Evidence map›Paper›PMID 39379382›Full record

ArticleScientific data2024

GaitRec-VR: 3D Gait Analysis for Walking Overground with and without a Head-Mounted-Display in Virtual Reality.

Mark Simonlehner, Bernhard Dumphart, Brian Horsak

Abstract readDataset
In one paragraph

Article in Scientific data, 2024. 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. A DICOM-based standard for quantitative physical rehabilitation.Computational and structural biotechnology journal · 2025
    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

3 authors.

Mark Simonlehner *Center for Digital Health & Social Innovation, St. Pölten University of Applied Sciences, St. Pölten, Austria. mark.simonlehner@fhstp.ac.at.ORCID 0000-0002-9195-1922
Bernhard Dumphart *Center for Digital Health & Social Innovation, St. Pölten University of Applied Sciences, St. Pölten, Austria.
Brian HorsakCenter for Digital Health & Social Innovation, St. Pölten University of Applied Sciences, St. Pölten, Austria.ORCID 0000-0002-9296-3212

Funding

Österreichische Forschungsförderungsgesellschaft (Austrian Research Promotion Agency) #866855
6 · The paper itself

Abstract

This data descriptor introduces GaitRec-VR, a 3D gait analysis dataset consisting of 20 healthy participants (9 males, 11 females, age range 21-56) walking at self-selected speeds in a real-world laboratory and the virtual reality (VR) replicas of this laboratory. Utilizing a head-mounted display and a 12-camera motion capture system alongside a synchronized force plate, the dataset encapsulates real and virtual walking experiences. A direct kinematic model and an inverse dynamic approach were employed for kinematics and computation of joint moments respectively, with an average of 23 ± 6 steps for kinematics and five clean force plate strikes per participant for kinetic analysis. GaitRec-VR facilitates a deeper understanding of human movement in virtual environments, particularly focusing on dynamic balance during walking in healthy adults, crucial for effective VR applications in clinical settings. The dataset, available in both.c3d and.csv formats, allows further exploration into VR's impact on gait, bridging the gap between physical and virtual locomotion.

Indexed as

GaitGait AnalysisVirtual RealityWalkingAdultBiomechanical PhenomenaFemaleHumansMaleMiddle AgedYoung Adult

Identifiers

PMID39379382
PMCPMC11461699

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.