Artificial intelligence tools for engagement prediction in neuromotor disorder patients during rehabilitation

Artificial intelligence tools for engagement prediction in neuromotor disorder patients during rehabilitation

Abstract Background Robot-Assisted Gait Rehabilitation (RAGR) is an established clinical practice to encourage neuroplasticity in patients with neuromotor disorders. Nevertheless, tasks repetition imposed by robots may induce boredom, affecting clinical outcomes. Thus, quantitative assessment of eng...

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Bibliographic Details
Main Authors:	Simone Costantini, Anna Falivene, Mattia Chiappini, Giorgia Malerba, Carla Dei, Silvia Bellazzecca, Fabio A. Storm, Giuseppe Andreoni, Emilia Ambrosini, Emilia Biffi
Format:	Article
Language:	English
Published:	BMC 2024-12-01
Series:	Journal of NeuroEngineering and Rehabilitation
Subjects:	Robot-Assisted Gait Rehabilitation Engagement Psychophysiological signals Classification K-Nearest Neighbors Random forest
Online Access:	https://doi.org/10.1186/s12984-024-01519-2
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