Work Helper: mobile application based on probabilistic model for assessing the risk of occupational low back pain

Authors

DOI:

https://doi.org/10.47456/bjpe.v11i4.50093

Keywords:

Low back pain, Ergonomics, Mobile application

Abstract

The prevalence of musculoskeletal disorders, particularly occupational low back pain, represents a persistent challenge to public health and industrial productivity. This study aimed to develop a mobile application based on a probabilistic model for assessing the risk of occupational low back pain. Development followed the agile Scrum methodology, applying principles of service-oriented software engineering, with iterative cycles of implementation and testing on both the frontend and backend. To calculate the risk of low back pain, the probabilistic model proposed by Santos and Monteiro (2020), derived from multiple logistic regression with 84 workers, was adopted. During the implementation phase, the application, called Work Helper, demonstrated the ability to calculate ergonomic risk levels and generate personalized action plans for mitigation. The information is presented in interactive reports, including risk distribution by sector, key identified factors, and prioritized recommendations, providing immediate support for decision-making and continuous monitoring of occupational health. This performance demonstrates the feasibility of integrating probabilistic models into a mobile application, offering a replicable approach that contributes to the prevention of occupational low back pain in various work environments.

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Author Biographies

  • José Welton dos Santos, Instituto Federal de Sergipe

    I hold a degree in Systems Analysis and Development and a Technical degree in Building Construction from the Federal Institute of Education, Science and Technology of Sergipe (IFS). I have a solid foundation in full-stack programming. Currently, I work as a Software Quality Analyst (QA) at DBC Company, actively participating in testing, automation, and quality assurance processes in systems development projects. I am interested in continuously evolving in areas related to software engineering, test automation, and quality best practices, contributing to the delivery of more reliable and innovative digital products.

  • José Wendel dos Santos, Universidade Federal de Sergipe

    Master's degree in Intellectual Property Science and Bachelor's degree in Production Engineering from the Federal University of Sergipe (UFS). Technician in Occupational Safety from the Federal Institute of Sergipe (IFS). Currently a doctoral candidate in Intellectual Property Science at UFS. Has worked on research projects linked to the Institutional Program for Scientific Initiation (PIBIC) and the Program for Initiation in Technological Development and Innovation (PIBITI), both at UFS. Received scholarships from the Coordination for the Improvement of Higher Education Personnel (CAPES), the National Council for Scientific and Technological Development (CNPq), and the Foundation for Support of Research and Technological Innovation of the State of Sergipe (FAPITEC/SE). Was a member of the Production Engineering Research Group (GPEP/UFS). Has national and international publications, with award-winning works at scientific events. Acts as a reviewer for journals and organizer of academic events. Has experience in the field of Production Engineering, with an emphasis on occupational biomechanics, health and safety at work. Conducts research in the area of ​​Intellectual Property, focusing on patent data mining and modeling technological trends in emerging markets.

  • Pedro Vieira Souza Santos, Universidade Federal de Pernambuco

    Máster en Ingeniería de Producción (UFPE). Licenciado en Ingeniería de Producción (UNIVASF), con experiencia en Logística de Distribución, Gestión de la Producción y Relaciones Internacionales, con producción científica en diversas áreas de la Ingeniería de Producción. Diplomatura en Medidas Físicas del Instituto Universitario de Tecnología de Blois - IUT / Universidad François-Rabelais (Francia - 2014). Técnico en Electromecánica del Servicio Nacional de Formación Profesional (SENAI/PE - 2010) con especialización en mecanizado y gestión del mantenimiento industrial. Colabora activamente como revisor en revistas nacionales e internacionales de Ingeniería y áreas afines. Sus intereses se centran en la Lean Manufacturing, la Optimización de Procesos de Producción y la Educación en Ingeniería de Producción. Trabaja como profesor, investigador y creador de contenido.

  • Glauco Luiz Rezende de Carvalho, Instituto Federal de Sergipe

    Glauco Luiz Rezende de Carvalho holds a Master's degree in Computer Science from the Federal University of Sergipe (2017), a Specialization in Software Development from the Federal University of Sergipe (2007), a Bachelor's degree in Information Systems from Tiradentes University (2005), and a Bachelor's degree in Pedagogical Training in Informatics (2020) from the Leonardo da Vinci University Center - UNIASSELVI. He is currently a tenured professor at the Federal Institute of Sergipe - IFS, Aracaju Campus, and a Systems Analyst at the Public Prosecutor's Office of the State of Sergipe - MPSE. He is a consultant with active participation in the corporate market in the areas of Computer Science, particularly in Databases and Business Intelligence. He was Commercial Director for over 12 years at Infracenter Soluções Corporativas Ltda, where he was a founding partner.

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Cover image showing a person wearing a blue shirt holding their lower back in pain, illustrating the theme of occupational low back pain for the article ‘Work Helper: Mobile Application Based on Probabilistic Model for Assessing the Risk of Occupational Low Back Pain.

Published

2025-11-17

How to Cite

Santos, J. W. dos, Santos, J. W. dos, Santos, P. V. S., & Carvalho, G. L. R. de. (2025). Work Helper: mobile application based on probabilistic model for assessing the risk of occupational low back pain. Brazilian Journal of Production Engineering, 11(4), 194-210. https://doi.org/10.47456/bjpe.v11i4.50093

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