Résumé
The World Health Organization (WHO) indicates that Musculoskeletal Disorders (MSD) “range from those that arise suddenly and are short-lived, such as fractures, sprains, and strains, tolifelong conditions associated with ongoing pain and disability” [1]. These conditions can man-ifest in individuals of any age and across global populations. They carry significant economicimplications, leading to a decline in work efficiency and adversely impacting the well-being ofthose affected.The "Regional Occupational Health Plan 2022-2025" for the Occitanie region mentions sev-eral figures to illustrate the necessity of placing health and prevention at the heart of workin the region: MSD represent 80% of recognized occupational diseases; 71% of employees areexposed to postural and articular constraints; 32% of employees are exposed to one or morechemicals regardless of their sector of activity. As for the statistical service responsible forlabor, employment, and vocational training within the public statistical system (DARES), itsanalysis No. 031 from August 2022 lists the thresholds above which exposure can be qualifiedas "onerous" (according to the Medical Surveillance of Employees’ Exposure to OccupationalRisks (SUMER) survey from 2017). However, it specifies that most quantification methods arebased on medical investigators’ expertise and employees’ perceptions [2].We focus on identifying and automatically calculating ergonomic risks in this context andthis preliminary work. First, we conduct a literature review on a well-known method called“REBA". Then, we use motion capture to analyze the human motion and calculate the REBAscore automatically