Validation of the Fitbit Charge 2 compared to the ActiGraph GT3X+ in older adults with knee osteoarthritis in free-living conditions
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OBJECTIVE: To evaluate physical activity (PA) and sedentary time in subjects with knee osteoarthritis (OA) measured by the Fitbit Charge 2 (Fitbit) and a wrist-worn ActiGraph GT3X+ (AGW) compared to the hip-worn ActiGraph (AGH). DESIGN: We recruited a cohort of subjects with knee OA from rheumatology clinics. Subjects wore the AGH for four weeks, AGW for two weeks, and Fitbit for two weeks over a four-week study period. We collected accelerometer counts (ActiGraphs) and steps (ActiGraphs, Fitbit) and calculated time spent in sedentary, light, and moderate-to-vigorous activity. We used triaxial PA intensity count cut-points from the literature for ActiGraph and a stride length-based cadence algorithm to categorize Fitbit PA. We compared Fitbit wear times calculated from a step-based algorithm and a novel algorithm that incorporates steps and heart rate (HR). RESULTS: We enrolled 15 subjects (67% female, mean age 68 years). Relative to AGH, Fitbit, on average, overestimated steps by 39% and sedentary time by 37% and underestimated MVPA by 5 minutes. Relative to AGH, AGW overestimated steps 116%, underestimated sedentary time by 66%, and captured 281 additional MVPA minutes. The step-based wear time Fitbit algorithm captured 14% less wear time than the HR-based algorithm. CONCLUSIONS: Fitbit overestimates steps and underestimates MVPA in knee OA subjects. Cut-offs validated for AGW should be developed to support the use of AGW for PA assessment. The HR-based Fitbit algorithm captured more wear time than the step-based algorithm. These data provide critical insight for researchers planning to use commercially-available accelerometers in pragmatic studies.
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Previous studies have used heart rate as a proxy for wear time, such that time intervals with no acquired heart rate data were regarded as nonwear periods.
“Previous studies have used HR as a proxy for wear time22 such that time intervals with no acquired HR data were regarded as nonwear periods.44”
From Association of Demographic and Socioeconomic Indicators With the Use of Wearable Devices Among Children (2023) · cites this paper as [44]
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Amount of Time Spent in Sedentary Behaviors in the United States, 2003-2004
Matthews, C. E., Chen, K. Y., Freedson, P. S., Buchowski, M. S., Beech, B. M., Pate, R. R., & Troiano, R. P. (2008) · American Journal of Epidemiology · doi:10.1093/aje/kwm390 · Cited by 2,631 · see citing works
Accuracy of Fitbit Devices: Systematic Review and Narrative Syntheses of Quantitative Data
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Physical activity is related to quality of life in older adults
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Fuller, D., Colwell, E., Low, J., Orychock, K., Tobin, M. A., Simango, B., Buote, R., Van Heerden, D., Luan, H., Cullen, K., et al. (2020) · JMIR mHealth and uHealth · doi:10.2196/18694 · Cited by 715 · see citing works
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- Authors
- Collins, J. E., Yang, H. Y., Trentadue, T. P., Gong, Y., & Losina, E.
- Affiliations
- Brigham and Women's Hospital (US)
- Boston University (US)
- Corresponding author
- Losina, Elena
- Venue
- PLOS ONE
- Publisher
- Public Library of Science (PLoS)
- Published
- 2019-01-30
- Volume
- 14
- Issue
- 1
- Pages
- e0211231
- ISSN
- 1932-6203 (ISSN-L)
- PMC
- PMC6353569
- OpenAlex
- W2912360256
- Cited by
- 55
- References
- 3
- Citations by year
- 2026: 4 · 2025: 8 · 2024: 2 · 2023: 12 · 2022: 6 · 2021: 10 · 2020: 11 · 2019: 2
- FWCI
- 4.97
- Type
- journal article
- Language
- en
- Open access
- gold
- doi.org
- Licence
- Locations
- PLoS ONE (publishedVersion, cc-by)
- Europe PMC (PubMed Central) (publishedVersion, cc-by)
- PubMed Central (publishedVersion, cc-by)
- PubMed (publishedVersion)
- RePEc: Research Papers in Economics (submittedVersion)
- DOAJ (DOAJ: Directory of Open Access Journals) (submittedVersion, cc-by-sa)
- Figshare (submittedVersion, cc-by)
- Funders
- National Institute of Arthritis and Musculoskeletal and Skin Diseases (U34 AR069187 01A1)
- 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
- ActiGraph GT3X+, knee osteoarthritis, older adults, physical activity measurement, sedentary time, moderate-to-vigorous physical activity, accelerometer validation, step counting, wrist-worn accelerometers, hip-worn accelerometers, free-living conditions
- MeSH terms
- Fitness Trackers, Aged, Algorithms, Female, Humans, Male, Middle Aged, Social Conditions, Exercise, Monitoring, Ambulatory, Osteoarthritis, Knee, Actigraphy, Independent Living, Accelerometry
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