Evidence map›Paper›PMID 39275462›Full record

ArticleSensors (Basel, Switzerland)2024

GaitKeeper: An AI-Enabled Mobile Technology to Standardize and Measure Gait Speed.

Naomi Davey, Gillian Harte, Aidan Boran, Paul Mc Elwaine, Seán P Kennelly

Abstract read
In one paragraph

Article in Sensors (Basel, Switzerland), 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing 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

2 citing papers in PubMed.

  1. Article
  2. 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

5 authors.

Naomi DaveyInstitute of Memory and Cognition, Tallaght University Hospital, D24 NR0A Dublin, Ireland.
Gillian HarteInstitute of Memory and Cognition, Tallaght University Hospital, D24 NR0A Dublin, Ireland.
Aidan BoranInsight Centre, Dublin City University, Collins Ave Ext, Whitehall, 9 Dublin, Ireland.
Paul Mc ElwaineInstitute of Memory and Cognition, Tallaght University Hospital, D24 NR0A Dublin, Ireland.
Seán P KennellyInstitute of Memory and Cognition, Tallaght University Hospital, D24 NR0A Dublin, Ireland.ORCID 0000-0002-3721-0197

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Gait speed is increasingly recognized as an important health indicator. However, gait analysis in clinical settings often encounters inconsistencies due to methodological variability and resource constraints. To address these challenges, GaitKeeper uses artificial intelligence (AI) and augmented reality (AR) to standardize gait speed assessments. In laboratory conditions, GaitKeeper demonstrates close alignment with the Vicon system and, in clinical environments, it strongly correlates with the Gaitrite system. The integration of a cloud-based processing platform and robust data security positions GaitKeeper as an accurate, cost-effective, and user-friendly tool for gait assessment in diverse clinical settings.

Indexed as

Artificial IntelligenceGaitWalking SpeedAdultAlgorithmsAugmented RealityFemaleGait AnalysisHumansMaleMobile Applicationsartificial intelligenceaugmented realityclinical assessment toolsgait analysisgait speed measurementhealthcare innovationhealth indicatorsmobile health technologymovement analysis techniques

Identifiers

PMID39275462
PMCPMC11398007

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.