Dipartimento di Ingegneria informatica, automatica e gestionale

This study presents an innovative training tool based on the digitalization of ISO/TR 12295 and ISO 11228-1 standards. It utilizes Computer Vision techniques to enhance the training of operators in lifting and carrying tasks, addressing the prevalent issue of musculoskeletal disorders (MSDs) in occupational settings caused by repetitive movements and improper techniques. The system employs pose detection and object recognition techniques, to enable real-time monitoring of operator movements. Additionally, it facilitates the semi-automated generation of reports that incorporate ergonomic indicators such as the Revised National Institute for Occupational Safety and Health (NIOSH) Lifting Equation and the Rapid Upper Limb Assessment (RULA) index. These reports serve as educational tools, helping operators understand their actions and identify potential ergonomic risks. In a case study, the system effectively identified incorrect actions and provided comprehensive reports with in-depth analyses and actionable improvement suggestions. The system demonstrated adaptability across a diverse range of individuals within the same occupational setting, thereby enhancing its practical utility. While these results are encouraging, it is important to note that the system is currently in a pilot phase and requires further validation through testing on a larger and more diverse sample in various occupational settings.