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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 201–250 of 252 papers

TitleStatusHype
Brain-Computer Interface with Corrupted EEG Data: A Tensor Completion Approach—0
Can EEG resting state data benefit data-driven approaches for motor-imagery decoding?—0
CATVis: Context-Aware Thought Visualization—0
Channel Reflection: Knowledge-Driven Data Augmentation for EEG-Based Brain-Computer Interfaces—0
Classification of EEG Motor Imagery Using Deep Learning for Brain-Computer Interface Systems—0
Classification of eye-state using EEG recordings: speed-up gains using signal epochs and mutual information measure—0
Classification of Upper Arm Movements from EEG signals using Machine Learning with ICA Analysis—0
Classifying Single-Trial EEG during Motor Imagery with a Small Training Set—0
CLEAN-MI: A Scalable and Efficient Pipeline for Constructing High-Quality Neurodata in Motor Imagery Paradigm—0
Common Spatial Generative Adversarial Networks based EEG Data Augmentation for Cross-Subject Brain-Computer Interface—0
Community Detection from Multiple Observations: from Product Graph Model to Brain Applications—0
Covariate Shift Estimation based Adaptive Ensemble Learning for Handling Non-Stationarity in Motor Imagery related EEG-based Brain-Computer Interface—0
CropCat: Data Augmentation for Smoothing the Feature Distribution of EEG Signals—0
Cross-Correlation Based Discriminant Criterion for Channel Selection in Motor Imagery BCI Systems—0
Dataset Refinement for Improving the Generalization Ability of the EEG Decoding Model—0
Decoding and interpreting cortical signals with a compact convolutional neural network—0
Decoding Brain Motor Imagery with various Machine Learning techniques—0
Decoding Imagined Movement in People with Multiple Sclerosis for Brain-Computer Interface Translation—0
Deep convolutional recurrent neural network for short-interval EEG motor imagery classification—0
Deep Feature Mining via Attention-based BiLSTM-GCN for Human Motor Imagery Recognition—0
Deep Learning Architecture for Motor Imaged Words—0
Deep learning for ECoG brain-computer interface: end-to-end vs. hand-crafted features—0
DGAFF: Deep Genetic Algorithm Fitness Formation for EEG Bio-Signal Channel Selection—0
Different factors determining Motor Execution and Motor Imagery performance in a serial reaction time task with intrinsic variability—0
EEG2TEXT: Open Vocabulary EEG-to-Text Decoding with EEG Pre-Training and Multi-View Transformer—0
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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