Abstract
An individual's quality of life can be greatly impacted by poor posture, which is frequently caused by mishaps, extended use of devices, or improper physical activity that may result in pain or injury. This is especially problematic for at-home physical therapy activities because they don't have professional supervision, which might make pre-existing conditions worse and cause new ones. Thus, the goal of this project is to create a user-friendly application that tracks and enhances users’ posture as they perform at- home physical therapy exercises by utilizing computer vision and machine learning approaches. The objective is to improve patients' medical outcomes by giving individualized and efficient care in real-time.
Recommended Citation
Ogg, Arthur Diesel; de Paiva Goberski, Jennifer Mayara; Caversan, Leonardo Feitoza; Cassenote, Mariane Sponchiado; and Patrocinio, Vinicius Dionizio, "Integração de Visão Computacional e Inteligência Artificial na Fisioterapia Domiciliar" (2024). ISLA 2024 Proceedings. 12.
https://aisel.aisnet.org/isla2024/12