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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 101–125 of 252 papers

TitleStatusHype
Transfer Learning between Motor Imagery Datasets using Deep Learning -- Validation of Framework and Comparison of DatasetsCode0
A Human-Machine Joint Learning Framework to Boost Endogenous BCI Training—0
Pseudo-online framework for BCI evaluation: A MOABB perspective—0
Aggregating Intrinsic Information to Enhance BCI Performance through Federated LearningCode0
Deep Learning Architecture for Motor Imaged Words—0
Feature Reweighting for EEG-based Motor Imagery Classification—0
End-to-End Deep Transfer Learning for Calibration-free Motor Imagery Brain Computer Interfaces—0
EEG Decoding for Datasets with Heterogenous Electrode Configurations using Transfer Learning Graph Neural Networks—0
Decoding Brain Motor Imagery with various Machine Learning techniques—0
A Convolutional Spiking Network for Gesture Recognition in Brain-Computer Interfaces—0
Time-space-frequency feature Fusion for 3-channel motor imagery classificationCode1
LMDA-Net:A lightweight multi-dimensional attention network for general EEG-based brain-computer interface paradigms and interpretabilityCode1
Scatter-based common spatial patterns -- a unified spatial filtering framework—0
Score-Based Data Generation for EEG Spatial Covariance Matrices: Towards Boosting BCI PerformanceCode1
Deep comparisons of Neural Networks from the EEGNet familyCode1
Classification of BCI-EEG based on augmented covariance matrixCode0
CropCat: Data Augmentation for Smoothing the Feature Distribution of EEG Signals—0
A Hybrid Brain-Computer Interface Using Motor Imagery and SSVEP Based on Convolutional Neural Network—0
Enhancing Low-Density EEG-Based Brain-Computer Interfaces with Similarity-Keeping Knowledge DistillationCode1
Motor Imagery Decoding Using Ensemble Curriculum Learning and Collaborative TrainingCode1
Adversarial Stimuli: Attacking Brain-Computer Interfaces via Perturbed Sensory Events—0
Motor imagery classification using EEG spectrograms—0
Spatial Graph Signal Interpolation with an Application for Merging BCI Datasets with Various Dimensionalities—0
Graph Neural Networks on SPD Manifolds for Motor Imagery Classification: A Perspective from the Time-Frequency AnalysisCode1
The evolution of AI approaches for motor imagery EEG-based BCIs—0
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