCode0
Towards Natural Brain-Machine Interaction using Endogenous Potentials based on Deep Neural Networks—0
Generating Ten BCI Commands Using Four Simple Motor Imageries—0
Classification of Motor Imagery EEG Signals by Using a Divergence Based Convolutional Neural NetworkCode0
A New Method for Features Normalization in Motor Imagery Few-Shot Learning using Resting-State—0
Model-Agnostic Meta-Learning for EEG Motor Imagery Decoding in Brain-Computer-Interfacing—0
Inter-subject Deep Transfer Learning for Motor Imagery EEG Decoding—0
Gaze-contingent decoding of human navigation intention on an autonomous wheelchair platform—0
Decoding and interpreting cortical signals with a compact convolutional neural network—0
Mixed-Precision Quantization and Parallel Implementation of Multispectral Riemannian Classification for Brain--Machine InterfacesCode0
On the use of generative deep neural networks to synthesize artificial multichannel EEG signals—0
End-to-end learnable EEG channel selection for deep neural networks with Gumbel-softmax—0
RIGOLETTO -- RIemannian GeOmetry LEarning: applicaTion To cOnnectivity. A contribution to the Clinical BCI Challenge -- WCCI2020Code0
Common Spatial Generative Adversarial Networks based EEG Data Augmentation for Cross-Subject Brain-Computer Interface—0
Probabilistic Learning Vector Quantization on Manifold of Symmetric Positive Definite Matrices—0
Sinc-based convolutional neural networks for EEG-BCI-based motor imagery classification—0
Motor-Imagery-Based Brain Computer Interface using Signal Derivation and Aggregation Functions—0
A Ternary Bi-Directional LSTM Classification for Brain Activation Pattern Recognition Using fNIRS—0
A Deep Learning Based Ternary Task Classification System Using Gramian Angular Summation Field in fNIRS Neuroimaging Data—0
Towards Real-World BCI: CCSPNet, A Compact Subject-Independent Motor Imagery FrameworkCode0
Comparison of Classification Algorithms Towards Subject-Specific and Subject-Independent BCICode0
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