Introduces c-MVEP paradigm using motion stimulation, achieving 85.67% accuracy in online 4-class BCI with comparable SNR to c-VEP but different spatial distribution.
Event -related EEG/MEG synchronization and desynchronization: basic principles
2 Pith papers cite this work. Polarity classification is still indexing.
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2026 2representative citing papers
A preprocessing pipeline for resting-state and motor-task EEG is described to support future machine learning models that predict treatment efficacy in chronic neck pain.
citing papers explorer
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Beyond Flickering: Introducing Code-Modulated Motion Visual Evoked Potentials for Brain-Computer Interfacing
Introduces c-MVEP paradigm using motion stimulation, achieving 85.67% accuracy in online 4-class BCI with comparable SNR to c-VEP but different spatial distribution.
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A Machine Learning Framework for EEG-Based Prediction of Treatment Efficacy in Chronic Neck Pain
A preprocessing pipeline for resting-state and motor-task EEG is described to support future machine learning models that predict treatment efficacy in chronic neck pain.