Testing machine learning algorithms to evaluate fluctuating and cognitive profiles in Parkinson’s disease by motion sensors and EEG data

Testing machine learning algorithms to evaluate fluctuating and cognitive profiles in Parkinson’s disease by motion sensors and EEG data

Objective: We aimed to test machine learning algorithms for classifying fluctuating and cognitive profiles in Parkinson’s Disease (PD) by using multimodal instrumental data. Methods: Data of motion transducers while performing instrumented Timed-Up-and-Go test (iTUG) (N = 30 subjects) and EEG (N = 4...

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Autori principali: Giovanni Mostile, Salvatore Quattropani, Federico Contrafatto, Claudio Terravecchia, Michelangelo Riccardo Caci, Alessandra Chiara, Calogero Edoardo Cicero, Giulia Donzuso, Alessandra Nicoletti, Mario Zappia
Natura: Articolo
Lingua:English
Pubblicazione: Elsevier 2025-01-01
Serie:Computational and Structural Biotechnology Journal
Soggetti:
Machine learning
Wereable sensors
EEG
Parkinson
Levodopa
Cognitive impairment
Accesso online:http://www.sciencedirect.com/science/article/pii/S2001037025000467

Accesso online

http://www.sciencedirect.com/science/article/pii/S2001037025000467

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