@inproceedings{3ab2a42a1fd741fdabaa5ba1dd355ba7,
title = "AI-Powered Early Detection of Musculoskeletal Disorders in Garment Industry Operators",
abstract = "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.",
keywords = "Bi-GRU, Bi-LSTM, CNN, Deep Learning, GRU, LSTM, Musculoskeletal Disorders",
author = "Ankit Vijayvargiya and Shruti Paliwal and Naveen Gehlot and Rajesh Kumar and Kieran Moran",
note = "Publisher Copyright: {\textcopyright} 2024 IEEE.; 2nd International Conference on Advancements in Smart, Secure and Intelligent Computing, ASSIC 2024 ; Conference date: 27-01-2024 Through 29-01-2024",
year = "2024",
doi = "10.1109/ASSIC60049.2024.10507807",
language = "English",
series = "Proceedings of 2nd International Conference on Advancements in Smart, Secure and Intelligent Computing, ASSIC 2024",
publisher = "Institute of Electrical and Electronics Engineers Inc.",
editor = "Sushruta Mishra and Tripathy, {Hrudaya Kumar} and Mohanty, {Jnyana Ranjan} and Sambit Mishra and Tarek Gaber and Sahoo, {Kshira Sagar}",
booktitle = "Proceedings of 2nd International Conference on Advancements in Smart, Secure and Intelligent Computing, ASSIC 2024",
address = "United States",
}