Evidence map›Paper›PMID 38165851›Full record

ArticlePloS one2024

Temporal precision and accuracy of audio-visual stimuli in mixed reality systems.

Daniel Eckhoff, Jan Schnupp, Alvaro Cassinelli

Open access · goldAbstract read
In one paragraph

Article in PloS one, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.

0numbers the graph read from it
0cells of the map it votes in
3citing papers in PubMed
3.6field-weighted citation impact, top 8% of its field
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

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

3 citing papers in PubMed, 7 citations in OpenAlex.

  1. Review
  2. Article
  3. Review
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

3 authors at 1 institution in 1 country.

Daniel EckhoffSchool of Creative Media, City University of Hong Kong, Kowloon Tong, Hong Kong.ORCID 0000-0002-7486-5651
Jan SchnuppDepartment of Neuroscience, City University of Hong Kong, Kowloon Tong, Hong Kong.
Alvaro CassinelliSchool of Creative Media, City University of Hong Kong, Kowloon Tong, Hong Kong.
City University of Hong Kong · HK

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Mixed Reality (MR) techniques, such as Virtual (VR) and Augmented Reality (AR), are gaining popularity as a new methodology for neuroscience and psychology research. In studies involving audiovisual stimuli, it is crucial to have MR systems that can deliver these bimodal stimuli with controlled timing between the onset of each modality. However, the extent to which modern MR setups can achieve the necessary precision and accuracy of audiovisual stimulus onset asynchronies (SOAs) remains largely unknown. The objective of this study is to systematically evaluate the lag and variability between the auditory and visual onset of audiovisual stimuli produced on popular modern MR head-mounted displays (HMDs) from Meta, Microsoft, HTC, and Varjo in conjunction with commonly used development environments such as Unity and the Unreal Engine. To accomplish this, we developed a low-cost measurement system that enabled us to measure the actual SOA and its associated jitter. Our findings revealed that certain MR systems exhibited significant SOAs, with one case averaging 156.63 ms, along with jitter of up to ±11.82 ms. Using our methodology, we successfully conducted experimental calibration of a headset, achieving SOAs of -3.89 ± 1.56 ms. This paper aims to raise awareness among neuroscience researchers regarding the limitations of MR systems in delivering audiovisual stimuli without prior calibration. Furthermore, we present cost-effective methods to calibrate these systems, thereby facilitating the replication of future results.

Indexed as

Augmented RealityNeurosciencesPhotic StimulationTime FactorsVisual Perception

Identifiers

PMID38165851
PMCPMC10760685
OpenAlexW4390511595

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

None linked

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.