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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 51–75 of 252 papers

TitleStatusHype
On-device Learning of EEGNet-based Network For Wearable Motor Imagery Brain-Computer Interface—0
How Does a Single EEG Channel Tell Us About Brain States in Brain-Computer Interfaces ?—0
EEGMamba: Bidirectional State Space Model with Mixture of Experts for EEG Multi-task Classification—0
Feature interpretability in BCIs: exploring the role of network lateralizationCode0
SCDM: Unified Representation Learning for EEG-to-fNIRS Cross-Modal Generation in MI-BCIs—0
Community Detection from Multiple Observations: from Product Graph Model to Brain Applications—0
Introducing the modularity graph: an application to brain functional networks—0
Single Channel-based Motor Imagery Classification using Fisher's Ratio and Pearson Correlation—0
Enhancing Computational Efficiency of Motor Imagery BCI Classification with Block-Toeplitz Augmented Covariance Matrices and Siegel Metric—0
GET: A Generative EEG Transformer for Continuous Context-Based Neural Signals—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
Subject-Adaptive Transfer Learning Using Resting State EEG Signals for Cross-Subject EEG Motor Imagery ClassificationCode1
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
The largest EEG-based BCI reproducibility study for open science: the MOABB benchmarkCode4
S-JEPA: towards seamless cross-dataset transfer through dynamic spatial attentionCode1
Unsupervised Adaptive Deep Learning Method For BCI Motor Imagery Decoding—0
Transferring BCI models from calibration to control: Observing shifts in EEG features—0
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