Visual perception and user satisfaction in video see-through head-mounted displays: a mixed-methods evaluation - de Souza, Jessica; Tartz, Robert (Frontiers in Virtual Reality, 2024)
Objective:Our study addresses the challenges limiting the adoption of Extended Reality (XR) Head-Mounted Displays (HMDs), mainly focusing on device quality and cybersickness. We aim to investigate the impact of hardware and software on user experience and task performance while wearing Video See-Through (VST) HMDs. We employ a novel methodology designed to bridge the gaps identified in previous research. Methods: This study uses a convergent mixed-methods approach, combining qualitative and quantitative data in a within-subjects evaluation involving 20 participants. This comprehensive evaluation examines visual perception, visual quality, and user experience through a range of tasks. Usability, comfort, and cybersickness are assessed, with insights derived from both user performance metrics and subjective measures collected through in-depth interviews and comments. The study includes three distinct HMDs—two prototypes (PD1 and PD2) and one commercial device (CD1)—to provide a broad analysis of the technology. Findings: Our findings reveal that while participants were generally satisfied with VST mode, their preferences varied across devices. CD1 was preferred for its realistic color representation and superior reading task performance due to its high-resolution display and camera. However, visual disturbances and temporal issues differed across devices, with CD1 exhibiting fewer artifacts when stationary but showing more disturbances when participants were moving. Participants found PD1 and PD2 more comfortable for extended use and fewer cybersickness symptoms, but they highlighted color and display resolution issues. These variations underscore the importance of considering both qualitative and quantitative measures in HMD evaluations. Conclusion: This mixed-methods evaluation emphasizes the limitations of relying solely on visual perception performance measures for VST HMDs. By integrating both quantitative and qualitative insights, we offer a more detailed evaluation framework to identify design flaws and user experience issues that quantitative metrics alone might miss. This methodology contributes to the field by illustrating how a mixed-methods approach provides a broader perspective on XR technology, guiding future improvements and enhancing VST adoption in future applications.