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Development of Virtual Reality Walking Collision Detection Test on Head-mounted display.

Alex D Hwang1, Eli Peli1, Jae-Hyun Jung1

  • 1Schepens Eye Research Institute of Massachusetts Eye and Ear, Department of Ophthalmology, Harvard Medical School, Boston, MA, USA 02114.

Proceedings of Spie--The International Society for Optical Engineering
|March 27, 2023
PubMed
Summary

This study introduces a virtual reality (VR) system for assessing walking collision detection and avoidance. The VR test offers a safe, controlled method for evaluating mobility and potential clinical interventions.

Keywords:
Virtual realitycollisionfield of viewhead-mounted displaymixed realitymobility testwalking simulator

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Area of Science:

  • Rehabilitation Engineering
  • Human-Computer Interaction
  • Biomechanics

Background:

  • Safe mobility relies on effective collision detection and avoidance during walking.
  • Objective outcome measures are crucial for assessing clinical interventions aimed at improving mobility.
  • Traditional real-world obstacle courses present safety and control limitations.

Purpose of the Study:

  • To develop and evaluate a virtual reality (VR) system for measuring walking collision detection and avoidance.
  • To overcome the limitations of physical obstacle courses by providing a controlled and safe environment.
  • To establish a potential objective outcome measure for clinical interventions in mobility.

Main Methods:

  • Developed a VR walking collision detection test using a standalone head-mounted display (Meta Quest 2) and the Unity 3D engine.
  • Implemented scenarios within a virtual busy shopping mall environment with simulated pedestrians.
  • Focused performance measures on collision detection and avoidance behaviors, incorporating mixed reality (MR) for calibration.

Main Results:

  • The VR system successfully enabled physical walking within a virtual environment.
  • Addressed challenges including visual perception mismatches, limited field of view, and pedestrian path design.
  • Demonstrated promising potential for the VR scenarios as objective clinical outcome measures.

Conclusions:

  • The developed VR system provides a safe and controllable method for assessing walking collision detection and avoidance.
  • This technology has significant potential as a novel outcome measure in clinical settings for mobility assessment.
  • Further implementation and validation are warranted to establish its clinical utility.