AI-Powered Early Detection of Musculoskeletal Disorders in Garment Industry Operators

The issue of work-related musculoskeletal disorders (WRMSD) is becoming increasingly prominent in occupational health and workplace safety, affecting a growing number of individuals. This pressing issue demands increased attention, especially in crucial sectors like the garment industry. In response to this challenge, our study focuses on developing and evaluating deep learning models to facilitate the early prediction and diagnosis of WRMSD in garment industry workers. This research investigates the potential of several deep learning models and conducts a comparative analysis of their performance metrics. The findings demonstrate that the Bi-directional Gated Recurrent Unit model achieved a remarkable accuracy of 97.19%, surpassing all other deep learning models examined in this study.