Evidence map›Paper›PMID 41291507›Full record

ArticleBMC geriatrics2025

Using 3D skeleton tracking for gait analysis in older adults compared to a kinect-based mobility analysis system.

Kathrin Raeder, Nicole Strutz, Simone Kuntz, Sandra Strube-Lahmann, René Schwesig, Ursula Müller-Werdan, Nils Axel Lahmann

Abstract readComparative Study
In one paragraph

Article in BMC geriatrics, 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
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0citing papers in PubMed
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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

7 authors.

Kathrin Raeder *Geriatrics Research Group, Charité - Universitätsmedizin Berlin (corporate member of Freie Universität Berlin and Humboldt-Universität zu Berlin), Berlin, Germany.
Nicole Strutz *Geriatrics Research Group, Charité - Universitätsmedizin Berlin (corporate member of Freie Universität Berlin and Humboldt-Universität zu Berlin), Berlin, Germany. nicole.strutz@hm.edu.
Simone KuntzGeriatrics Research Group, Charité - Universitätsmedizin Berlin (corporate member of Freie Universität Berlin and Humboldt-Universität zu Berlin), Berlin, Germany.
Sandra Strube-LahmannGeriatrics Research Group, Charité - Universitätsmedizin Berlin (corporate member of Freie Universität Berlin and Humboldt-Universität zu Berlin), Berlin, Germany.
René SchwesigDepartment of Orthopedic and Trauma Surgery, Martin Luther University Halle- Wittenberg, Halle, Germany.
Ursula Müller-WerdanGeriatrics Research Group, Charité - Universitätsmedizin Berlin (corporate member of Freie Universität Berlin and Humboldt-Universität zu Berlin), Berlin, Germany.
Nils Axel LahmannGeriatrics Research Group, Charité - Universitätsmedizin Berlin (corporate member of Freie Universität Berlin and Humboldt-Universität zu Berlin), Berlin, Germany.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundOlder persons are affected by falls and their associated consequences. This cohort is often unaware of their own risk of falling or misjudge it. Mobility and fall risk apps are therefore useful tools for recognizing fall risks and creating opportunities to reduce them. The aim of the study was to compare the agreement of a mobility analysis smartphone camera-based application (SCA) with an included advanced 3D skeleton tracking with the reference system Microsoft Kinect System

methodsIn a cross-sectional design, 186 data sets from 31 older adults were assessed at the same time with both systems depending on two gait modes (comfort and fast).

resultsFor the comfort mode, the ICC values ranged from 0.74 (gait speed; 95% CI: 0, 0.93) to 0.85 (cadence; 95% CI: 0.62, 0.93). The fast mode showed a slightly lower agreement between both systems. ICC values moved from 0.66 (gait speed; 95% CI: 0, 0.90) to 0.81 (cadence; 95% CI: 0.46, 0.91).

conclusionWith the exception of gait speed, both systems demonstrated good agreement (ICC > 0.75) in measuring spatiotemporal gait parameters. These findings suggest that the SCA has the potential to serve as a reliable and practical instrument in the context of clinical gait analysis.

Indexed as

Accidental FallsGaitGait AnalysisImaging, Three-DimensionalAgedAged, 80 and overCross-Sectional StudiesFemaleHumansMaleSmartphoneWalking SpeedAppGait parameterMovementNew algorithmOlder adultsSmartphone

Identifiers

PMID41291507
PMCPMC12687496

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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.