Low-cost consumer-based trackers to measure physical activity and sleep duration among adults in free-living conditions: validation study
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Abstract
BACKGROUND: Wearable trackers for monitoring physical activity (PA) and total sleep time (TST) are increasingly popular. These devices are used not only by consumers to monitor their behavior but also by researchers to track the behavior of large samples and by health professionals to implement interventions aimed at health promotion and to remotely monitor patients. However, high costs and accuracy concerns may be barriers to widespread adoption. OBJECTIVE: This study aimed to investigate the concurrent validity of 6 low-cost activity trackers for measuring steps, moderate-to-vigorous physical activity (MVPA), and TST: Geonaut On Coach, iWown i5 Plus, MyKronoz ZeFit4, Nokia GO, VeryFit 2.0, and Xiaomi MiBand 2. METHODS: A free-living protocol was used in which 20 adults engaged in their usual daily activities and sleep. For 3 days and 3 nights, they simultaneously wore a low-cost tracker and a high-cost tracker (Fitbit Charge HR) on the nondominant wrist. Participants wore an ActiGraph GT3X+ accelerometer on the hip at daytime and a BodyMedia SenseWear device on the nondominant upper arm at nighttime. Validity was assessed by comparing each tracker with the ActiGraph GT3X+ and BodyMedia SenseWear using mean absolute percentage error scores, correlations, and Bland-Altman plots in IBM SPSS 24.0. RESULTS: Large variations were shown between trackers. Low-cost trackers showed moderate-to-strong correlations (Spearman r=0.53-0.91) and low-to-good agreement (intraclass correlation coefficient [ICC]=0.51-0.90) for measuring steps. Weak-to-moderate correlations (Spearman r=0.24-0.56) and low agreement (ICC=0.18-0.56) were shown for measuring MVPA. For measuring TST, the low-cost trackers showed weak-to-strong correlations (Spearman r=0.04-0.73) and low agreement (ICC=0.05-0.52). The Bland-Altman plot revealed a variation between overcounting and undercounting for measuring steps, MVPA, and TST, depending on the used low-cost tracker. None of the trackers, including Fitbit (a high-cost tracker), showed high validity to measure MVPA. CONCLUSIONS: This study was the first to examine the concurrent validity of low-cost trackers. Validity was strongest for the measurement of steps; there was evidence of validity for measurement of sleep in some trackers, and validity for measurement of MVPA time was weak throughout all devices. Validity ranged between devices, with Xiaomi having the highest validity for measurement of steps and VeryFit performing relatively strong across both sleep and steps domains. Low-cost trackers hold promise for monitoring and measurement of movement and sleep behaviors, both for consumers and researchers.
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Wearable activity trackers are affordable, visually appealing, user-friendly, and encourage lifestyle physical activity, reducing barriers associated with more structured physical activity.
“Wearable activity trackers offer an appealing, low-cost tool to address physical inactivity.”
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- Authors
- Degroote, L., Hamerlinck, G., Poels, K., Maher, C., Crombez, G., De Bourdeaudhuij, I., Vandendriessche, A., Curtis, R. G., & DeSmet, A.
- Affiliations
- Research Foundation - Flanders (BE)
- Ghent University (BE)
- University of Antwerp (BE)
- University of South Australia (AU)
- Université Libre de Bruxelles (BE)
- Corresponding author
- Degroote, Laurent
- ORCID
- Venue
- JMIR mhealth and uhealth
- Publisher
- JMIR Publications Inc.
- Published
- 2020-05-19
- Volume
- 8
- Issue
- 5
- Pages
- e16674
- ISSN
- 2291-5222 (ISSN-L)
- PMC
- PMC7268004
- OpenAlex
- W3007476422
- Cited by
- 60
- References
- 76
- Citations by year
- 2026: 7 · 2025: 8 · 2024: 6 · 2023: 11 · 2022: 14 · 2021: 10 · 2020: 4
- FWCI
- 5.85
- Type
- journal article
- Language
- en
- Open access
- gold
- doi.org
- Licence
- cc-by
- Locations
- JMIR mhealth and uhealth (publishedVersion, cc-by)
- PubMed Central (publishedVersion, cc-by)
- PubMed (publishedVersion)
- Ghent University Academic Bibliography (Ghent University) (publishedVersion)
- UniSA Research Outputs Repository (University of South Australia) (acceptedVersion, other-oa)
- Adelaide Research & Scholarship (AR&S) (University of Adelaide) (submittedVersion, cc-by)
- Ghent University Academic Bibliography (Ghent University) (submittedVersion, cc-by)
- Dépôt institutionnel de l'Université libre de Bruxelles (Université Libre de Bruxelles) (submittedVersion, other-oa)
- DOAJ (DOAJ: Directory of Open Access Journals) (submittedVersion, cc-by-sa)
- Topics
- Health Sciences › Medicine › Physiology › Physical Activity and Health
- Physical Sciences › Computer Science › Computer Vision and Pattern Recognition › Context-Aware Activity Recognition Systems
- Health Sciences › Health Professions › General Health Professions › Mobile Health and mHealth Applications
- Keywords
- wearable activity trackers, physical activity measurement, sleep duration, total sleep time, moderate-to-vigorous physical activity, step counting, concurrent validity, ActiGraph GT3X+, free-living conditions, consumer health technology, remote patient monitoring
- MeSH terms
- Adult, Humans, Sleep, Reproducibility of Results, Exercise, Monitoring, Ambulatory, Accelerometry
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