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Feasibility of a Mobile-Based System for Unsupervised Monitoring in Parkinson’s Disease
Mobile health (mHealth) has emerged as a potential solution to providing valuable ecological information about the severity and burden of Parkinson’s disease (PD) symptoms in real-life conditions. Objective: The objective of our study was to explore the feasibility and usability of an mHealth system...
Autores principales: | , , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
MDPI
2021
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8347665/ https://www.ncbi.nlm.nih.gov/pubmed/34372208 http://dx.doi.org/10.3390/s21154972 |
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author | Bouça-Machado, Raquel Pona-Ferreira, Filipa Leitão, Mariana Clemente, Ana Vila-Viçosa, Diogo Kauppila, Linda Azevedo Costa, Rui M. Matias, Ricardo Ferreira, Joaquim J. |
author_facet | Bouça-Machado, Raquel Pona-Ferreira, Filipa Leitão, Mariana Clemente, Ana Vila-Viçosa, Diogo Kauppila, Linda Azevedo Costa, Rui M. Matias, Ricardo Ferreira, Joaquim J. |
author_sort | Bouça-Machado, Raquel |
collection | PubMed |
description | Mobile health (mHealth) has emerged as a potential solution to providing valuable ecological information about the severity and burden of Parkinson’s disease (PD) symptoms in real-life conditions. Objective: The objective of our study was to explore the feasibility and usability of an mHealth system for continuous and objective real-life measures of patients’ health and functional mobility, in unsupervised settings. Methods: Patients with a clinical diagnosis of PD, who were able to walk unassisted, and had an Android smartphone were included. Patients were asked to answer a daily survey, to perform three weekly active tests, and to perform a monthly in-person clinical assessment. Feasibility and usability were explored as primary and secondary outcomes. An exploratory analysis was performed to investigate the correlation between data from the mKinetikos app and clinical assessments. Results: Seventeen participants (85%) completed the study. Sixteen participants (94.1%) showed a medium-to-high level of compliance with the mKinetikos system. A 6-point drop in the total score of the Post-Study System Usability Questionnaire was observed. Conclusions: Our results support the feasibility of the mKinetikos system for continuous and objective real-life measures of a patient’s health and functional mobility. The observed correlations of mKinetikos metrics with clinical data seem to suggest that this mHealth solution is a promising tool to support clinical decisions. |
format | Online Article Text |
id | pubmed-8347665 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2021 |
publisher | MDPI |
record_format | MEDLINE/PubMed |
spelling | pubmed-83476652021-08-08 Feasibility of a Mobile-Based System for Unsupervised Monitoring in Parkinson’s Disease Bouça-Machado, Raquel Pona-Ferreira, Filipa Leitão, Mariana Clemente, Ana Vila-Viçosa, Diogo Kauppila, Linda Azevedo Costa, Rui M. Matias, Ricardo Ferreira, Joaquim J. Sensors (Basel) Article Mobile health (mHealth) has emerged as a potential solution to providing valuable ecological information about the severity and burden of Parkinson’s disease (PD) symptoms in real-life conditions. Objective: The objective of our study was to explore the feasibility and usability of an mHealth system for continuous and objective real-life measures of patients’ health and functional mobility, in unsupervised settings. Methods: Patients with a clinical diagnosis of PD, who were able to walk unassisted, and had an Android smartphone were included. Patients were asked to answer a daily survey, to perform three weekly active tests, and to perform a monthly in-person clinical assessment. Feasibility and usability were explored as primary and secondary outcomes. An exploratory analysis was performed to investigate the correlation between data from the mKinetikos app and clinical assessments. Results: Seventeen participants (85%) completed the study. Sixteen participants (94.1%) showed a medium-to-high level of compliance with the mKinetikos system. A 6-point drop in the total score of the Post-Study System Usability Questionnaire was observed. Conclusions: Our results support the feasibility of the mKinetikos system for continuous and objective real-life measures of a patient’s health and functional mobility. The observed correlations of mKinetikos metrics with clinical data seem to suggest that this mHealth solution is a promising tool to support clinical decisions. MDPI 2021-07-21 /pmc/articles/PMC8347665/ /pubmed/34372208 http://dx.doi.org/10.3390/s21154972 Text en © 2021 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 Bouça-Machado, Raquel Pona-Ferreira, Filipa Leitão, Mariana Clemente, Ana Vila-Viçosa, Diogo Kauppila, Linda Azevedo Costa, Rui M. Matias, Ricardo Ferreira, Joaquim J. Feasibility of a Mobile-Based System for Unsupervised Monitoring in Parkinson’s Disease |
title | Feasibility of a Mobile-Based System for Unsupervised Monitoring in Parkinson’s Disease |
title_full | Feasibility of a Mobile-Based System for Unsupervised Monitoring in Parkinson’s Disease |
title_fullStr | Feasibility of a Mobile-Based System for Unsupervised Monitoring in Parkinson’s Disease |
title_full_unstemmed | Feasibility of a Mobile-Based System for Unsupervised Monitoring in Parkinson’s Disease |
title_short | Feasibility of a Mobile-Based System for Unsupervised Monitoring in Parkinson’s Disease |
title_sort | feasibility of a mobile-based system for unsupervised monitoring in parkinson’s disease |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8347665/ https://www.ncbi.nlm.nih.gov/pubmed/34372208 http://dx.doi.org/10.3390/s21154972 |
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