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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
Decoding and interpreting cortical signals with a compact convolutional neural network—0
Decoding Brain Motor Imagery with various Machine Learning techniques—0
Decoding Imagined Movement in People with Multiple Sclerosis for Brain-Computer Interface Translation—0
Deep convolutional recurrent neural network for short-interval EEG motor imagery classification—0
Deep Feature Mining via Attention-based BiLSTM-GCN for Human Motor Imagery Recognition—0
Deep Learning Architecture for Motor Imaged Words—0
Deep learning for ECoG brain-computer interface: end-to-end vs. hand-crafted features—0
DGAFF: Deep Genetic Algorithm Fitness Formation for EEG Bio-Signal Channel Selection—0
Source Data Selection for Brain-Computer Interfaces based on Simple Features—0
Sparse Multitask Learning for Efficient Neural Representation of Motor Imagery and Execution—0
Spatial Filtering for Brain Computer Interfaces: A Comparison between the Common Spatial Pattern and Its Variant—0
Spatial Graph Signal Interpolation with an Application for Merging BCI Datasets with Various Dimensionalities—0
Spatial-Spectral Boosting Analysis for Stroke Patients' Motor Imagery EEG in Rehabilitation Training—0
Spatiotemporal Pooling on Appropriate Topological Maps Represented as Two-Dimensional Images for EEG Classification—0
Spectrally Adaptive Common Spatial Patterns—0
SSTAF: Spatial-Spectral-Temporal Attention Fusion Transformer for Motor Imagery Classification—0
Sub-100uW Multispectral Riemannian Classification for EEG-based Brain--Machine Interfaces—0
Subject-Independent Deep Architecture for EEG-based Motor Imagery Classification—0
Subject Specific Deep Learning Model for Motor Imagery Direction Decoding—0
Team Cogitat at NeurIPS 2021: Benchmarks for EEG Transfer Learning Competition—0
The evolution of AI approaches for motor imagery EEG-based BCIs—0
The Sandwich meta-framework for architecture agnostic deep privacy-preserving transfer learning for non-invasive brainwave decoding—0
Towards Asynchronous Motor Imagery-Based Brain-Computer Interfaces: a joint training scheme using deep learning—0
Towards Natural Brain-Machine Interaction using Endogenous Potentials based on Deep Neural Networks—0
Towards Personalized Brain-Computer Interface Application Based on Endogenous EEG Paradigms—0
Towards physiology-informed data augmentation for EEG-based BCIs—0
Transfer Learning Enhanced Common Spatial Pattern Filtering for Brain Computer Interfaces (BCIs): Overview and a New Approach—0
Transfer Learning for EEG-Based Brain-Computer Interfaces: A Review of Progress Made Since 2016—0
Transfer Learning improves MI BCI models classification accuracy in Parkinson's disease patients—0
Transfer Learning in Brain-Computer Interfaces with Adversarial Variational Autoencoders—0
Transferring BCI models from calibration to control: Observing shifts in EEG features—0
Transferring Spatial Filters via Tangent Space Alignment in Motor Imagery BCIs—0
Transferring Subspaces Between Subjects in Brain-Computer Interfacing—0
Uncertainty Quantification for Motor Imagery BCI -- Machine Learning vs. Deep Learning—0
Understanding Brain Connectivity Patterns during Motor Imagery for Brain-Computer Interfacing—0
Unsupervised Adaptive Deep Learning Method For BCI Motor Imagery Decoding—0
Unsupervised Motor Imagery Saliency Detection Based on Self-Attention Mechanism—0
Motor Imagery Classification of Single-Arm Tasks Using Convolutional Neural Network based on Feature Refining—0
Motor imagery classification using EEG spectrograms—0
Motor Imagery EEG Signals: Multi-Task Classification and Subject Identification with a Lightweight CNN—0
Motor Imagery Task Alters Dynamics of Human Body Posture—0
Multiclass Common Spatial Pattern for EEG based Brain Computer Interface with Adaptive Learning Classifier—0
Multiview Contrastive Learning for Unsupervised Domain Adaptation in Brain–Computer Interfaces—0
Mu-suppression detection in motor imagery electroencephalographic signals using the generalized extreme value distribution—0
MutualGraphNet: A novel model for motor imagery classification—0
Navigating in Virtual Reality using Thought: The Development and Assessment of a Motor Imagery based Brain-Computer Interface—0
Neural Network-Based Feature Extraction for Multi-Class Motor Imagery Classification—0
NeuroAssist: Enhancing Cognitive-Computer Synergy with Adaptive AI and Advanced Neural Decoding for Efficient EEG Signal Classification—0
Neurophysiological Analysis in Motor and Sensory Cortices for Improving Motor Imagination—0
NiSNN-A: Non-iterative Spiking Neural Networks with Attention with Application to Motor Imagery EEG Classification—0
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