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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 76–100 of 252 papers

TitleStatusHype
Uncertainty Quantification for cross-subject Motor Imagery classificationCode0
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
Calibration-free online test-time adaptation for electroencephalography motor imagery decodingCode1
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
Neuro-GPT: Towards A Foundation Model for EEGCode2
Enhancing Motor Imagery Decoding in Brain Computer Interfaces using Riemann Tangent Space Mapping and Cross Frequency Coupling—0
Improved Motor Imagery Classification Using Adaptive Spatial Filters Based on Particle Swarm Optimization Algorithm—0
EEG motor imagery decoding: A framework for comparative analysis with channel attention mechanismsCode1
LGL-BCI: A Lightweight Geometric Learning Framework for Motor Imagery-Based Brain-Computer Interfaces—0
HappyFeat -- An interactive and efficient BCI framework for clinical applicationsCode1
Graph Neural Network-based EEG Classification: A Survey—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
Intentional binding enhances hybrid BCI control—0
Spatial Variation Generation Algorithm for Motor Imagery Data Augmentation: Increasing the Density of Sample VicinityCode1
A Strong and Simple Deep Learning Baseline for BCI MI DecodingCode1
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