Evaluation of Commercial Self-Monitoring Devices for Clinical Purposes: Results from the Future Patient Trial, Phase I
Open accessAbstract
Commercial self-monitoring devices are becoming increasingly popular, and over the last decade, the use of self-monitoring technology has spread widely in both consumer and medical markets. The purpose of this study was to evaluate five commercially available self-monitoring devices for further testing in clinical applications. Four activity trackers and one sleep tracker were evaluated based on step count validity and heart rate validity. Methods: The study enrolled 22 healthy volunteers in a walking test. Volunteers walked a 100 m track at 2 km/h and 3.5 km/h. Steps were measured by four activity trackers and compared to gyroscope readings. Two trackers were also tested on nine subjects by comparing pulse readings to Holter monitoring. Results: The lowest average systematic error in the walking tests was −0.2%, recorded on the Garmin Vivofit 2 at 3.5 km/h; the highest error was the Fitbit Charge HR at 2 km/h with an error margin of 26.8%. Comparisons of pulse measurements from the Fitbit Charge HR revealed a margin error of −3.42% ± 7.99% compared to the electrocardiogram. The Beddit sleep tracker measured a systematic error of −3.27% ± 4.60%. Conclusion: The measured results revealed the current functionality and limitations of the five self-tracking devices, and point towards a need for future research in this area.
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Step counts are most accurate at slow walking speeds.
“Leth et al. demonstrated that step counts are most accurate at slow walking speeds [145].”
From Wearables and the Medical Revolution (2018) · cites this paper as [145]
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- Authors
- Leth, S., Hansen, J., Nielsen, O., & Dinesen, B.
- Affiliations
- Laboratory of Welfare Technologies—Telehealth & Telerehabilitation, SMI, Department of Health Science and Technology, Aalborg University, Aalborg 9100, Denmark
- Aalborg University (DK)
- Bispebjerg Hospital (DK)
- Venue
- Sensors
- Publisher
- MDPI AG
- Published
- 2017-01-22
- Volume
- 17
- Issue
- 1
- Pages
- 211
- ISSN
- 1424-8220 (ISSN-L)
- PMC
- PMC5298782
- OpenAlex
- W2581366853
- Cited by
- 64
- References
- 28
- Citations by year
- 2026: 2 · 2025: 3 · 2024: 1 · 2023: 1 · 2022: 3 · 2021: 5 · 2020: 12 · 2019: 15 · 2018: 14 · 2017: 8
- FWCI
- 6.03
- Type
- journal article
- Language
- en
- Open access
- gold
- doi.org
- Licence
- Locations
- Sensors (publishedVersion, cc-by)
- PubMed Central (publishedVersion, cc-by)
- PubMed (publishedVersion)
- Research at the University of Copenhagen (University of Copenhagen) (publishedVersion, cc-by)
- VBN Forskningsportal (Aalborg Universitet) (submittedVersion, cc-by)
- DOAJ (DOAJ: Directory of Open Access Journals) (submittedVersion, cc-by-sa)
- Funders
- Aalborg Universitet
- Topics
- Physical Sciences › Engineering › Biomedical Engineering › Non-Invasive Vital Sign Monitoring
- Health Sciences › Medicine › Physiology › Physical Activity and Health
- Health Sciences › Health Professions › General Health Professions › Mobile Health and mHealth Applications
- Keywords
- self-monitoring devices, wearable activity trackers, sleep trackers, step count accuracy, heart rate monitoring, wearable sensors, Holter monitoring, walking test, electrocardiogram comparison
- MeSH terms
- Electrocardiography, Heart Rate, Humans, Monitoring, Physiologic, Sleep, Walking
About these checks
Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
Statistics and arithmetic are recomputed, not judged.
Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.
What counts as a claim ›How we measure confidence ›How we check this ›
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