ITM Web Conf.
Volume 44, 2022International Conference on Automation, Computing and Communication 2022 (ICACC-2022)
|Number of page(s)||6|
|Published online||05 May 2022|
Body Posture Detection and Motion Tracking using AI for Medical Exercises and Recommendation System
Department of Computer Engineering, Ramrao Adik Institute of Technology, D Y Patil Deemed to be University, Navi Mumbai
a Electronic Mail: firstname.lastname@example.org
b Electronic Mail: email@example.com
c Electronic Mail: firstname.lastname@example.org
d Electronic Mail: email@example.com
e Electronic Mail: firstname.lastname@example.org
Exercises are highly essential in our everyday lives, especially when patients are in the middle of a healing process and need to speed up their body's recuperation. Exercise has become more important in our lives as a result of this. They provide the cornerstone for improving human capacities and extending their lives. Artificial Intelligence and Image Processing can be utilized to improve and supplement the workout process without the need for professional supervision. A software-based motion tracker can keep track of all the exercises you've done and provide you feedback on your posture while you're working out. Through computing data and analysis, the exercise's beneficial efficiency will be increased. The MediaPipe framework could be utilized for this application; in this machine learning model, points are plotted at several joints of the human body posture, and movement is tracked, stored, and analyzed. This detailed analysis of the body tracking could be used in the implementation of an application that could keep a track of the medical exercise of a registered individual. The software could be further improvised in such a manner that the registered user could be mapped to an authentic verified doctor having the access to the diagnosis reports and exercise history of the mapped patient using databases.
Key words: MediaPipe / BlazePose / BlazeFace / Bicep curls
© The Authors, published by EDP Sciences, 2022
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.
Current usage metrics show cumulative count of Article Views (full-text article views including HTML views, PDF and ePub downloads, according to the available data) and Abstracts Views on Vision4Press platform.
Data correspond to usage on the plateform after 2015. The current usage metrics is available 48-96 hours after online publication and is updated daily on week days.
Initial download of the metrics may take a while.