Abdlkarim, Diar

Aves, Poppy

Di Luca, Massimiliano

Galea, Joeseph M.

Holland, Peter

Maaroufi, Mohamed

Miall, R. Chris

Yeo, Sang Hoon

English

Optical markerless hand-tracking systems incorporated into virtual reality (VR) headsets are transforming the ability to assess fine motor skills 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 are little data regarding the accuracy, delay, and overall performance of these types of hand-tracking systems. Here we present a novel methodological framework based on a fixed grid of targets, which can be easily applied to measure these systems’ absolute positional error and delay. We also demonstrate a method to assess 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 9.6∘ and an average temporal delay of 45.0 ms. This methodological framework provides a powerful tool to ensure the reliability and validity of data originating from VR-based, markerless hand-tracking systems.</p

University of Birmingham Research Portal

A methodological framework to assess the accuracy of virtual reality hand-tracking systems:A case study with the Meta Quest 2

http://pure-oai.bham.ac.uk/ws/files/186972704/s13428_022_02051_8.pdf

A methodological framework to assess the accuracy of virtual reality hand-tracking systems:A case study with the Meta Quest 2

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University of Birmingham Research Portal

University of Birmingham Research Portal