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Open-source data management system for Parkinson’s disease follow-up

BACKGROUND: Parkinson’s disease (PD) is a neurodegenerative condition of the central nervous system that causes motor and non-motor dysfunctions. The disease affects 1% of the world population over 60 years and remains cureless. Knowledge and monitoring of PD are essential to provide better living c...

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Autores principales: Folador, João Paulo, Vieira, Marcus Fraga, Pereira, Adriano Alves, Andrade, Adriano de Oliveira
Formato: Online Artículo Texto
Lenguaje:English
Publicado: PeerJ Inc. 2021
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7959639/
https://www.ncbi.nlm.nih.gov/pubmed/33817042
http://dx.doi.org/10.7717/peerj-cs.396
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author Folador, João Paulo
Vieira, Marcus Fraga
Pereira, Adriano Alves
Andrade, Adriano de Oliveira
author_facet Folador, João Paulo
Vieira, Marcus Fraga
Pereira, Adriano Alves
Andrade, Adriano de Oliveira
author_sort Folador, João Paulo
collection PubMed
description BACKGROUND: Parkinson’s disease (PD) is a neurodegenerative condition of the central nervous system that causes motor and non-motor dysfunctions. The disease affects 1% of the world population over 60 years and remains cureless. Knowledge and monitoring of PD are essential to provide better living conditions for patients. Thus, diagnostic exams and monitoring of the disease can generate a large amount of data from a given patient. This study proposes the development and usability evaluation of an integrated system, which can be used in clinical and research settings to manage biomedical data collected from PD patients. METHODS: A system, so-called Sistema Integrado de Dados Biomédicos (SIDABI) (Integrated Biomedical Data System), was designed following the model-view-controller (MVC) standard. A modularized architecture was created in which all the other modules are connected to a central security module. Thirty-six examiners evaluated the system usability through the System Usability Scale (SUS). The agreement between examiners was measured by Kendall’s coefficient with a significance level of 1%. RESULTS: The free and open-source web-based system was implemented using modularized and responsive methods to adapt the system features on multiple platforms. The mean SUS score was 82.99 ± 13.97 points. The overall agreement was 70.2%, as measured by Kendall’s coefficient (p < 0.001). CONCLUSION: According to the SUS scores, the developed system has good usability. The system proposed here can help researchers to organize and share information, avoiding data loss and fragmentation. Furthermore, it can help in the follow-up of PD patients, in the training of professionals involved in the treatment of the disorder, and in studies that aim to find hidden correlations in data.
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spelling pubmed-79596392021-04-02 Open-source data management system for Parkinson’s disease follow-up Folador, João Paulo Vieira, Marcus Fraga Pereira, Adriano Alves Andrade, Adriano de Oliveira PeerJ Comput Sci Bioinformatics BACKGROUND: Parkinson’s disease (PD) is a neurodegenerative condition of the central nervous system that causes motor and non-motor dysfunctions. The disease affects 1% of the world population over 60 years and remains cureless. Knowledge and monitoring of PD are essential to provide better living conditions for patients. Thus, diagnostic exams and monitoring of the disease can generate a large amount of data from a given patient. This study proposes the development and usability evaluation of an integrated system, which can be used in clinical and research settings to manage biomedical data collected from PD patients. METHODS: A system, so-called Sistema Integrado de Dados Biomédicos (SIDABI) (Integrated Biomedical Data System), was designed following the model-view-controller (MVC) standard. A modularized architecture was created in which all the other modules are connected to a central security module. Thirty-six examiners evaluated the system usability through the System Usability Scale (SUS). The agreement between examiners was measured by Kendall’s coefficient with a significance level of 1%. RESULTS: The free and open-source web-based system was implemented using modularized and responsive methods to adapt the system features on multiple platforms. The mean SUS score was 82.99 ± 13.97 points. The overall agreement was 70.2%, as measured by Kendall’s coefficient (p < 0.001). CONCLUSION: According to the SUS scores, the developed system has good usability. The system proposed here can help researchers to organize and share information, avoiding data loss and fragmentation. Furthermore, it can help in the follow-up of PD patients, in the training of professionals involved in the treatment of the disorder, and in studies that aim to find hidden correlations in data. PeerJ Inc. 2021-02-17 /pmc/articles/PMC7959639/ /pubmed/33817042 http://dx.doi.org/10.7717/peerj-cs.396 Text en © 2021 Folador et al. https://creativecommons.org/licenses/by/4.0/ This is an open access article distributed under the terms of the Creative Commons Attribution License (https://creativecommons.org/licenses/by/4.0/) , which permits unrestricted use, distribution, reproduction and adaptation in any medium and for any purpose provided that it is properly attributed. For attribution, the original author(s), title, publication source (PeerJ Computer Science) and either DOI or URL of the article must be cited.
spellingShingle Bioinformatics
Folador, João Paulo
Vieira, Marcus Fraga
Pereira, Adriano Alves
Andrade, Adriano de Oliveira
Open-source data management system for Parkinson’s disease follow-up
title Open-source data management system for Parkinson’s disease follow-up
title_full Open-source data management system for Parkinson’s disease follow-up
title_fullStr Open-source data management system for Parkinson’s disease follow-up
title_full_unstemmed Open-source data management system for Parkinson’s disease follow-up
title_short Open-source data management system for Parkinson’s disease follow-up
title_sort open-source data management system for parkinson’s disease follow-up
topic Bioinformatics
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7959639/
https://www.ncbi.nlm.nih.gov/pubmed/33817042
http://dx.doi.org/10.7717/peerj-cs.396
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