Using Affordable at Home VR to Evaluate Training Methods for Medical Devices
Event Type
Oral Presentations
TimeFriday, April 1612:30pm - 1:00pm EDT
LocationEducation and Simulation
DescriptionDue to the COVID-19 Pandemic, many research studies have had to pivot to online research. Virtual reality (VR) studies face additional obstacles, as these types of studies are difficult to complete while maintaining appropriate social distancing measures (McLaughlin et al., 2020). In this lecture, we present our methods, decision making process and final design choices that allowed our current VR study to be carried out remotely.
Our research involves measuring the effectiveness of Diminished Reality (DR) as a cognitive aid in a complex, novel medical task. DR is similar to Augmented Reality (AR) but rather than adding to the environment, it de-emphasizes visual and auditory elements of the environment (Kim et al., 2018). While AR has been used to provide relevant information during training, DR can be useful for those who need distractions minimized during training. Additionally, DR can be effectively simulated in VR environments. (Ragan et al., 2009).
In our study, participants assembled a medical ventilator during a scripted medical emergency on the International Space Station within a VR environment. DR was simulated by varying the levels of visual and auditory distractions for the 3 phases of the assembly task. The purpose of the study was to evaluate DR as a cognitive aid, its effect on secondary situational awareness (SA) and how individual differences may affect performance with the use of DR.
To conduct this research remotely, we needed a way to present the DR scenario to participants, provide SA probes at random times, and control the progression of the DR scenario in real time. We also needed to create the DR scenario from the ground up. Most importantly, we needed to deliver the entire DR experience to participants remotely.
The lecture will start by explaining DR and its potential uses for training. From there, we will discuss the process of making the DR environment, which involved green screen recordings, 3D modeling and the platform Unity 3D. We will also discuss our decision process for implementing the Situational Awareness Global Assessment Technique (SAGAT) remotely, without the use of a simulator for secondary situational awareness. (Endsley, 1995)
We will also explain the process of mailing Google cardboards or similarly priced VR headsets to participants to deliver the DR experience. Zoom Video Conferencing was used to see participants in real time, and we will discuss the creation of a Wizard of Oz interface to control the progression of the assembly task due to limited interaction options with smartphone based VR environments. We will highlight design decisions that were later changed, to provide the audience with a clear picture of our iterative process and show what may or may not work for those who want to conduct similar studies remotely. Finally, we will discuss how our methods can be generalized to evaluate other types of assembly tasks or training methods. We will also briefly talk about future applications such as using this method to enhance long term retention, near transfer, far transfer or using a more interactive simulation to allow for more complex tasks and to allow participants to complete the task without researcher control via a Wizard of Oz interface.

Endsley, M. R. (1995). Measurement of Situation Awareness in Dynamic Systems. Human Factors, 37(1), 65–84.

Kim, C., Lee, J., Lee, K., & Park, J. (2018). There is only you: Actively diminishing
people in a scene. 2018 International Conference on Electronics, Information,
and Communication (ICEIC), 1–4.

McLaughlin, A. C., DeLucia, P. R., Drews, F. A., Vaughn-Cooke, M., Kumar, A., Nesbitt, R. R., & Cluff, K. (2020). Evaluating Medical Devices Remotely: Current Methods and Potential Innovations. Human Factors, 62(7), 1041–1060.

Ragan, E., Wilkes, C., Bowman, D. A., & Hollerer, T. (2009). Simulation of Augmented
Reality Systems in Purely Virtual Environments. 2009 IEEE Virtual Reality Conference, 287–288.