Login | Register

An Online Balance Training Application Using Pose Estimation and Augmented Reality

Title:

An Online Balance Training Application Using Pose Estimation and Augmented Reality

Etaat, Amirhossein (2021) An Online Balance Training Application Using Pose Estimation and Augmented Reality. Masters thesis, Concordia University.

[thumbnail of Etaat_MASc_F2021.pdf]
Text (application/pdf)
Etaat_MASc_F2021.pdf - Accepted Version
Restricted to Registered users only until 9 January 2023.
Available under License Spectrum Terms of Access.
6MB

Abstract

The evolution of digitally connected devices and artificial intelligence has opened the door for novel health and fitness applications that can be used by individuals at a time and in an environment convenient to them. The purpose of our research was to develop a platform that requires no additional hardware to provide an online balance training program. Balance exercises are often prescribed for healthy aging to keep the body active, improve balance and coordination, and prevent falls and injuries, as well as, for those doing rehabilitation after injuries or diseases such as stroke. We developed a simple web application (BaART: Balance Augmented Reality Trainer) that uses PoseNet to determine a user's location and pose to count the number of repetitions that were done successfully. Furthermore, we looked at how augmented reality, and specifically adding a virtual chair, might impact a user's sense of balance. In a study of 20 participants with and without balance disorders, we found that the developed system was easy to use and many would consider using such a system, particularly our older participants who spend more time at home. However, we also found that the virtual object (i.e. chair) was not used by most people. Furthermore, those with balance issues felt they required a real chair for balance and some even felt that the virtual object was distracting from the exercise. In the future, we plan to explore other uses of augmented reality, such as feedback on exercise quality, gaming features, and a virtual avatar trainer.

Divisions:Concordia University > Gina Cody School of Engineering and Computer Science > Computer Science and Software Engineering
Item Type:Thesis (Masters)
Authors:Etaat, Amirhossein
Institution:Concordia University
Degree Name:M.A. Sc.
Program:Computer Science
Date:15 December 2021
Thesis Supervisor(s):Kersten-Oertel, Marta
ID Code:990142
Deposited By: Amirhossein Etaat
Deposited On:16 Jun 2022 14:37
Last Modified:16 Jun 2022 14:37
All items in Spectrum are protected by copyright, with all rights reserved. The use of items is governed by Spectrum's terms of access.

Repository Staff Only: item control page

Downloads per month over past year

Research related to the current document (at the CORE website)
- Research related to the current document (at the CORE website)
Back to top Back to top