Evidence map›Paper›PMID 40804054›Full record

ArticleScientific data2025

A dataset of high-resolution plantar pressures for gait analysis across varying footwear and walking speeds.

Robyn Larracy, Angkoon Phinyomark, Ala Salehi, Eve MacDonald, Saeed Kazemi, Shikder Shafiul Bashar, Aaron Tabor, Erik Scheme

Abstract readDataset
PubMed Full text at PMC Publisher
In one paragraph

Article in Scientific data, 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

8 authors.

Robyn LarracyUniversity of New Brunswick, Institute of Biomedical Engineering, Fredericton, E3B 5A3, Canada.ORCID 0000-0003-3885-1022
Angkoon PhinyomarkUniversity of New Brunswick, Institute of Biomedical Engineering, Fredericton, E3B 5A3, Canada.
Ala SalehiUniversity of New Brunswick, Institute of Biomedical Engineering, Fredericton, E3B 5A3, Canada.
Eve MacDonaldUniversity of New Brunswick, Institute of Biomedical Engineering, Fredericton, E3B 5A3, Canada.
Saeed KazemiUniversity of New Brunswick, Institute of Biomedical Engineering, Fredericton, E3B 5A3, Canada.
Shikder Shafiul BasharUniversity of New Brunswick, Institute of Biomedical Engineering, Fredericton, E3B 5A3, Canada.
Aaron TaborUniversity of New Brunswick, Institute of Biomedical Engineering, Fredericton, E3B 5A3, Canada.
Erik SchemeUniversity of New Brunswick, Institute of Biomedical Engineering, Fredericton, E3B 5A3, Canada. escheme@unb.ca.ORCID 0000-0002-4421-1016

Funding

Gouvernement du Canada | Natural Sciences and Engineering Research Council of Canada (Conseil de Recherches en Sciences Naturelles et en Génie du Canada) ALLRP 558340-20
6 · The paper itself

Abstract

Gait refers to the patterns of limb movement generated during walking, which are unique to each individual due to both physical and behavioural traits. Walking patterns have been widely studied in biometrics, biomechanics, sports, and rehabilitation. While traditional methods rely on video and motion capture, advances in plantar pressure sensing technology now offer deeper insights into gait. However, underfoot pressures during walking remain underexplored due to the lack of large, publicly accessible datasets. To address this, we introduce the UNB StepUP-P150 dataset: a footStep database for gait analysis and recognition using Underfoot Pressure, including data from 150 individuals. This dataset comprises high-resolution plantar pressure data (4 sensors/cm

Indexed as

FootGaitGait AnalysisShoesWalkingWalking SpeedBiomechanical PhenomenaHumansPressure

Identifiers

PMID40804054
PMCPMC12350911

What OpenQuestion holds

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Registered trials

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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.