Leveraging Accelerometry and Heart Rate Data from Consumer Wearables to Predict Physical Activity in Children: A Device Agnostic Approach
Except for Fitbit, accelerometry and HR data from consumer wearables predicted PAEE comparably to research-grade devices, and there was little variability across modeling approach. These outcomes support deploying a consumer wearable device-agnostic approach for PAEE estimation in children.
Authors
- R. Glenn Weaver (ORCID: https://orcid.org/0000-0001-5889-974X)
- Gregory J. Welk (ORCID: https://orcid.org/0000-0001-7132-9725)
- James White (ORCID: https://orcid.org/0000-0001-8371-8453)
- Elizabeth L. Adams (ORCID: https://orcid.org/0000-0002-5602-8470)
- Bridget Armstrong (ORCID: https://orcid.org/0000-0002-1909-8170)
- Olivia Finnegan (ORCID: https://orcid.org/0000-0003-0625-1479)
- Michael W. Beets (ORCID: https://orcid.org/0000-0001-6728-6742)
- Sarah Burkart (ORCID: https://orcid.org/0000-0002-0840-1680)
- Massimiliano de Zambotti (ORCID: https://orcid.org/0000-0002-0057-5977)
- Srihari Nelakuditi (ORCID: https://orcid.org/0000-0001-5990-394X)
- Rahul Ghosal (ORCID: https://orcid.org/0000-0003-0939-4731)
- Yuan Wang (ORCID: https://orcid.org/0000-0001-5871-9497)
- R. R. Pate
- Trey Brown
Institutions
- University of South Carolina (US)
- Iowa State University (US)
- Oklahoma State University Center for Health Sciences (US)
Publication Details
- Journal
- Medicine & Science in Sports & Exercise
- Published
- 2025-04-04
- DOI
- https://doi.org/10.1249/mss.0000000000003721
- Citations
- 1
- Primary Topic
- Physical Activity and Health
- Type
- article
- Field-Weighted Citation Impact
- 1.16