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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Detalhes bibliográficos
Main Authors: Giovanni Mostile, Salvatore Quattropani, Federico Contrafatto, Claudio Terravecchia, Michelangelo Riccardo Caci, Alessandra Chiara, Calogero Edoardo Cicero, Giulia Donzuso, Alessandra Nicoletti, Mario Zappia
Formato: Artigo
Idioma:English
Publicado em: Elsevier 2025-01-01
Colecção:Computational and Structural Biotechnology Journal
Assuntos:
Machine learning
Wereable sensors
EEG
Parkinson
Levodopa
Cognitive impairment
Acesso em linha:http://www.sciencedirect.com/science/article/pii/S2001037025000467

Internet

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

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