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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 151–200 of 252 papers

TitleStatusHype
Deep learning for ECoG brain-computer interface: end-to-end vs. hand-crafted features—0
Impact of dataset size and long-term ECoG-based BCI usage on deep learning decoders performance—0
Classification of eye-state using EEG recordings: speed-up gains using signal epochs and mutual information measure—0
Partial Least Square Regression via Three-factor SVD-type Manifold Optimization for EEG Decoding—0
An intertwined neural network model for EEG classification in brain-computer interfaces—0
Improving Motor Imagery EEG Classification Based on Channel Selection Using a Deep Learning ArchitectureCode0
Factorization Approach for Sparse Spatio-Temporal Brain-Computer Interface—0
Classification of EEG Motor Imagery Using Deep Learning for Brain-Computer Interface Systems—0
Unsupervised Motor Imagery Saliency Detection Based on Self-Attention Mechanism—0
A Subject-Independent Brain-Computer Interface Framework Based on Supervised Autoencoder—0
A self-paced BCI system with low latency for motor imagery onset detection based on time series prediction paradigm—0
MI-BMInet: An Efficient Convolutional Neural Network for Motor Imagery Brain--Machine Interfaces with EEG Channel Selection—0
Towards physiology-informed data augmentation for EEG-based BCIs—0
DGAFF: Deep Genetic Algorithm Fitness Formation for EEG Bio-Signal Channel Selection—0
Spectrally Adaptive Common Spatial Patterns—0
Team Cogitat at NeurIPS 2021: Benchmarks for EEG Transfer Learning Competition—0
Enhanced motor imagery-based EEG classification using a discriminative graph Fourier subspace—0
Neural Network-Based Feature Extraction for Multi-Class Motor Imagery Classification—0
Uncertainty Detection and Reduction in Neural Decoding of EEG SignalsCode0
Sub-100uW Multispectral Riemannian Classification for EEG-based Brain--Machine Interfaces—0
Interpretable Convolutional Neural Networks for Subject-Independent Motor Imagery Classification—0
Minimizing subject-dependent calibration for BCI with Riemannian transfer learning—0
A channel attention based MLP-Mixer network for motor imagery decoding with EEG—0
Novel EEG-based BCIs for Elderly Rehabilitation Enhancement—0
Deep convolutional recurrent neural network for short-interval EEG motor imagery classification—0
MutualGraphNet: A novel model for motor imagery classification—0
A SPA-based Manifold Learning Framework for Motor Imagery EEG Data Classification—0
Classification of Upper Arm Movements from EEG signals using Machine Learning with ICA Analysis—0
Motor Imagery Classification based on CNN-GRU Network with Spatio-Temporal Feature Representation—0
Complex common spatial patterns on time-frequency decomposed EEG for brain-computer interfaceCode0
Towards Natural Brain-Machine Interaction using Endogenous Potentials based on Deep Neural Networks—0
Generating Ten BCI Commands Using Four Simple Motor Imageries—0
Classification of Motor Imagery EEG Signals by Using a Divergence Based Convolutional Neural NetworkCode0
A New Method for Features Normalization in Motor Imagery Few-Shot Learning using Resting-State—0
Model-Agnostic Meta-Learning for EEG Motor Imagery Decoding in Brain-Computer-Interfacing—0
Inter-subject Deep Transfer Learning for Motor Imagery EEG Decoding—0
Gaze-contingent decoding of human navigation intention on an autonomous wheelchair platform—0
Decoding and interpreting cortical signals with a compact convolutional neural network—0
Mixed-Precision Quantization and Parallel Implementation of Multispectral Riemannian Classification for Brain--Machine InterfacesCode0
On the use of generative deep neural networks to synthesize artificial multichannel EEG signals—0
End-to-end learnable EEG channel selection for deep neural networks with Gumbel-softmax—0
RIGOLETTO -- RIemannian GeOmetry LEarning: applicaTion To cOnnectivity. A contribution to the Clinical BCI Challenge -- WCCI2020Code0
Common Spatial Generative Adversarial Networks based EEG Data Augmentation for Cross-Subject Brain-Computer Interface—0
Probabilistic Learning Vector Quantization on Manifold of Symmetric Positive Definite Matrices—0
Sinc-based convolutional neural networks for EEG-BCI-based motor imagery classification—0
Motor-Imagery-Based Brain Computer Interface using Signal Derivation and Aggregation Functions—0
A Ternary Bi-Directional LSTM Classification for Brain Activation Pattern Recognition Using fNIRS—0
A Deep Learning Based Ternary Task Classification System Using Gramian Angular Summation Field in fNIRS Neuroimaging Data—0
Towards Real-World BCI: CCSPNet, A Compact Subject-Independent Motor Imagery FrameworkCode0
Comparison of Classification Algorithms Towards Subject-Specific and Subject-Independent BCICode0
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