Digital system for monitoring and analysis of musculoskeletal disorders using the kuorinka test

Abstract

This study proposes the design and implementation of an information system for monitoring musculoskeletal symptoms in workers, using the digitalized Nordic Kuorinka Test as a foundation. The objective was to develop a computational platform that enables efficient collection, processing, and visualization of ergonomic data to support decision-making in occupational health. The pilot application was carried out at a bottling plant in Riobamba, Ecuador, with a sample of 10 workers. Data were collected through digital forms and analyzed using automated spreadsheets, complemented by interactive visualizations developed in Power BI. This allowed for automated analysis with Excel formulas and dynamic visualization through interactive Power BI dashboards, facilitating the identification of critical ergonomic risk areas. The results showed a high prevalence of discomfort in the dorsal and cervical regions, associated with repetitive tasks and manual load handling. The system enabled the identification of priority ergonomic risks and the generation of preventive alerts. It is concluded that digitalizing the Kuorinka Test and integrating it into a data analysis tool significantly improves the efficiency of musculoskeletal disorder monitoring and strengthens preventive management in workplace environments.