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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
Improved Motor Imagery Classification Using Adaptive Spatial Filters Based on Particle Swarm Optimization Algorithm—0
Enhancing Motor Imagery Decoding in Brain Computer Interfaces using Riemann Tangent Space Mapping and Cross Frequency Coupling—0
LGL-BCI: A Lightweight Geometric Learning Framework for Motor Imagery-Based Brain-Computer Interfaces—0
Graph Neural Network-based EEG Classification: A Survey—0
Intentional binding enhances hybrid BCI control—0
Phase Synchrony Component Self-Organization in Brain Computer Interface—0
A Dynamic Domain Adaptation Deep Learning Network for EEG-based Motor Imagery Classification—0
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
Scatter-based common spatial patterns -- a unified spatial filtering framework—0
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
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
The evolution of AI approaches for motor imagery EEG-based BCIs—0
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