An investigation of multimodal EMG-EEG fusion strategies for upper-limb gesture classification

. Upper-limb gesture identification is an important problem in the advancement of robotic prostheses. Prevailing research into classifying electromyographic (EMG) muscular data or electroencephalographic (EEG) brain data for this purpose is often limited in methodological rigour, the extent to which...

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Veröffentlicht in:	Journal of neural engineering Jg. 22; H. 4
Hauptverfasser:	Pritchard, Michael, Campelo, Felipe, Goldingay, Harry
Format:	Journal Article
Sprache:	Englisch
Veröffentlicht:	England IOP Publishing 01.08.2025
Schlagworte:	Adult Algorithms automated machine learning biosignal fusion Brain-Computer Interfaces brain-computer-interface Electroencephalography - classification Electroencephalography - methods Electromyography - classification Electromyography - methods Female Gestures Humans Machine Learning Male multimodal gesture classification Upper Extremity - physiology Young Adult biosignal fusion brain-computer-interface automated machine learning multimodal gesture classification
ISSN:	1741-2560, 1741-2552, 1741-2552
Online-Zugang:	Volltext
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