Validity Evaluation of the Fitbit Charge2 and the Garmin vivosmart HR+ in Free-Living Environments in an Older Adult Cohort
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Abstract
BACKGROUND: Few studies have investigated the validity of mainstream wrist-based activity trackers in healthy older adults in real life, as opposed to laboratory settings. OBJECTIVE: This study explored the performance of two wrist-worn trackers (Fitbit Charge 2 and Garmin vivosmart HR+) in estimating steps, energy expenditure, moderate-to-vigorous physical activity (MVPA) levels, and sleep parameters (total sleep time [TST] and wake after sleep onset [WASO]) against gold-standard technologies in a cohort of healthy older adults in a free-living environment. METHODS: Overall, 20 participants (>65 years) took part in the study. The devices were worn by the participants for 24 hours, and the results were compared against validated technology (ActiGraph and New-Lifestyles NL-2000i). Mean error, mean percentage error (MPE), mean absolute percentage error (MAPE), intraclass correlation (ICC), and Bland-Altman plots were computed for all the parameters considered. RESULTS: For step counting, all trackers were highly correlated with one another (ICCs>0.89). Although the Fitbit tended to overcount steps (MPE=12.36%), the Garmin and ActiGraph undercounted (MPE 9.36% and 11.53%, respectively). The Garmin had poor ICC values when energy expenditure was compared against the criterion. The Fitbit had moderate-to-good ICCs in comparison to the other activity trackers, and showed the best results (MAPE=12.25%), although it underestimated calories burned. For MVPA levels estimation, the wristband trackers were highly correlated (ICC=0.96); however, they were moderately correlated against the criterion and they overestimated MVPA activity minutes. For the sleep parameters, the ICCs were poor for all cases, except when comparing the Fitbit with the criterion, which showed moderate agreement. The TST was slightly overestimated with the Fitbit, although it provided good results with an average MAPE equal to 10.13%. Conversely, WASO estimation was poorer and was overestimated by the Fitbit but underestimated by the Garmin. Again, the Fitbit was the most accurate, with an average MAPE of 49.7%. CONCLUSIONS: The tested well-known devices could be adopted to estimate steps, energy expenditure, and sleep duration with an acceptable level of accuracy in the population of interest, although clinicians should be cautious in considering other parameters for clinical and research purposes.
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In systematic reviews, Fitbits outperform other commercially available devices when correlated with research-grade devices.
“however, in systematic reviews, Fitbits outperform other commercially available devices when correlated with research-grade devices25,26.”
From Association of step counts over time with the risk of chronic disease in the All of Us Research Program (2022) · cites this paper as [26]
The Results and Discussion (page not available in our copy) report that the Fitbit performed better than the Garmin for some measures against reference devices, including energy expenditure and sleep. But this paper is a study of two consumer devices in older adults, not a systematic review, and it does not establish that Fitbits outperform commercially available devices generally; the Discussion reports no significant Fitbit–Garmin difference for step counting. (LLM, conf=0.88)
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References 45 · Cited by 139
- Authors
- Tedesco, S., Sica, M., Ancillao, A., Timmons, S., Barton, J., & O'Flynn, B.
- Affiliations
- University College Cork (IE)
- Corresponding author
- Tedesco, Salvatore
- Venue
- JMIR mHealth and uHealth
- Publisher
- JMIR Publications Inc.
- Published
- 2019-06-19
- Volume
- 7
- Issue
- 6
- Pages
- e13084
- ISSN
- 2291-5222 (ISSN-L)
- PMC
- PMC6607774
- OpenAlex
- W2911364828
- Cited by
- 139
- References
- 45
- Citations by year
- 2026: 15 · 2025: 16 · 2024: 17 · 2023: 24 · 2022: 22 · 2021: 29 · 2020: 15 · 2019: 1
- FWCI
- 11.49
- 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)
- Arrow@dit (Dublin Institute of Technology) (submittedVersion, cc-by)
- Cork Open Research Archive (University College Cork, Ireland) (submittedVersion, cc-by)
- DOAJ (DOAJ: Directory of Open Access Journals) (submittedVersion, cc-by-sa)
- Funders
- Science Foundation Ireland (13/RC/2077)
- Horizon 2020 Framework Programme (689996)
- European Regional Development Fund (H2020, 13/RC/2077)
- Interreg
- 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
- older adults, step counting, energy expenditure, moderate-to-vigorous physical activity, sleep duration, wake after sleep onset, device validity, free-living conditions, wearable activity trackers
- MeSH terms
- Fitness Trackers, Aged, Aged, 80 and over, Female, Humans, Ireland, Male, Reproducibility of Results, Cohort Studies, Exercise, Polysomnography, Accelerometry
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