Evidence map›Paper›PMID 40041039›Full record

ArticleVirtual reality2025

Obstacle avoidance of physical, stereoscopic, and pictorial objects.

Martin Giesel, Daniela Ruseva, Constanze Hesse

Abstract read
In one paragraph

Article in Virtual reality, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing 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

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

0 citing papers in PubMed.

No citing paper in PubMed yet.

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.

Martin GieselSchool of Psychology, University of Aberdeen, William Guild Building, Aberdeen, AB24 3FX UK.ORCID 0000-0002-3832-7442
Daniela RusevaSchool of Psychology, University of Aberdeen, William Guild Building, Aberdeen, AB24 3FX UK.ORCID 0009-0008-0054-7467
Constanze HesseSchool of Psychology, University of Aberdeen, William Guild Building, Aberdeen, AB24 3FX UK.ORCID 0000-0002-4395-0781

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Simulated environments, e.g., virtual or augmented reality environments, are becoming increasingly popular for the investigation and training of motor actions. Yet, so far it remains unclear if results of research and training in those environments transfer in the expected way to natural environments. Here, we investigated the types of visual cues that are required to ensure naturalistic hand movements in simulated environments. We compared obstacle avoidance of physical objects with obstacle avoidance of closely matched 2D and 3D images of the physical objects. Participants were asked to reach towards a target position without colliding with obstacles of varying height that were placed in the movement path. Using a pre-test post-test design, we tested obstacle avoidance for 2D and 3D images of obstacles both before and after exposure to the physical obstacles. Consistent with previous findings, we found that participants initially underestimated the magnitude differences between the obstacles, but after exposure to the physical obstacles avoidance performance for the 3D images became similar to performance for the physical obstacles. No such change was found for 2D images. Our findings highlight the importance of disparity cues for naturalistic motor actions in personal space. Furthermore, they suggest that the observed change in obstacle avoidance for 3D images resulted from a calibration of the disparity cues in the 3D images using an accurate estimate of the egocentric distance to the obstacles gained from the interaction with the physical obstacles.

Indexed as

Binocular disparitiesDistance perceptionHand movementsHeight perceptionPerception and actionVR

Identifiers

PMID40041039
PMCPMC11872779

What Socratic 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 Socratic graph.