Bibliographic citations
Bassino, F., Mosqueira, C. (2024). Estimación de Pose para prevenir trastornos musculoesqueléticos utilizando una Red recurrente de largo y corto plazo [Tesis, Universidad Peruana de Ciencias Aplicadas (UPC)]. http://hdl.handle.net/10757/683154
Bassino, F., Mosqueira, C. Estimación de Pose para prevenir trastornos musculoesqueléticos utilizando una Red recurrente de largo y corto plazo [Tesis]. PE: Universidad Peruana de Ciencias Aplicadas (UPC); 2024. http://hdl.handle.net/10757/683154
@misc{renati/1300216,
title = "Estimación de Pose para prevenir trastornos musculoesqueléticos utilizando una Red recurrente de largo y corto plazo",
author = "Mosqueira Chacon, Cesar Manuel",
publisher = "Universidad Peruana de Ciencias Aplicadas (UPC)",
year = "2024"
}
Office work has become the most prevalent occupation in contemporary society, necessitating long hours of sedentary behavior that can lead to mental and physical fatigue, including the risk of developing musculoskeletal disorders (MSDs). To address this issue, we have proposed an innovative system that utilizes the NAO robot for posture alerts, YoloV7 for landmark extraction, and an LSTM recurrent network for posture prediction. In our evaluation, the model achieved an accuracy of 85%, recall of 93%, and an F1 score of 89%. These metrics provide valuable insights into the system's effectiveness and highlight the areas where further refinements can be implemented. By refining the model and leveraging a more extensive dataset, we aim to enhance the accuracy and precision of bad posture detection, thereby empowering office workers to adopt healthier postural habits and reduce the risk of developing MSDs.
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