Abstract
Detecting and avoiding collisions during walking is critical for safe mobility. To determine the effectiveness of clinical interventions, a realistic objective outcome measure is needed. A real-world obstacle course with moving hazards has numerous limitations (e.g., safety concerns of physical collision, inability to control events, maintaining event consistency, and event randomization). Virtual reality (VR) platforms may overcome such limitations. We developed a VR walking collision detection test using a standalone head-mounted display (HMD, Meta Quest 2) with the Unity 3D engine to enable subjects' physical walking within a VR environment (i.e., a busy shopping mall). The performance measures focus on the detection and avoidance of potential collisions, where a pedestrian may (or may not) walks toward a collision with the subject, while various non-colliding pedestrians are presented simultaneously. The physical space required for the system was minimized. During the development, we addressed expected and unexpected hurdles, such as mismatch of visual perception of VR space, limited field of view (FOV) afforded by the HMD, design of pedestrian paths, design of the subject task, handling of subject's response (detection or avoidance behavior), use of mixed reality (MR) for walking path calibration. We report the initial implementation of the HMD VR walking collision detection and avoidance scenarios that showed promising potential as clinical outcome measures.