Evidence map›Paper›PMID 39205017›Full record

ArticleSensors (Basel, Switzerland)2024

Algorithm Validation for Quantifying ActiGraph™ Physical Activity Metrics in Individuals with Chronic Low Back Pain and Healthy Controls.

Jordan F Hoydick, Marit E Johnson, Harold A Cook, Zakiy F Alfikri, John M Jakicic, Sara R Piva, April J Chambers, Kevin M Bell

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

8 authors.

Jordan F HoydickDepartment of Bioengineering, University of Pittsburgh, Pittsburgh, PA 15213, USA.
Marit E JohnsonDepartment of Orthopaedic Surgery, University of Pittsburgh, Pittsburgh, PA 15213, USA.
Harold A CookDepartment of Bioengineering, University of Pittsburgh, Pittsburgh, PA 15213, USA.
Zakiy F AlfikriDepartment of Bioengineering, University of Pittsburgh, Pittsburgh, PA 15213, USA.ORCID 0000-0003-1661-1079
John M JakicicDepartment of Internal Medicine, University of Kansas Medical Center, Kansas City, KS 66160, USA.ORCID 0000-0001-6800-9368
Sara R PivaDepartment of Physical Therapy, University of Pittsburgh, Pittsburgh, PA 15213, USA.ORCID 0000-0002-1716-3151
April J ChambersDepartment of Bioengineering, University of Pittsburgh, Pittsburgh, PA 15213, USA.
Kevin M BellDepartment of Bioengineering, University of Pittsburgh, Pittsburgh, PA 15213, USA.ORCID 0000-0003-2099-413X

Funding

Influence of inflammation-related genetic variants on PT treatment response in a population affected by CLBPU19AR076725 · NIAMS · UNIVERSITY OF PITTSBURGH AT PITTSBURGH · PI SOWA, GWENDOLYN A, VO, NAM V · 2019 to 2023
$21.7M
Biomedical Data Translator Technical Feasibility Assessment and Architecture DesignOT3TR002020 · NCATS · UNIV OF NORTH CAROLINA CHAPEL HILL · PI AHALT, STANLEY CARLTON, TROPSHA, ALEXANDER · 2016 to 2019
$3.1M
NIAMS NIH HHS U19 AR076725NIH HHS 1U19AR076725-01A1University of Pittsburgh's Clinical and Translational Science Institute (CTSI) Virginia Kaufman Pain Research Challenge 2020
6 · The paper itself

Abstract

Assessing physical activity is important in the treatment of chronic conditions, including chronic low back pain (cLBP). ActiGraph™, a widely used physical activity monitor, collects raw acceleration data, and processes these data through proprietary algorithms to produce physical activity measures. The purpose of this study was to replicate ActiGraph™ algorithms in MATLAB and test the validity of this method with both healthy controls and participants with cLBP. MATLAB code was developed to replicate ActiGraph™'s activity counts and step counts algorithms, to sum the activity counts into counts per minute (CPM), and categorize each minute into activity intensity cut points. A free-living validation was performed where 24 individuals, 12 cLBP and 12 healthy, wore an ActiGraph™ GT9X on their non-dominant hip for up to seven days. The raw acceleration data were processed in both ActiLife™ (v6), ActiGraph™'s data analysis software platform, and through MATLAB (2022a). Percent errors between methods for all 24 participants, as well as separated by cLBP and healthy, were all less than 2%. ActiGraph™ algorithms were replicated and validated for both populations, based on minimal error differences between ActiLife™ and MATLAB, allowing researchers to analyze data from any accelerometer in a manner comparable to ActiLife™.

Indexed as

AlgorithmsExerciseLow Back PainAccelerometryActigraphyAdultCase-Control StudiesChronic PainFemaleHumansMaleMiddle AgedActiGraphactigraphyalgorithmschronic low back paininertial measurement units

Identifiers

PMID39205017
PMCPMC11360344

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.