PT  - JOURNAL ARTICLE
AU  - Diar Abdlkarim
AU  - Massimiliano Di Luca
AU  - Poppy Aves
AU  - Sang-Hoon Yeo
AU  - R. Chris Miall
AU  - Peter Holland
AU  - Joseph M. Galea
TI  - A Methodological Framework to Assess the Accuracy of Virtual Reality Hand-Tracking Systems: A case study with the Oculus Quest 2
AID  - 10.1101/2022.02.18.481001
DP  - 2022 Jan 01
TA  - bioRxiv
PG  - 2022.02.18.481001
4099  - http://biorxiv.org/content/early/2022/02/20/2022.02.18.481001.short
4100  - http://biorxiv.org/content/early/2022/02/20/2022.02.18.481001.full
AB  - Optical marker-less hand-tracking systems incorporated into virtual reality (VR) headsets are transforming the ability to assess motor skills, including hand movements, in VR. This promises to have far-reaching implications for the increased applicability of VR across scientific, industrial and clinical settings. However, so far, there is little data regarding the accuracy, delay and overall performance of these types of hand-tracking systems. Here we present a novel methodological framework which can be easily applied to measure these systems’ absolute positional error, temporal delay and finger joint-angle accuracy. We used this framework to evaluate the Meta Quest 2 hand-tracking system. Our results showed an average fingertip positional error of 1.1cm, an average finger joint angle error of 9.6o and an average temporal delay of 38.0ms. Finally, a novel approach was developed to correct for these positional errors based on a lens distortion model. This methodological framework provides a powerful tool to ensure the reliability and validity of data originating from VR-based, marker-less hand-tracking systems.Competing Interest StatementThe authors have declared no competing interest.