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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
Novel EEG-based BCIs for Elderly Rehabilitation Enhancement—0
On-device Learning of EEGNet-based Network For Wearable Motor Imagery Brain-Computer Interface—0
On the use of generative deep neural networks to synthesize artificial multichannel EEG signals—0
Optimized Feature Selection and Neural Network-Based Classification of Motor Imagery Using EEG Signals—0
Partial Least Square Regression via Three-factor SVD-type Manifold Optimization for EEG Decoding—0
Performance of Dual-Augmented Lagrangian Method and Common Spatial Patterns applied in classification of Motor-Imagery BCI—0
Phase/amplitude synchronization of brain signals during motor imagery BCI tasks—0
Phase Synchrony Component Self-Organization in Brain Computer Interface—0
Preliminary Assessment of hands motor imagery in theta- and beta-bands for Brain-Machine-Interfaces using functional connectivity analysis—0
Probabilistic Learning Vector Quantization on Manifold of Symmetric Positive Definite Matrices—0
Pseudo Channel: Time Embedding for Motor Imagery Decoding—0
Pseudo-online framework for BCI evaluation: A MOABB perspective—0
Real-Time EEG Classification via Coresets for BCI Applications—0
Research on Event-Related Desynchronization of Motor Imagery and Movement Based on Localized EEG Cortical Sources—0
Riemannian Flow Matching for Brain Connectivity Matrices via Pullback Geometry—0
RLEEGNet: Integrating Brain-Computer Interfaces with Adaptive AI for Intuitive Responsiveness and High-Accuracy Motor Imagery Classification—0
Robust Feature Engineering Techniques for Designing Efficient Motor Imagery-Based BCI-Systems—0
Robust Spatial Filtering with Beta Divergence—0
Scatter-based common spatial patterns -- a unified spatial filtering framework—0
SCDM: Unified Representation Learning for EEG-to-fNIRS Cross-Modal Generation in MI-BCIs—0
Siamese Neural Networks for EEG-based Brain-computer Interfaces—0
Sinc-based convolutional neural networks for EEG-BCI-based motor imagery classification—0
Single Channel-based Motor Imagery Classification using Fisher's Ratio and Pearson Correlation—0
Motor Imagery Classification for Asynchronous EEG-Based Brain-Computer InterfacesCode0
Feature interpretability in BCIs: exploring the role of network lateralizationCode0
RIGOLETTO -- RIemannian GeOmetry LEarning: applicaTion To cOnnectivity. A contribution to the Clinical BCI Challenge -- WCCI2020Code0
MixNet: Joining Force of Classical and Modern Approaches Toward the Comprehensive Pipeline in Motor Imagery EEG ClassificationCode0
Classification of Motor Imagery EEG Signals by Using a Divergence Based Convolutional Neural NetworkCode0
Classification of BCI-EEG based on augmented covariance matrixCode0
Q-EEGNet: an Energy-Efficient 8-bit Quantized Parallel EEGNet Implementation for Edge Motor-Imagery Brain--Machine InterfacesCode0
Mixed-Precision Quantization and Parallel Implementation of Multispectral Riemannian Classification for Brain--Machine InterfacesCode0
Quantifying Spatial Domain Explanations in BCI using Earth Mover's DistanceCode0
Minima Possible Weights: A Homogenous Deep Ensemble Method for Cross-Subject Motor Imagery ClassificationCode0
EEG-DCNet: A Fast and Accurate MI-EEG Dilated CNN Classification MethodCode0
Classification of High-Dimensional Motor Imagery Tasks based on An End-to-end role assigned convolutional neural networkCode0
Fast and Accurate Multiclass Inference for MI-BCIs Using Large Multiscale Temporal and Spectral FeaturesCode0
Towards Real-World BCI: CCSPNet, A Compact Subject-Independent Motor Imagery FrameworkCode0
Applying Dimensionality Reduction as Precursor to LSTM-CNN Models for Classifying Imagery and Motor Signals in ECoG-Based BCIsCode0
Improving Motor Imagery EEG Classification Based on Channel Selection Using a Deep Learning ArchitectureCode0
Uncertainty Quantification for cross-subject Motor Imagery classificationCode0
Federated Motor Imagery Classification for Privacy-Preserving Brain-Computer InterfacesCode0
Dataset combining EEG, eye-tracking, and high-speed video for ocular activity analysis across BCI paradigmsCode0
Aggregating Intrinsic Information to Enhance BCI Performance through Federated LearningCode0
Alignment-Based Adversarial Training (ABAT) for Improving the Robustness and Accuracy of EEG-Based BCIsCode0
Exploring Embedding Methods in Binary Hyperdimensional Computing: A Case Study for Motor-Imagery based Brain-Computer InterfacesCode0
Converting Your Thoughts to Texts: Enabling Brain Typing via Deep Feature Learning of EEG SignalsCode0
Transfer Learning between Motor Imagery Datasets using Deep Learning -- Validation of Framework and Comparison of DatasetsCode0
Complex common spatial patterns on time-frequency decomposed EEG for brain-computer interfaceCode0
EEG-DG: A Multi-Source Domain Generalization Framework for Motor Imagery EEG ClassificationCode0
Comparison of Classification Algorithms Towards Subject-Specific and Subject-Independent BCICode0
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