| Issue |
E3S Web Conf.
Volume 532, 2024
Second International Conference of Applied Industrial Engineering: Intelligent Production Automation and its Sustainable Development (CIIA 2024)
|
|
|---|---|---|
| Article Number | 02001 | |
| Number of page(s) | 14 | |
| Section | Applied Technological Innovations for Sustainable Industrial Environments | |
| DOI | https://doi.org/10.1051/e3sconf/202453202001 | |
| Published online | 06 June 2024 | |
Risk Assessment of Musculoskeletal Disorders Using Artificial Intelligence
1 Universidad de Guayaquil, Guayaquil, Ecuador
2 Universidad de Especialidades Espíritu Santo, Guayaquil, Ecuador
* Corresponding author: michelle.varasch@ug.edu.ec
Agricultural ergonomics employs methods such as Rapid Upper Limb Assessment (RULA) and Rapid Entire Body Assessment (REBA) to assess postural risks. However, these methods may be inaccurate and time-consuming. The objective of this study is to compare the effectiveness of Artificial Intelligence (AI), specifically a software based on MediaPipe, with conventional methods (RULA-REBA) to identify and assess ergonomic risks due to postures in rice agriculture. The methodology employed involved the development of AI software with MediaPipe, which was designed to detect postures in real time. This model was capable of identifying 33 anatomical points, thereby enabling detailed analysis of movement and posture. The results demonstrated that the AI outperformed RULA and REBA in detecting forced postures. Furthermore, it provided faster and more accurate assessments. The findings indicated that AI could be a valuable tool in agricultural ergonomics, potentially outperforming traditional methods. This could significantly improve working conditions and reduce musculoskeletal disorders among farmers.
© The Authors, published by EDP Sciences, 2024
This is an Open Access article distributed under the terms of the Creative Commons Attribution License 4.0, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
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