Deep Learning-Based Decoding and Feature Visualization of Motor Imagery Speeds From EEG Signals

<italic>Objective:</italic> This study investigates the neurodynamics of motor imagery speed decoding using deep learning. <italic>Methods:</italic> The EEGConformer model was employed to analyze EEG signals and decode different speeds of imagined movements. Explainable artificial intelligence techn...

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Autors principals:	Shogo Todoroki, Chatrin Phunruangsakao, Keisuke Goto, Kyo Kutsuzawa, Dai Owaki, Mitsuhiro Hayashibe
Format:	Artigo
Idioma:	Inglês
Publicat:	IEEE 2026-01-01
Col·lecció:	IEEE Open Journal of Engineering in Medicine and Biology
Matèries:	Brain-computer interface deep learning explainable artificial intelligence motor imagery speed decoding
Accés en línia:	https://ieeexplore.ieee.org/document/11303869/
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