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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
Enhancing Computational Efficiency of Motor Imagery BCI Classification with Block-Toeplitz Augmented Covariance Matrices and Siegel Metric—0
Motor Imagery Task Alters Dynamics of Human Body Posture—0
Pseudo Channel: Time Embedding for Motor Imagery Decoding—0
NeuroAssist: Enhancing Cognitive-Computer Synergy with Adaptive AI and Advanced Neural Decoding for Efficient EEG Signal Classification—0
EEG2TEXT: Open Vocabulary EEG-to-Text Decoding with EEG Pre-Training and Multi-View Transformer—0
Quantifying Spatial Domain Explanations in BCI using Earth Mover's DistanceCode0
EEG_RL-Net: Enhancing EEG MI Classification through Reinforcement Learning-Optimised Graph Neural Networks—0
EEGEncoder: Advancing BCI with Transformer-Based Motor Imagery Classification—0
EEG_GLT-Net: Optimising EEG Graphs for Real-time Motor Imagery Signals Classification—0
BDAN: Mitigating Temporal Difference Across Electrodes in Cross-Subject Motor Imagery Classification via Generative Bridging Domain—0
The Sandwich meta-framework for architecture agnostic deep privacy-preserving transfer learning for non-invasive brainwave decoding—0
Unsupervised Adaptive Deep Learning Method For BCI Motor Imagery Decoding—0
Uncertainty Quantification for cross-subject Motor Imagery classificationCode0
Transferring BCI models from calibration to control: Observing shifts in EEG features—0
Spatiotemporal Pooling on Appropriate Topological Maps Represented as Two-Dimensional Images for EEG Classification—0
FingerNet: EEG Decoding of A Fine Motor Imagery with Finger-tapping Task Based on A Deep Neural Network—0
Multiview Contrastive Learning for Unsupervised Domain Adaptation in Brain–Computer Interfaces—0
RLEEGNet: Integrating Brain-Computer Interfaces with Adaptive AI for Intuitive Responsiveness and High-Accuracy Motor Imagery Classification—0
Subject-Independent Deep Architecture for EEG-based Motor Imagery Classification—0
3D-CLMI: A Motor Imagery EEG Classification Model via Fusion of 3D-CNN and LSTM with Attention—0
Sparse Multitask Learning for Efficient Neural Representation of Motor Imagery and Execution—0
NiSNN-A: Non-iterative Spiking Neural Networks with Attention with Application to Motor Imagery EEG Classification—0
Latent Alignment with Deep Set EEG Decoders—0
Applying Dimensionality Reduction as Precursor to LSTM-CNN Models for Classifying Imagery and Motor Signals in ECoG-Based BCIsCode0
EEG-DG: A Multi-Source Domain Generalization Framework for Motor Imagery EEG ClassificationCode0
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