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

Author:

Folador João Paulo1ORCID,Vieira Marcus Fraga2ORCID,Pereira Adriano Alves1,Andrade Adriano de Oliveira1ORCID

Affiliation:

1. Centre for Innovation and Technology Assessment in Health, Postgraduate Program in Electrical and Biomedical Engineering, Faculty of Electrical Engineering, Federal University of Uberlândia, Uberlândia, Minas Gerais, Brazil

2. Bioengineering and Biomechanics Laboratory, Federal University of Goiás, Goiânia, Goiás, Brazil

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.

Funder

National Council for Scientific and Technological Development

State of Minas Gerais

CNPq, Brazil

Publisher

PeerJ

Subject

General Computer Science

Reference47 articles.

1. Big data in digital healthcare: lessons learnt and recommendations for general practice;Agrawal;Heredity,2020

2. Human tremor: origins, detection and quantification—in: practical applications in biomedical engineering [Internet]—InTech; 2013;Andrade,2013

3. A reliability assessment software using Kinect to complement the clinical evaluation of Parkinson’s disease;Arango Paredes,2015

4. Determining what individual SUS scores mean: adding an adjective rating scale;Bangor;Journal of Usability Studies,2009

5. Patient-tailored augmented reality games for assessing upper extremity motor impairments in Parkinson’s disease and stroke;Bank;Journal of Medical Systems,2018

同舟云学术

1.学者识别学者识别

2.学术分析学术分析

3.人才评估人才评估

"同舟云学术"是以全球学者为主线,采集、加工和组织学术论文而形成的新型学术文献查询和分析系统,可以对全球学者进行文献检索和人才价值评估。用户可以通过关注某些学科领域的顶尖人物而持续追踪该领域的学科进展和研究前沿。经过近期的数据扩容,当前同舟云学术共收录了国内外主流学术期刊6万余种,收集的期刊论文及会议论文总量共计约1.5亿篇,并以每天添加12000余篇中外论文的速度递增。我们也可以为用户提供个性化、定制化的学者数据。欢迎来电咨询!咨询电话:010-8811{复制后删除}0370

www.globalauthorid.com

TOP

Copyright © 2019-2024 北京同舟云网络信息技术有限公司
京公网安备11010802033243号  京ICP备18003416号-3