SOTAVerified

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 226–250 of 252 papers

TitleStatusHype
EEG-Based Mental Imagery Task Adaptation via Ensemble of Weight-Decomposed Low-Rank Adapters—0
EEG Decoding for Datasets with Heterogenous Electrode Configurations using Transfer Learning Graph Neural Networks—0
EEGEncoder: Advancing BCI with Transformer-Based Motor Imagery Classification—0
EEG Foundation Models for BCI Learn Diverse Features of Electrophysiology—0
EEG_GLT-Net: Optimising EEG Graphs for Real-time Motor Imagery Signals Classification—0
EEGMamba: Bidirectional State Space Model with Mixture of Experts for EEG Multi-task Classification—0
EEG_RL-Net: Enhancing EEG MI Classification through Reinforcement Learning-Optimised Graph Neural Networks—0
Effective Correlates of Motor Imagery Performance based on Default Mode Network in Resting-State—0
Effect of Simulated Space Conditions on functional Connectivity—0
Electrocorticographic Dynamics Predict Visually Guided Motor Imagery of Grasp Shaping—0
Emotion-robust EEG Classification for Motor Imagery—0
End-to-End Deep Transfer Learning for Calibration-free Motor Imagery Brain Computer Interfaces—0
End-to-end learnable EEG channel selection for deep neural networks with Gumbel-softmax—0
Enhanced motor imagery-based EEG classification using a discriminative graph Fourier subspace—0
Enhancing Computational Efficiency of Motor Imagery BCI Classification with Block-Toeplitz Augmented Covariance Matrices and Siegel Metric—0
Enhancing Motor Imagery Decoding in Brain Computer Interfaces using Riemann Tangent Space Mapping and Cross Frequency Coupling—0
Error-related Potential driven Reinforcement Learning for adaptive Brain-Computer Interfaces—0
Evaluating a Semi-Autonomous Brain-Computer Interface Based on Conformal Geometric Algebra and Artificial Vision—0
Factorization Approach for Sparse Spatio-Temporal Brain-Computer Interface—0
Feature Learning from Incomplete EEG with Denoising Autoencoder—0
Feature Reweighting for EEG-based Motor Imagery Classification—0
Feature Selection via Dynamic Graph-based Attention Block in MI-based EEG Signals—0
Few-Shot Relation Learning with Attention for EEG-based Motor Imagery Classification—0
FingerNet: EEG Decoding of A Fine Motor Imagery with Finger-tapping Task Based on A Deep Neural Network—0
From Electrode to Global Brain: Integrating Multi- and Cross-Scale Brain Connections and Interactions Under Cross-Subject and Within-Subject Scenarios—0
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