Cargando…

Statistical Analysis and Kinematic Assessment of Upper Limb Reaching Task in Parkinson’s Disease

The impact of neurodegenerative disorders is twofold; they affect both quality of life and healthcare expenditure. In the case of Parkinson’s disease, several strategies have been attempted to support the pharmacological treatment with rehabilitation protocols aimed at restoring motor function. In t...

Descripción completa

Detalles Bibliográficos
Autores principales: Ponsiglione, Alfonso Maria, Ricciardi, Carlo, Amato, Francesco, Cesarelli, Mario, Cesarelli, Giuseppe, D’Addio, Giovanni
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2022
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8915106/
https://www.ncbi.nlm.nih.gov/pubmed/35270853
http://dx.doi.org/10.3390/s22051708
_version_ 1784667934850809856
author Ponsiglione, Alfonso Maria
Ricciardi, Carlo
Amato, Francesco
Cesarelli, Mario
Cesarelli, Giuseppe
D’Addio, Giovanni
author_facet Ponsiglione, Alfonso Maria
Ricciardi, Carlo
Amato, Francesco
Cesarelli, Mario
Cesarelli, Giuseppe
D’Addio, Giovanni
author_sort Ponsiglione, Alfonso Maria
collection PubMed
description The impact of neurodegenerative disorders is twofold; they affect both quality of life and healthcare expenditure. In the case of Parkinson’s disease, several strategies have been attempted to support the pharmacological treatment with rehabilitation protocols aimed at restoring motor function. In this scenario, the study of upper limb control mechanisms is particularly relevant due to the complexity of the joints involved in the movement of the arm. For these reasons, it is difficult to define proper indicators of the rehabilitation outcome. In this work, we propose a methodology to analyze and extract an ensemble of kinematic parameters from signals acquired during a complex upper limb reaching task. The methodology is tested in both healthy subjects and Parkinson’s disease patients (N = 12), and a statistical analysis is carried out to establish the value of the extracted kinematic features in distinguishing between the two groups under study. The parameters with the greatest number of significances across the submovements are duration, mean velocity, maximum velocity, maximum acceleration, and smoothness. Results allowed the identification of a subset of significant kinematic parameters that could serve as a proof-of-concept for a future definition of potential indicators of the rehabilitation outcome in Parkinson’s disease.
format Online
Article
Text
id pubmed-8915106
institution National Center for Biotechnology Information
language English
publishDate 2022
publisher MDPI
record_format MEDLINE/PubMed
spelling pubmed-89151062022-03-12 Statistical Analysis and Kinematic Assessment of Upper Limb Reaching Task in Parkinson’s Disease Ponsiglione, Alfonso Maria Ricciardi, Carlo Amato, Francesco Cesarelli, Mario Cesarelli, Giuseppe D’Addio, Giovanni Sensors (Basel) Article The impact of neurodegenerative disorders is twofold; they affect both quality of life and healthcare expenditure. In the case of Parkinson’s disease, several strategies have been attempted to support the pharmacological treatment with rehabilitation protocols aimed at restoring motor function. In this scenario, the study of upper limb control mechanisms is particularly relevant due to the complexity of the joints involved in the movement of the arm. For these reasons, it is difficult to define proper indicators of the rehabilitation outcome. In this work, we propose a methodology to analyze and extract an ensemble of kinematic parameters from signals acquired during a complex upper limb reaching task. The methodology is tested in both healthy subjects and Parkinson’s disease patients (N = 12), and a statistical analysis is carried out to establish the value of the extracted kinematic features in distinguishing between the two groups under study. The parameters with the greatest number of significances across the submovements are duration, mean velocity, maximum velocity, maximum acceleration, and smoothness. Results allowed the identification of a subset of significant kinematic parameters that could serve as a proof-of-concept for a future definition of potential indicators of the rehabilitation outcome in Parkinson’s disease. MDPI 2022-02-22 /pmc/articles/PMC8915106/ /pubmed/35270853 http://dx.doi.org/10.3390/s22051708 Text en © 2022 by the authors. https://creativecommons.org/licenses/by/4.0/Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/).
spellingShingle Article
Ponsiglione, Alfonso Maria
Ricciardi, Carlo
Amato, Francesco
Cesarelli, Mario
Cesarelli, Giuseppe
D’Addio, Giovanni
Statistical Analysis and Kinematic Assessment of Upper Limb Reaching Task in Parkinson’s Disease
title Statistical Analysis and Kinematic Assessment of Upper Limb Reaching Task in Parkinson’s Disease
title_full Statistical Analysis and Kinematic Assessment of Upper Limb Reaching Task in Parkinson’s Disease
title_fullStr Statistical Analysis and Kinematic Assessment of Upper Limb Reaching Task in Parkinson’s Disease
title_full_unstemmed Statistical Analysis and Kinematic Assessment of Upper Limb Reaching Task in Parkinson’s Disease
title_short Statistical Analysis and Kinematic Assessment of Upper Limb Reaching Task in Parkinson’s Disease
title_sort statistical analysis and kinematic assessment of upper limb reaching task in parkinson’s disease
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8915106/
https://www.ncbi.nlm.nih.gov/pubmed/35270853
http://dx.doi.org/10.3390/s22051708
work_keys_str_mv AT ponsiglionealfonsomaria statisticalanalysisandkinematicassessmentofupperlimbreachingtaskinparkinsonsdisease
AT ricciardicarlo statisticalanalysisandkinematicassessmentofupperlimbreachingtaskinparkinsonsdisease
AT amatofrancesco statisticalanalysisandkinematicassessmentofupperlimbreachingtaskinparkinsonsdisease
AT cesarellimario statisticalanalysisandkinematicassessmentofupperlimbreachingtaskinparkinsonsdisease
AT cesarelligiuseppe statisticalanalysisandkinematicassessmentofupperlimbreachingtaskinparkinsonsdisease
AT daddiogiovanni statisticalanalysisandkinematicassessmentofupperlimbreachingtaskinparkinsonsdisease