Citas bibligráficas
Ayamamani, L., Bances, R., Cabrera, C., Alcantara, M. (2023). Desarrollo de un software web para la clasificación, comparación, retroalimentación y predicción de pérdida de calorías de cinco ejercicios de calistenia [Trabajo de investigación, Universidad Peruana de Ciencias Aplicadas (UPC)]. http://hdl.handle.net/10757/672185
Ayamamani, L., Bances, R., Cabrera, C., Alcantara, M. Desarrollo de un software web para la clasificación, comparación, retroalimentación y predicción de pérdida de calorías de cinco ejercicios de calistenia [Trabajo de investigación]. PE: Universidad Peruana de Ciencias Aplicadas (UPC); 2023. http://hdl.handle.net/10757/672185
@mastersthesis{renati/414233,
title = "Desarrollo de un software web para la clasificación, comparación, retroalimentación y predicción de pérdida de calorías de cinco ejercicios de calistenia",
author = "Alcantara Zapata, Manuel David",
publisher = "Universidad Peruana de Ciencias Aplicadas (UPC)",
year = "2023"
}
Physical activity is a fundamental pillar in the promotion of health and well-being of people. According to the World Health Organization (WHO, 2020) at least 4 million deaths per year could be avoided if the world's population were more active; because, physical activity helps prevent and treat non-communicable diseases such as cardiovascular disease, type 2 diabetes and some types of cancer. In addition, physical activity is also beneficial for mental health, helps maintain a healthy weight and contributes to overall well-being. Social isolation due to COVID-19 altered, decreased or even eliminated exercise in gyms or in open spaces. Also, labor policies encouraged remote work and with it, people eliminated daily physical activities with which they exercised in some way. For example, many people stopped walking for a few minutes when they commuted to their offices. That is why our research work aims to provide a self-training tool that measures the efficiency of performing certain calisthenics routines, with respect to expert videos, and to provide feedback, based on data, to improve the performance of these routines. Also, predict the calorie burn with respect to the history of exercises performed. All this through a web application that uses Machine Learning techniques.
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