Aquatic Virtual Reality: From Feasibility to Application
Aquatic virtual reality (VR) is a minimally researched area. VR replaces what a user interacts with and sees with virtual objects and aquatic VR does the same while the user is in an aquatic environment (e.g., a pool) physically. As VR technology is becoming more mobile (e.g., wireless), aquatic VR is becoming more feasible and less expensive. However, with such little research in the area, it is not known how similar aquatic VR is to non-aquatic VR. Furthermore, there have been no studies on how persons with disabilities interact with aquatic VR. To address this gap, I first looked at how effective consumer tracking systems work underwater as compared to above water. The results from that study revealed that the inertial measurement units (IMU) in phones and the magnetic tracking system employed by the Razer Hydra are both minimally affected by being underwater. Further, the difference between the Hydra and IMUs were minimal. In my second study, I compared common object manipulation techniques underwater to above water. The results indicated that the manipulation techniques are similar underwater and above water, with the added benefit of users reporting less fatigue underwater than above. My third study built upon the results of my first and second studies, resulting in a full VR application for use by children with disabilities undergoing aquatic therapy. I conducted a pilot study with 13 children and found high levels of engagement. The high engagement suggests that children undergoing aquatic therapy with VR might be more motivated to continue with their treatment. However, there were technical issues with the jumping interaction method. The IMU used for jump detection did not register several actual jumps. For my final study, I compared four different tracking devices (i.e., Optitrack as baseline, Razer Hydra, Vuforia, and a phone IMU) right above the surface of the water to determine the most effective jump detection method. Results indicate that a phone IMU has several limitations that result in poor accuracy. The Hydra had the least error in position, rotation, and jump detection while Vuforia had slightly worse accuracy in slow movement and greatly less accuracy during fast movement. The Hydra, Optitrack, and Vuforia all had high jump detection accuracy, regardless of position and rotation accuracy.