Evidence map›Paper›PMID 39075097›Full record

ArticleScientific reports2024

A validation study demonstrating portable motion capture cameras accurately characterize gait metrics when compared to a pressure-sensitive walkway.

Kevin A Mazurek, Leland Barnard, Hugo Botha, Teresa Christianson, Jonathan Graff-Radford, Ronald Petersen, Prashanthi Vemuri, B Gwen Windham, David T Jones, Farwa Ali

Abstract readValidation Study
In one paragraph

Article in Scientific reports, 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
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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

10 authors.

Kevin A MazurekDepartment of Neurology, Mayo Clinic, Rochester, MN, USA. mazurek.kevin@mayo.edu.
Leland BarnardDepartment of Neurology, Mayo Clinic, Rochester, MN, USA.
Hugo BothaDepartment of Neurology, Mayo Clinic, Rochester, MN, USA.
Teresa ChristiansonDepartment of Quantitative Health Sciences, Mayo Clinic, Rochester, MN, USA.
Jonathan Graff-RadfordDepartment of Neurology, Mayo Clinic, Rochester, MN, USA.
Ronald PetersenDepartment of Neurology, Mayo Clinic, Rochester, MN, USA.
Prashanthi VemuriDepartment of Radiology, Mayo Clinic, Rochester, MN, USA.
B Gwen WindhamDepartment of Medicine, The MIND Center, University of Mississippi Medical Center, Jackson, MS, USA.
David T JonesDepartment of Neurology, Mayo Clinic, Rochester, MN, USA.
Farwa AliDepartment of Neurology, Mayo Clinic, Rochester, MN, USA. ali.farwa@mayo.edu.

Funding

SUPPLEMENT TO ALZHEIMERS DISEASE PATIENT REGISTRYU01AG006786 · NIA · MAYO CLINIC ROCHESTER · PI GRAFF-RADFORD, JONATHAN, JACK, CLIFFORD R. · 1986 to 2023
$49.6M
Research Education ComponentP30AG062677 · NIA · MAYO CLINIC ROCHESTER · PI Walter K. Kremers · 2019 to 2026
$33.5M
Mechanisms of Gait and Balance Impairment in Progressive Supranuclear PalsyK23NS124688 · NINDS · MAYO CLINIC ROCHESTER · PI Farwa Ali · 2022 to 2026
$947k
NIA NIH HHS P30 AG062677NIA NIH HHS U01 AG006786NINDS NIH HHS K23 NS124688U.S. Department of Health & Human Services | NIH | National Institute of Neurological Disorders and Stroke (NINDS) K23NS124688U.S. Department of Health & Human Services | NIH | National Institute on Aging (U.S. National Institute on Aging) P30AG062677U.S. Department of Health & Human Services | NIH | National Institute on Aging (U.S. National Institute on Aging) U01AG006786
6 · The paper itself

Abstract

Digital quantification of gait can be used to measure aging- and disease-related decline in mobility. Gait performance also predicts prognosis, disease progression, and response to therapies. Most gait analysis systems require large amounts of space, resources, and expertise to implement and are not widely accessible. Thus, there is a need for a portable system that accurately characterizes gait. Here, depth video from two portable cameras accurately reconstructed gait metrics comparable to those reported by a pressure-sensitive walkway. 392 research participants walked across a four-meter pressure-sensitive walkway while depth video was recorded. Gait speed, cadence, and step and stride durations and lengths strongly correlated (r > 0.9) between modalities, with root-mean-squared-errors (RMSE) of 0.04 m/s, 2.3 steps/min, 0.03 s, and 0.05-0.08 m for speed, cadence, step/stride duration, and step/stride length, respectively. Step, stance, and double support durations (gait cycle percentage) significantly correlated (r > 0.6) between modalities, with 5% RMSE for step and stance and 10% RMSE for double support. In an exploratory analysis, gait speed from both modalities significantly related to healthy, mild, moderate, or severe categorizations of Charleson Comorbidity Indices (ANOVA, Tukey's HSD, p < 0.0125). These findings demonstrate the viability of using depth video to expand access to quantitative gait assessments.

Indexed as

GaitGait AnalysisAdultAgedFemaleHumansMaleMiddle AgedMotion CapturePressureVideo RecordingWalkingWalking SpeedDepth videoGait analysisMotion capturePoint-cloudPortable cameras

Identifiers

PMID39075097
PMCPMC11286855

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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.