Evidence map›Paper›PMID 35831446›Full record

ArticleScientific reports2022

Quantification of acceleration as activity counts in ActiGraph wearable.

Ali Neishabouri, Joe Nguyen, John Samuelsson, Tyler Guthrie, Matt Biggs, Jeremy Wyatt, Doug Cross, Marta Karas, Jairo H Migueles, Sheraz Khan and 1 more

Abstract read
In one paragraph

Article in Scientific reports, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 90 papers, 2 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
90citing papers in PubMed, 2 pooled it
–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

90 citing papers in PubMed, 2 syntheses or guidelines pooled it.

  1. Contextualising Physical Activity Levels in Patients With Anorexia Nervosa: A Systematic Review and Meta-Analysis.European eating disorders review : the journal of the Eating Disorders Association · 2025
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30 more citing papers are in PubMed but not listed here.

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

11 authors.

Ali NeishabouriActiGraph LLC, 49 East Chase St., Pensacola, FL, 32502, US. ali.neishabouri@theactigraph.com.
Joe NguyenActiGraph LLC, 49 East Chase St., Pensacola, FL, 32502, US.
John SamuelssonActiGraph LLC, 49 East Chase St., Pensacola, FL, 32502, US.
Tyler GuthrieActiGraph LLC, 49 East Chase St., Pensacola, FL, 32502, US.
Matt BiggsActiGraph LLC, 49 East Chase St., Pensacola, FL, 32502, US.
Jeremy WyattActiGraph LLC, 49 East Chase St., Pensacola, FL, 32502, US.
Doug CrossActiGraph LLC, 49 East Chase St., Pensacola, FL, 32502, US.
Marta KarasDepartment of Biostatistics, Harvard T.H. Chan School of Public Health, Harvard University, 677 Huntington Avenue, Boston, MA02115, US.
Jairo H MiguelesDepartment of Biosciences and Nutrition, Karolinska Institute, Huddinge, Sweden.
Sheraz KhanActiGraph LLC, 49 East Chase St., Pensacola, FL, 32502, US.
Christine C GuoActiGraph LLC, 49 East Chase St., Pensacola, FL, 32502, US.

Funding

Intensive longitudinal study of suicidal behaviors and related health outcomesU01MH116928 · NIMH · HARVARD UNIVERSITY · PI NOCK, MATTHEW K · 2018 to 2022
$4.3M
NIMH NIH HHS 5U01MH116928NIMH NIH HHS U01 MH116928
6 · The paper itself

Abstract

Digital clinical measures based on data collected by wearable devices have seen rapid growth in both clinical trials and healthcare. The widely-used measures based on wearables are epoch-based physical activity counts using accelerometer data. Even though activity counts have been the backbone of thousands of clinical and epidemiological studies, there are large variations of the algorithms that compute counts and their associated parameters-many of which have often been kept proprietary by device providers. This lack of transparency has hindered comparability between studies using different devices and limited their broader clinical applicability. ActiGraph devices have been the most-used wearable accelerometer devices for over two decades. Recognizing the importance of data transparency, interpretability and interoperability to both research and clinical use, we here describe the detailed counts algorithms of five generations of ActiGraph devices going back to the first AM7164 model, and publish the current counts algorithm in ActiGraph's ActiLife and CentrePoint software as a standalone Python package for research use. We believe that this material will provide a useful resource for the research community, accelerate digital health science and facilitate clinical applications of wearable accelerometry.

Indexed as

AccelerometryWearable Electronic DevicesAccelerationExerciseSoftware

Identifiers

PMID35831446
PMCPMC9279376

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.