Quantification of acceleration as activity counts in ActiGraph wearable.


Journal

Scientific reports
ISSN: 2045-2322
Titre abrégé: Sci Rep
Pays: England
ID NLM: 101563288

Informations de publication

Date de publication:
13 07 2022
Historique:
received: 08 03 2022
accepted: 04 07 2022
entrez: 13 7 2022
pubmed: 14 7 2022
medline: 16 7 2022
Statut: epublish

Résumé

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.

Identifiants

pubmed: 35831446
doi: 10.1038/s41598-022-16003-x
pii: 10.1038/s41598-022-16003-x
pmc: PMC9279376
doi:

Types de publication

Journal Article Research Support, N.I.H., Extramural Research Support, Non-U.S. Gov't

Langues

eng

Sous-ensembles de citation

IM

Pagination

11958

Subventions

Organisme : NIMH NIH HHS
ID : 5U01MH116928
Pays : United States

Informations de copyright

© 2022. The Author(s).

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Auteurs

Ali Neishabouri (A)

ActiGraph LLC, 49 East Chase St., Pensacola, FL, 32502, US. ali.neishabouri@theactigraph.com.

Joe Nguyen (J)

ActiGraph LLC, 49 East Chase St., Pensacola, FL, 32502, US.

John Samuelsson (J)

ActiGraph LLC, 49 East Chase St., Pensacola, FL, 32502, US.
Athinoula A. Martinos Center for Biomedical Imaging, MGH/MIT/Harvard, 149, 13th St., Boston, MA, 02129, USA.

Tyler Guthrie (T)

ActiGraph LLC, 49 East Chase St., Pensacola, FL, 32502, US.

Matt Biggs (M)

ActiGraph LLC, 49 East Chase St., Pensacola, FL, 32502, US.

Jeremy Wyatt (J)

ActiGraph LLC, 49 East Chase St., Pensacola, FL, 32502, US.

Doug Cross (D)

ActiGraph LLC, 49 East Chase St., Pensacola, FL, 32502, US.

Marta Karas (M)

Department of Biostatistics, Harvard T.H. Chan School of Public Health, Harvard University, 677 Huntington Avenue, Boston, MA02115, US.

Jairo H Migueles (JH)

Department of Biosciences and Nutrition, Karolinska Institute, Huddinge, Sweden.
Department of Physical Education and Sports, Faculty of Sport Sciences, PROFITH "PROmoting FITness and Health through physical activity" Research Group, Sport and Health University Research Institute (iMUDS), University of Granada, Granada, Spain.

Sheraz Khan (S)

ActiGraph LLC, 49 East Chase St., Pensacola, FL, 32502, US.
Athinoula A. Martinos Center for Biomedical Imaging, MGH/MIT/Harvard, 149, 13th St., Boston, MA, 02129, USA.

Christine C Guo (CC)

ActiGraph LLC, 49 East Chase St., Pensacola, FL, 32502, US.

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Classifications MeSH