ArticleJMIR mHealth and uHealth2019
Validity Evaluation of the Fitbit Charge2 and the Garmin vivosmart HR+ in Free-Living Environments in an Older Adult Cohort.
Article in JMIR mHealth and uHealth, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 85 papers, 3 of them syntheses that pooled it.
What it found
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
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Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
85 citing papers in PubMed, 3 syntheses or guidelines pooled it.
- Quality Evaluation of Free-living Validation Studies for the Assessment of 24-Hour Physical Behavior in Adults via Wearables: Systematic Review.JMIR mHealth and uHealth · 2022Pooled it
- Accuracy and Precision of Energy Expenditure, Heart Rate, and Steps Measured by Combined-Sensing Fitbits Against Reference Measures: Systematic Review and Meta-analysis.JMIR mHealth and uHealth · 2022Pooled it
- Continuous home monitoring of Parkinson's disease using inertial sensors: A systematic review.PloS one · 2021Pooled it
- Effect of Intrapersonal and Interpersonal Behavior Change Strategies on Physical Activity Among Older Adults: A Randomized Clinical Trial.JAMA network open · 2024Trial
- Acute Effects of Coffee Consumption on Health among Ambulatory Adults.The New England journal of medicine · 2023Trial
- Evaluation of the Immediate Effects of Web-Based Intervention Modules for Goals, Planning, and Coping Planning on Physical Activity: Secondary Analysis of a Randomized Controlled Trial on Weight Loss Maintenance.Journal of medical Internet research · 2022Trial
- Validity, Reliability and Sensitivity to Change of Three Consumer-Grade Activity Trackers in Controlled and Free-Living Conditions among Older Adults.Sensors (Basel, Switzerland) · 2021Trial
- A Mobile Health Intervention to Increase Physical Activity in Pulmonary Arterial Hypertension.Chest · 2021Trial
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- A systematic review of digital and wearable sensor data in the ABCD study: Insights, methods, and emerging opportunities.Developmental cognitive neuroscience · 2026Article
- Criterion Validity of a Consumer Wearable for Step Counting and Activity Intensity Classification in Adults With Lung Cancer: Laboratory-Based Validation Study.JMIR formative research · 2026Article
- Wearable Technology and Sensors for Healthcare and Wellbeing.Sensors (Basel, Switzerland) · 2026Article
- A Testbed for the Development and Validation of Contactless Vital Signs Monitoring Systems.Sensors (Basel, Switzerland) · 2026Article
- Comparing daily step counts between a hip and wrist-worn device in adults with Parkinson's disease.Clinical parkinsonism & related disorders · 2026Article
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- Assessment of Frailty in Community-Dwelling Older Adults Using Smartphone-Based Digital Lifelogging: A Multi-Center, Prospective Observational Study.Sensors (Basel, Switzerland) · 2025Observational
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- Predicting recovery after stressors using step count data derived from activity monitors.NPJ digital medicine · 2025Article
- Association of activity with the risk of developing musculoskeletal pain in the All of Us research program.The journal of pain · 2025Article
- Association between continuous device-based physical activity monitoring over six months and cardiorespiratory, metabolic and body composition outcomes in post-surgery cancer survivors - An observational cohort analysis within a randomized controlled trial (CRBP-TS Study).BMC sports science, medicine & rehabilitation · 2025Article
25 more citing papers are in PubMed but not listed here.
Corrections and comments
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Authors and funding
6 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
backgroundFew studies have investigated the validity of mainstream wrist-based activity trackers in healthy older adults in real life, as opposed to laboratory settings.
objectiveThis 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.
methodsOverall, 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.
resultsFor 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%.
conclusionsThe 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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