Evaluating Perceptional Tasks for Medicine: A Comparative User Study Between a Virtual Reality and a Desktop Application

Abstract

Since for most consumers the Virtual Reality (VR) experience exceeds that of desktop applications, an increasing number of applications is being transferred from desktop to VR. Industrial and entertainment applications primarily expect for a richer consumer experience, while others, such as surgical applications, seek for improved precision over their desktop counterparts. One way to improve the performance of precision-based VR applications is to provide suitable visualizations. Today, these "suitable" visualizations are mostly transferred from desktop to VR without considering their spatial and temporal performance might change in VR. This may not lead to an optimal solution, which can be crucial for precision-based tasks. Misinterpretation of shape or distance in a surgical or pre-operative simulation can affect the chosen treatment and thus directly impact the outcome. Therefore, we evaluate the performance differences of multiple visualizations for 3D surfaces based on their shape and distance estimation for desktop and VR applications. We conducted a quantitative user study with 56 participants evaluating seven visualizations (Phong, Toon, Fresnel, Pseudo-Chromadepth, Heatmap, Isolines, and Arrow Glyphs). Our results show that the performance of each visualization varies depending on the task, system, and surface type, with VR generally providing improved results. While Isolines are able to improve distance estimation, Phong and Heatmaps are beneficial for shape estimation.