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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
Transfer Learning for Brain-Computer Interfaces: A Euclidean Space Data Alignment ApproachCode1
EEGNet: A Compact Convolutional Network for EEG-based Brain-Computer InterfacesCode1
AFPM: Alignment-based Frame Patch Modeling for Cross-Dataset EEG Decoding—0
CATVis: Context-Aware Thought Visualization—0
Uncertainty Quantification for Motor Imagery BCI -- Machine Learning vs. Deep Learning—0
CLEAN-MI: A Scalable and Efficient Pipeline for Constructing High-Quality Neurodata in Motor Imagery Paradigm—0
Dataset combining EEG, eye-tracking, and high-speed video for ocular activity analysis across BCI paradigmsCode0
EEG Foundation Models for BCI Learn Diverse Features of Electrophysiology—0
Riemannian Flow Matching for Brain Connectivity Matrices via Pullback Geometry—0
Covariance Density Neural Networks—0
Transferring Spatial Filters via Tangent Space Alignment in Motor Imagery BCIs—0
SSTAF: Spatial-Spectral-Temporal Attention Fusion Transformer for Motor Imagery Classification—0
Optimized Feature Selection and Neural Network-Based Classification of Motor Imagery Using EEG Signals—0
A Generative System for Robot-to-Human Handovers: from Intent Inference to Spatial Configuration Imagery—0
Research on Event-Related Desynchronization of Motor Imagery and Movement Based on Localized EEG Cortical Sources—0
Motor Imagery EEG Signals: Multi-Task Classification and Subject Identification with a Lightweight CNN—0
Error-related Potential driven Reinforcement Learning for adaptive Brain-Computer Interfaces—0
Minima Possible Weights: A Homogenous Deep Ensemble Method for Cross-Subject Motor Imagery ClassificationCode0
Subject Specific Deep Learning Model for Motor Imagery Direction Decoding—0
Human-AI Teaming Using Large Language Models: Boosting Brain-Computer Interfacing (BCI) and Brain Research—0
Low count of optically pumped magnetometers furnishes a reliable real-time access to sensorimotor rhythm—0
Motor Imagery Classification for Asynchronous EEG-Based Brain-Computer InterfacesCode0
Robust Feature Engineering Techniques for Designing Efficient Motor Imagery-Based BCI-Systems—0
EEG-Based Mental Imagery Task Adaptation via Ensemble of Weight-Decomposed Low-Rank Adapters—0
Channel Reflection: Knowledge-Driven Data Augmentation for EEG-Based Brain-Computer Interfaces—0
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