Ergonomics and Machine Learning: Wearable Sensors in the Prevention of Work-Related Musculoskeletal Disorders

Abstract

One of the biggest challenges of the labor world is to ensure the health and well-being of the workers. Preventing work-related musculoskeletal disorders (WRMSDs) is increasingly relevant across all sectors. In recent studies, there has been a growing application of machine learning and sensory technology to develop strategies for ergonomic risk detection and prevention of WRMSDs in the short and long term. The use of wearable sensors allows real-time monitoring of workers’ postures, and has proven to be an asset for ergonomic studies due to its high accuracy. In addition to preventive applications, machine learning can increase workers’ productivity and safety. Despite being an area that shows great potential, it still has some limitations and opportunities for development. This literature review was carried out in a structured and systematic way based on the defined inclusion criteria and keywords chosen. Fifteen articles published between 2017 and 2022 were analyzed. This paper aims to study the current state of the use of the application of wearable sensors in Ergonomics and identify the challenges that this technology faces in the future.