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Virtual physical therapist application with human pose detection

Chan, Jia Yi (2022) Virtual physical therapist application with human pose detection. Final Year Project, UTAR.

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    In general, the accessibility of tele-physical therapy faced more difficulties especially when the strikes of COVID-19 hits. In this project, the problems in the targeted users in accessing physical therapy at home will be discussed, as well as the previous existing works from other researchers are also be studied and discussed in this paper. After researches on different works, it is shocked that the applications with monitoring mechanism to prevent patients from performing wrong action and assessment mechanism for therapist to make further diagnosis are still sparse in the market. The proposed solution will attempt to solved the current problems to enhance a better performance for the existing application. As result, patients could have access to rehabilitation treatment so that they could continue to improve their health condition during Covid-19 outbreak. A mobile application is chosen as a solution to assists patients and therapists in accessing the physical therapy session at home. The aim of this project is to develop an improved assistance system for physical therapy with enhanced flexibility and functionalities that could assist both therapists and patients for remote physical therapy. Hence, functionalities such as Body Detection and Pose Estimation System, Real-time Guidance System and Assessment System will be designed and developed. It allows patients to receive real-time instructions and corrective messages during exercising, visualize performance results to patients and therapists and able to perform body pose tracking instantly. All of these functions can be carried out with a small device like smartphone. The project will be developed using Dart language with Flutter, database with Firebase, and mechine learning solutions from Google Mediapipe Framework. Waterfall methodology is used to develop this application.

    Item Type: Final Year Project / Dissertation / Thesis (Final Year Project)
    Subjects: Q Science > Q Science (General)
    T Technology > T Technology (General)
    Divisions: Faculty of Information and Communication Technology > Bachelor of Computer Science (Honours)
    Depositing User: ML Main Library
    Date Deposited: 15 Jan 2023 21:20
    Last Modified: 15 Jan 2023 21:20
    URI: http://eprints.utar.edu.my/id/eprint/4641

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