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A standardised and cost-effective VR approach for powered wheelchair training

Zorzi, Chantal, Tabbaa, Luma, Covaci, Alexandra, Sirlantzis, Konstantinos, Marcelli, Gianluca (2023) A standardised and cost-effective VR approach for powered wheelchair training. IEEE Access, . E-ISSN 2169-3536. (doi:10.1109/ACCESS.2023.3288424) (KAR id:101921)

Abstract

Mastering wheelchair driving skills is essential for the safety of wheelchair users (WUs), yet the acquisition of these skills can be challenging, and training resources can be costly or not available. Technologies such as virtual reality (VR) have grown in popularity as they can provide a motivating training environment without the risks found in real-life training. However, these approaches often deploy navigation controllers which are different from the ones WUs utilise, and do not use a standardised approach in assessing the acquisition of skills. We propose a VR training system based on the wheelchair skills training program (WSTP) and utilizing a sensor device that can be retrofitted to any joystick and communicates wirelessly with a Head-Mounted Display. In this paper, we present a first-validation study with fourteen able-bodied participants, split between a VR test group and a non-VR control group. To determine the acquisition of skills, participants complete tasks in real-life before and after the VR training, where completion time and length of joystick movements are measured. We also assess our system using heart rate measurements, the WSTP questionnaire, the simulator sickness questionnaire and the igroup presence questionnaire. We found that the VR training facilitates the acquisition of skills for more challenging tasks; thus, our system has the potential of being used for training skills of powered wheelchair users, with the benefit of conducting the training in safely and in a low-cost setup.

Item Type: Article
DOI/Identification number: 10.1109/ACCESS.2023.3288424
Additional information: For the purpose of open access, the author has applied a CC BY public copyright licence to any Author Accepted Manuscript version arising from this submission.
Uncontrolled keywords: assistive technologies for persons with disabilities; emerging technologies; sensors; virtual reality
Subjects: T Technology > TJ Mechanical engineering and machinery
Divisions: Divisions > Division of Computing, Engineering and Mathematical Sciences > School of Engineering and Digital Arts
Funders: Engineering and Physical Sciences Research Council (https://ror.org/0439y7842)
SWORD Depositor: JISC Publications Router
Depositing User: JISC Publications Router
Date Deposited: 03 Jul 2023 14:45 UTC
Last Modified: 04 Jul 2023 15:00 UTC
Resource URI: https://kar.kent.ac.uk/id/eprint/101921 (The current URI for this page, for reference purposes)

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