Evidence map›Paper›PMID 36217006›Full record

ArticleBehavior research methods2023

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

Matthew Warburton, Mark Mon-Williams, Faisal Mushtaq, J Ryan Morehead

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Article in Behavior research methods, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 17 papers.

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0cells of the map it votes in
17citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

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3 · Its place in the literature

Who cites it

17 citing papers in PubMed.

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4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

4 authors.

Matthew WarburtonSchool of Psychology, University of Leeds, Leeds, UK. pscmwa@leeds.ac.uk.ORCID 0000-0001-5309-4424
Mark Mon-WilliamsSchool of Psychology, University of Leeds, Leeds, UK.
Faisal MushtaqSchool of Psychology, University of Leeds, Leeds, UK.
J Ryan MoreheadSchool of Psychology, University of Leeds, Leeds, UK.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

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.

Indexed as

Virtual RealityHumansMotionMovementSoftwareUser-Computer InterfaceLatencyMovementSensorimotorVirtual reality

Identifiers

PMID36217006
PMCPMC10616216

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.