Measuring motion-to-photon latency for sensorimotor experiments with virtual reality systems.


Journal

Behavior research methods
ISSN: 1554-3528
Titre abrégé: Behav Res Methods
Pays: United States
ID NLM: 101244316

Informations de publication

Date de publication:
10 2023
Historique:
accepted: 19 09 2022
medline: 1 11 2023
pubmed: 11 10 2022
entrez: 10 10 2022
Statut: ppublish

Résumé

Consumer virtual reality (VR) systems are increasingly being deployed in research to study sensorimotor behaviors, but properties of such systems require verification before being used as scientific tools. The 'motion-to-photon' latency (the lag between a user making a movement and the movement being displayed within the display) is a particularly important metric as temporal delays can degrade sensorimotor performance. Extant approaches to quantifying this measure have involved the use of bespoke software and hardware and produce a single measure of latency and ignore the effect of the motion prediction algorithms used in modern VR systems. This reduces confidence in the generalizability of the results. We developed a novel, system-independent, high-speed camera-based latency measurement technique to co-register real and virtual controller movements, allowing assessment of how latencies change through a movement. We applied this technique to measure the motion-to-photon latency of controller movements in the HTC Vive, Oculus Rift, Oculus Rift S, and Valve Index, using the Unity game engine and SteamVR. For the start of a sudden movement, all measured headsets had mean latencies between 21 and 42 ms. Once motion prediction could account for the inherent delays, the latency was functionally reduced to 2-13 ms, and our technique revealed that this reduction occurs within ~25-58 ms of movement onset. Our findings indicate that sudden accelerations (e.g., movement onset, impacts, and direction changes) will increase latencies and lower spatial accuracy. Our technique allows researchers to measure these factors and determine the impact on their experimental design before collecting sensorimotor data from VR systems.

Identifiants

pubmed: 36217006
doi: 10.3758/s13428-022-01983-5
pii: 10.3758/s13428-022-01983-5
pmc: PMC10616216
doi:

Types de publication

Journal Article Research Support, Non-U.S. Gov't

Langues

eng

Sous-ensembles de citation

IM

Pagination

3658-3678

Informations de copyright

© 2022. The Author(s).

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Auteurs

Matthew Warburton (M)

School of Psychology, University of Leeds, Leeds, UK. pscmwa@leeds.ac.uk.

Mark Mon-Williams (M)

School of Psychology, University of Leeds, Leeds, UK.
Centre for Immersive Technologies, University of Leeds, Leeds, UK.
Centre for Applied Education Research, Wolfson Centre for Applied Health Research, Bradford Teaching Hospitals NHS Foundation Trust, Bradford, West Yorkshire, UK.
National Centre for Optics, Vision and Eye Care, University of South-Eastern Norway, Hasbergs vei 36, 3616, Kongsberg, Norway.

Faisal Mushtaq (F)

School of Psychology, University of Leeds, Leeds, UK.
Centre for Immersive Technologies, University of Leeds, Leeds, UK.

J Ryan Morehead (JR)

School of Psychology, University of Leeds, Leeds, UK.
Centre for Immersive Technologies, University of Leeds, Leeds, UK.

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Classifications MeSH