Aplicaciones de la inteligencia artificial en la identificación temprana de peligros y evaluación de riesgos ergonómicos: revisión sistemática de la literatura

Abstract

The general objective of this research project was to analyze, through a systematic review, the applications of artificial intelligence in the early detection and assessment of ergonomic risks, in order to establish its contribution to improving occupational health and safety management. The PRISMA methodology was used for the information search. Scopus, Web of Science, and PubMed were used as databases. The methodological quality of the research was evaluated using the guidelines of the JB manual, which, after carrying out the corresponding procedures, allowed for the selection of 20 academic sources that met the inclusion and exclusion criteria. The results showed that AI, through the implementation of techniques such as wearable sensors, human posture estimation, computer vision, and machine learning algorithms, helps to identify inadequate postures, biomechanical loads, and repetitive movements in workers. In general, it is concluded that AI provides greater precision, objectivity, and real-time monitoring capabilities, strengthening the prevention of musculoskeletal disorders and supporting preventive decision-making. Keywords: ergonomics, artificial intelligence, hazards, risks, occupational safety and health.