Evidence map›Paper›PMID 40292711›Full record

ArticleSensors (Basel, Switzerland)2025

Obstacle Circumvention Strategies During Omnidirectional Treadmill Walking in Virtual Reality.

Marco A Bühler, Anouk Lamontagne

Abstract read
In one paragraph

Article in Sensors (Basel, Switzerland), 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing 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

1 citing paper in PubMed.

  1. Article
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

2 authors.

Marco A BühlerSchool of Physical and Occupational Therapy, McGill University, Montreal, QC H3G 1Y5, Canada.ORCID 0000-0002-8041-0979
Anouk LamontagneSchool of Physical and Occupational Therapy, McGill University, Montreal, QC H3G 1Y5, Canada.ORCID 0000-0003-2033-9063

Funding

Canada Foundation for Innovation CFI-36053Natural Sciences and Engineering Research Council of Canada RGPIN-2022-03746
6 · The paper itself

Abstract

Obstacle circumvention is an important task for community ambulation that is challenging to replicate in research and clinical environments. Omnidirectional treadmills combined with virtual reality (ODT-VR) offer a promising solution, allowing users to change walking direction and speed while walking in large, simulated environments. However, the extent to which such a setup yields circumvention strategies representative of overground walking in the real world (OVG-RW) remains to be determined. This study examined obstacle circumvention strategies in ODT-VR versus OVG-RW and measured how they changed with practice. Fifteen healthy young individuals walked while avoiding an interferer, performing four consecutive blocks of trials per condition. Distance at onset trajectory deviation, minimum distance from the interferer, and walking speed were compared across conditions and blocks. In ODT-VR, larger clearances and slower walking speeds were observed. In contrast, onset distances and proportions of right-side circumvention were similar between conditions. Walking speed increased from the first to the second block exclusively. Results suggest the use of a cautious locomotor behavior while using the ODT-VR setup, with some key features of circumvention strategies being preserved. Although ODT-VR setups offer exciting prospects for research and clinical applications, consideration should be given to the generalizability of findings to the real world.

Indexed as

Exercise TestVirtual RealityWalkingAdultBiomechanical PhenomenaFemaleGaitHumansMaleWalking SpeedYoung Adultgaitobstacle avoidanceomnidirectional treadmillrehabilitationvirtual reality

Identifiers

PMID40292711
PMCPMC11945152

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.