4.6 Article

A simulator for both manual and powered wheelchairs in immersive virtual reality CAVE

Journal

VIRTUAL REALITY
Volume 26, Issue 1, Pages 187-203

Publisher

SPRINGER LONDON LTD
DOI: 10.1007/s10055-021-00547-w

Keywords

Manual wheelchair; Powered wheelchair; Simulating system; Immersive virtual reality

Funding

  1. National Institute for Insurance against Accidents at Work (INAIL), part of the Rientr@ project [PDT2/1]
  2. Italian Ministry of Health

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This study describes and technically validates simulation models for manual and powered wheelchairs based on immersive virtual reality CAVE. Results demonstrated that the virtual simulation of wheelchair motion was consistent with real wheelchair motion, making it a reliable tool for training and validation.
A large number of people in the world need to use a wheelchair because of different disabilities. Driving a wheelchair requires complex physical and cognitive abilities which need to be trained. Virtual training helps users acquire driving skills in a safe environment. The aim of this paper is to describe and technically validate simulation models for both manual (MW) and powered wheelchairs (PW) based on immersive virtual reality CAVE (VR). As VR system, the Gait Real-time Analysis Interactive Lab (GRAIL) was used, a CAVE equipped with a motion platform with two degrees of freedom and an optoelectronic motion capture system. A real wheelchair was positioned onto the motion platform with rear wheels free to turn in MW modality, and a commercial joystick was installed on an armrest to simulate the PW modality. Passive markers were used to track the wheel rotation, the joystick and the user hand motion. Custom D-flow applications were developed to manage virtual scene response to user actions. Overground tests, based on single wheel rotation, were performed to verify the simulation model reliability. Quantitative results demonstrated that the MW simulator kinematics was consistent with a real wheelchair overground in the absence of wheel slip and inertia (median error for MW 0.40 degrees, no systematic bias p = 0.943, high correlation rho > 0.999, p < 0.01). The proposed solution is flexible and adaptable to different wheelchairs, joysticks and optoelectronic systems. The main limitation is the absence of force feedback. Nevertheless, it is a reliable prototype that can be used to validate new virtual scenarios as well as for wheelchair training. The next steps include the system validation with real end users and assessment of the simulator effectiveness as a training tool.

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