Literature DB >> 33817042

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

João Paulo Folador1, Marcus Fraga Vieira2, Adriano Alves Pereira1, Adriano de Oliveira Andrade1.   

Abstract

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.
© 2021 Folador et al.

Entities:  

Keywords:  Data management; Parkinson’s disease; System usability scale

Year:  2021        PMID: 33817042      PMCID: PMC7959639          DOI: 10.7717/peerj-cs.396

Source DB:  PubMed          Journal:  PeerJ Comput Sci        ISSN: 2376-5992


  14 in total

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Journal:  Conf Proc IEEE Eng Med Biol Soc       Date:  2016-08

4.  PRISM: A DATA-DRIVEN PLATFORM FOR MONITORING MENTAL HEALTH.

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5.  Preliminary results of ON/OFF detection using an integrated system for Parkinson's disease monitoring.

Authors:  Matteo Pastorino; Jorge Cancela; Maria T Arredondo; Laura Pastor-Sanz; Sara Contardi; Franco Valzania
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Authors:  Ivo D Dinov; Ben Heavner; Ming Tang; Gustavo Glusman; Kyle Chard; Mike Darcy; Ravi Madduri; Judy Pa; Cathie Spino; Carl Kesselman; Ian Foster; Eric W Deutsch; Nathan D Price; John D Van Horn; Joseph Ames; Kristi Clark; Leroy Hood; Benjamin M Hampstead; William Dauer; Arthur W Toga
Journal:  PLoS One       Date:  2016-08-05       Impact factor: 3.240

7.  Design and development of a gait training system for Parkinson's disease.

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Review 8.  Big data in digital healthcare: lessons learnt and recommendations for general practice.

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9.  Developing a Tool for Remote Digital Assessment of Parkinson's Disease.

Authors:  Panagiotis Kassavetis; Tabish A Saifee; George Roussos; Loukas Drougkas; Maja Kojovic; John C Rothwell; Mark J Edwards; Kailash P Bhatia
Journal:  Mov Disord Clin Pract       Date:  2015-10-20

10.  Average annual cost of Parkinson's disease in São Paulo, Brazil, with a focus on disease-related motor symptoms.

Authors:  Tânia M Bovolenta; Sônia Maria Cesar de Azevedo Silva; Roberta Arb Saba; Vanderci Borges; Henrique Ballalai Ferraz; Andre C Felicio
Journal:  Clin Interv Aging       Date:  2017-12-14       Impact factor: 4.458

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