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Related Experiment Video

Updated: Nov 10, 2025

Dynamic Digital Biomarkers of Motor and Cognitive Function in Parkinson's Disease
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Open-source data management system for Parkinson's disease follow-up.

João Paulo Folador1, Marcus Fraga Vieira2, Adriano Alves Pereira1

  • 1Centre 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.

Peerj. Computer Science
|April 5, 2021
PubMed
Summary

This study developed an integrated biomedical data system for Parkinson's disease (PD) management. The user-friendly system effectively organizes patient data, aiding research and clinical follow-up for this neurodegenerative condition.

Keywords:
Data managementParkinson’s diseaseSystem usability scale

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Area of Science:

  • Biomedical Informatics
  • Neuroscience

Background:

  • Parkinson's disease (PD) is a prevalent neurodegenerative disorder affecting 1% of individuals over 60, characterized by motor and non-motor symptoms.
  • Currently, PD lacks a cure, highlighting the need for effective patient monitoring and data management to improve care.
  • The complexity of PD diagnosis and monitoring generates substantial patient data, necessitating robust management solutions.

Purpose of the Study:

  • To develop and evaluate the usability of an integrated system for managing biomedical data from Parkinson's disease patients.
  • To create a system applicable in both clinical and research environments for enhanced PD data handling.

Main Methods:

  • The Sistema Integrado de Dados Biomédicos (SIDABI) was designed using the Model-View-Controller (MVC) architecture with a central security module.
  • System usability was assessed by 36 examiners using the System Usability Scale (SUS).
  • Inter-rater agreement was quantified using Kendall's coefficient with a 1% significance level.

Main Results:

  • A free, open-source, web-based system was implemented, featuring modular and responsive design for cross-platform compatibility.
  • The system achieved a mean SUS score of 82.99 ± 13.97, indicating good usability.
  • Kendall's coefficient confirmed significant agreement among examiners (70.2%, p < 0.001).

Conclusions:

  • The developed SIDABI system demonstrates good usability based on SUS scores.
  • The system facilitates organized information management and sharing for researchers, mitigating data loss and fragmentation.
  • SIDABI can support Parkinson's disease patient follow-up, professional training, and the identification of hidden data correlations.