Development of novel data representations for virtual reality exergames

Abstract

Being physically active is important to people of all ages for supporting health and wellbeing. Engaging in regular physical activity has been shown to foster growth and development, improve physical and cognitive functions, relieve mental stress and depression, and reduce the risks of developing chronic diseases [1, 2, 3]. However, participation in physical activity can be low, especially among older adults living with dementia (OAwD), due to lack of motivation, safety and cost concerns, physical and cognitive limitations, and poor access to appropriate exercise opportunities [4, 5].

In addition to providing sustainable motivations in promoting physical activity engagement, virtual reality (VR) exergames have the potential to collect quantified, objective, and complementary information about the exergaming sessions through the use of motion-based technologies. While several studies have shown the potential of VR exergames as complementary interventions for exercise therapy in clinical practice, there has been limited research exploring how VR exergames can be used as tools to manage and administer exercise programs using the information collected in exergaming sessions.

This research explores metrics related to the performance of a person and creates data visualizations for the information collected through Exerfarm Valley, which is a head-mounted display virtual reality (HMD-VR)exergames system developed in part through this thesis work. The data visualizations resulting from this thesis research are intended to be used by exercise professionals in evaluating the client's performance during an exercise program and manage exercise therapy. The identified metrics for representing the player's performance during exergaming sessions could be applied to other exergames, potentially providing useful information about the client's status and exergaming sessions to exercise professionals. To the author's knowledge, this research represents the first data visualisations to be created for HMD-VR exergames through multi-disciplinary collaboration using user-centered design methods.