Measuring Moderate-Intensity Exercise with the Apple Watch: Validation Study
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Abstract
BACKGROUND Moderate fitness levels and habitual exercise have a protective effect for cardiovascular disease, stroke, type 2 diabetes, and all-cause mortality. The Apple Watch displays exercise completed at an intensity of a brisk walk or above using a green “exercise” ring. However, it is unknown if the exercise ring accurately represents an exercise intensity comparable to that defined as moderate-intensity. In order for health professionals to prescribe exercise intensity with confidence, consumer wearable devices need to be accurate and precise if they are to be used as part of a personalized medicine approach to disease management. OBJECTIVE The aim of this study was to examine the validity and reliability of the Apple Watch for measuring moderate-intensity exercise, as defined as 40-59% oxygen consumption reserve (VO2R). METHODS Twenty recreationally active participants completed resting oxygen consumption (VO2rest) and maximal oxygen consumption (VO2 max) tests prior to a series of 5-minute bouts of treadmill walking at increasing speed while wearing an Apple Watch on both wrists, and with oxygen consumption measured continuously. Five-minute exercise bouts were added until the Apple Watch advanced the green “exercise” ring by 5 minutes (defined as the treadmill inflection speed). Validity was examined using a one-sample t-test, with interdevice and intradevice reliability reported as the standardized typical error and intraclass correlation. RESULTS The mean %VO2R at the treadmill inflection speed was 30% (SD 7) for both Apple Watches. There was a large underestimation of moderate-intensity exercise (left hand: mean difference = -10% [95% CI -14 to -7], d=-1.4; right hand: mean difference = -10% [95% CI -13 to -7], d=-1.5) when compared to the criterion of 40% VO2R. Standardized typical errors for %VO2R at the treadmill inflection speed were small to moderate, with intraclass correlations higher within trials compared to between trials. CONCLUSIONS The Apple Watch threshold for moderate-intensity exercise was lower than the criterion, which would lead to an overestimation of moderate-intensity exercise minutes completed throughout the day.
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In recent studies involving predominantly steady-state aerobic activities, wrist-worn activity monitors have been shown to have reasonable accuracy in heart rate estimation (approximately 5% error) but a poor estimate of energy expenditure, where the error was found to be closer to approximately 30% with a negative bias.
“In recent studies involving predominantly steady-state aerobic activities, wrist-worn activity monitors have been shown to have reasonable accuracy in HR estimation (approximately 5% error) but a poor estimate of EE, where the error was found to be closer to approximately 30% with a negative bias [16,17].”
From Accuracy of Wrist-Worn Activity Monitors During Common Daily Physical Activities and Types of Structured Exercise: Evaluation Study (2018) · cites this paper as [17]
The Discussion (Principal Findings; page not available) says the Apple Watch does not substantially overestimate or underestimate heart rate, supporting the qualitative heart-rate point. It gives no approximately 5% heart-rate error or approximately 30% negatively biased energy-expenditure error. The Results report a 10-percentage-point underestimation of the moderate-intensity exercise threshold, which is a different measure. (LLM, conf=0.83)
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Cites
HASKELL, W. L., LEE, I.-M., PATE, R. R., POWELL, K. E., BLAIR, S. N., FRANKLIN, B. A., MACERA, C. A., HEATH, G. W., THOMPSON, P. D., & BAUMAN, A. (2007) · Medicine & Science in Sports & Exercise · doi:10.1249/mss.0b013e3180616b27 · Cited by 4,616 · see citing works
Limiting factors for maximum oxygen uptake and determinants of endurance performance
BASSETT, D. R. (2000) · Medicine & Science in Sports & Exercise · doi:10.1097/00005768-200001000-00012 · Cited by 2,410 · see citing works
Migueles, J. H., Cadenas‐Sánchez, C., Ekelund, U., Nyström, C. D., Mora-González, J., Löf, M., Labayen, I., Ruiz, J. R., & Ortega, F. B. (2017) · Sports Medicine · doi:10.1007/s40279-017-0716-0 · Cited by 1,879 · see citing works
Wilmot, E. G., Edwardson, C. L., Achana, F. A., Davies, M. J., Gorely, T., Gray, L. J., Khunti, K., Yates, T., & Biddle, S. J. H. (2012) · Diabetologia · doi:10.1007/s00125-012-2677-z · Cited by 1,789 · see citing works
Hamine, S., Gerth-Guyette, E., Faulx, D., Green, B. B., & Ginsburg, A. S. (2015) · Journal of Medical Internet Research · doi:10.2196/jmir.3951 · Cited by 1,149 · see citing works
Soligard, T., Schwellnus, M., Alonso, J.-M., Bahr, R., Clarsen, B., Dijkstra, H. P., Gabbett, T., Gleeson, M., Hägglund, M., Hutchinson, M. R., et al. (2016) · British Journal of Sports Medicine · doi:10.1136/bjsports-2016-096581 · Cited by 1,041 · see citing works
Physical Activity in U.S. Adults
Tucker, J. M., Welk, G. J., & Beyler, N. K. (2011) · American Journal of Preventive Medicine · doi:10.1016/j.amepre.2010.12.016 · Cited by 977 · see citing works
U.S. Department of Health and Human (2015) · Journal of Pain & Palliative Care Pharmacotherapy · doi:10.3109/15360288.2015.1037530 · Cited by 891 · see citing works
Schwellnus, M., Soligard, T., Alonso, J.-M., Bahr, R., Clarsen, B., Dijkstra, H. P., Gabbett, T. J., Gleeson, M., Hägglund, M., Hutchinson, M. R., et al. (2016) · British Journal of Sports Medicine · doi:10.1136/bjsports-2016-096572 · Cited by 836 · see citing works
Physical activity behavior change: Issues in adoption and maintenance.
Marcus, B. H., Forsyth, L. H., Stone, E. J., Dubbert, P. M., McKenzie, T. L., Dunn, A. L., & Blair, S. N. (2000) · Health Psychology · doi:10.1037/0278-6133.19.suppl1.32 · Cited by 570 · see citing works
Hurling, R., Catt, M., De Boni, M., Fairley, B. W., Hurst, T., Murray, P., Richardson, A., & Sodhi, J. S. (2007) · Journal of Medical Internet Research · doi:10.2196/jmir.9.2.e7 · Cited by 536 · see citing works
Physiological tests for elite athletes
Gore, C. J. (2000) · Cited by 524 · see citing works
Exercise comes of age: rationale and recommendations for a geriatric exercise prescription
Singh, M. A. F. (2002) · The Journals of Gerontology Series A: Biological Sciences and Medical Sciences · doi:10.1093/gerona/57.5.m262 · Cited by 485 · see citing works
Accuracy of Heart Rate Watches: Implications for Weight Management
Wallen, M. P., Gomersall, S. R., Keating, S. E., Wisløff, U., & Coombes, J. S. (2016) · PLOS ONE · doi:10.1371/journal.pone.0154420 · Cited by 336 · see citing works
Effects of age and physical activity status on the speed-aerobic demand relationship of walking
Martin, P. E., Rothstein, D. E., & Larish, D. D. (1992) · Journal of Applied Physiology · doi:10.1152/jappl.1992.73.1.200 · Cited by 262 · see citing works
Strategies to Improve Running Economy
Barnes, K. R., & Kilding, A. E. (2015) · Sports Medicine · doi:10.1007/s40279-014-0246-y · Cited by 245 · see citing works
MobileMums: A Randomized Controlled Trial of an SMS-Based Physical Activity Intervention
Fjeldsoe, B. S., Miller, Y. D., & Marshall, A. L. (2010) · Annals of Behavioral Medicine · doi:10.1007/s12160-010-9170-z · Cited by 244 · see citing works
Gardner, B., & Lally, P. J. (2012) · Journal of Behavioral Medicine · doi:10.1007/s10865-012-9442-0 · Cited by 176 · see citing works
Sushames, A., Edwards, A., Thompson, F., McDermott, R., & Gebel, K. (2016) · PLOS ONE · doi:10.1371/journal.pone.0161224 · Cited by 152 · see citing works
Compliance with physical activity recommendations in US adults with diabetes
Zhao, G., Ford, E. S., Li, C., & Mokdad, A. H. (2008) · Diabetic Medicine · doi:10.1111/j.1464-5491.2007.02332.x · Cited by 141 · see citing works
Combining Internal- and External-Training-Load Measures in Professional Rugby League
Weaving, D., Marshall, P., Earle, K., Nevill, A. M., & Abt, G. (2014) · International Journal of Sports Physiology and Performance · doi:10.1123/ijspp.2013-0444 · Cited by 111 · see citing works
Self-citationGomersall, S. R., Ng, N., Burton, N. W., Pavey, T., Gilson, N. D., & Brown, W. J. (2016) · Journal of Medical Internet Research · doi:10.2196/jmir.5531 · Cited by 90 · see citing works
Predicting Walking METs and Energy Expenditure from Speed or Accelerometry
Brooks, A. G., Gunn, S. M., Withers, R. T., Gore, C. J., & Plummer, J. L. (2005) · Medicine & Science in Sports & Exercise · doi:10.1249/01.mss.0000170074.19649.0e · Cited by 89 · see citing works
Thompson, D., Batterham, A. M., Peacock, O. J., Western, M. J., & Booso, R. (2016) · Preventive Medicine · doi:10.1016/j.ypmed.2016.06.017 · Cited by 61 · see citing works
Miller, W. M., Spring, T. J., Zalesin, K. C., Kaeding, K. R., Janosz, K. E. N., McCullough, P. A., & Franklin, B. A. (2011) · Obesity · doi:10.1038/oby.2011.262 · Cited by 42 · see citing works
Technologies to Measure and Modify Physical Activity and Eating Environments
King, A. C., Glanz, K., & Patrick, K. (2015) · American Journal of Preventive Medicine · doi:10.1016/j.amepre.2014.10.005 · Cited by 41 · see citing works
The validity and inter-device variability of the Apple Watch™ for measuring maximal heart rate
Abt, G., Bray, J., & Benson, A. C. (2018) · Journal of Sports Sciences · doi:10.1080/02640414.2017.1397282 · Cited by 41 · see citing works
Self-citation
Flagged first, then by citations
Research works printed but not linked: 1
- [3]Pescatello LS American College of Sports Medicine. ACSM's Guidelines for Exercise Testing and Prescription. 9th edition 2014 Philadelphia, PA Wolters Kluwer/Lippincott Williams & Wilkins Health
Cited by
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Reddy, R. K., Pooni, R., Zaharieva, D. P., Senf, B., El Youssef, J., Dassau, E., Doyle III, F. J., Clements, M. A., Rickels, M. R., Patton, S. R., et al. (2018) · JMIR mHealth and uHealth · doi:10.2196/10338 · Cited by 157 · see citing works
Cosoli, G., Spinsante, S., & Scalise, L. (2020) · Measurement · doi:10.1016/j.measurement.2020.107789 · Cited by 122 · see citing works
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Marcelino, R., Sampaio, J. E., Amichay, G., Gonçalves, B. V., Couzin, I. D., & Nagy, M. (2020) · Chaos Solitons & Fractals · doi:10.1016/j.chaos.2020.109831 · Cited by 82 · see citing works
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Lui, G. Y., Loughnane, D. C., Polley, C., Jayarathna, T., & Breen, P. P. (2022) · JMIR Mental Health · doi:10.2196/37354 · Cited by 65 · see citing works
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Martín-Escudero, P., Cabanas, A. M., Dotor-Castilla, M. L., Galindo-Canales, M., Miguel‐Tobal, F., Fernández, C., Fuentes, M. E., & Giannetti, R. (2023) · Bioengineering · doi:10.3390/bioengineering10020254 · Cited by 40 · see citing works
Accuracy of the Apple Watch Oxygen Saturation Measurement in Adults: A Systematic Review
Windisch, P. Y., Schröder, C., Forster, R. E., Čihorić, N., & Zwahlen, D. R. (2023) · Cureus · doi:10.7759/cureus.35355 · Cited by 23 · see citing works
Abt, G., Bray, J., Myers, T., & Benson, A. C. (2019) · Journal of Sports Sciences · doi:10.1080/02640414.2019.1612505 · Cited by 21 · see citing works
Self-citationCaserman, P., Yum, S., Göbel, S. P., Reif, A., & Matura, S. (2024) · JMIR Biomedical Engineering · doi:10.2196/59459 · Cited by 22 · see citing works
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Hong, K.-R., Hwang, I.-W., Kim, H.-J., Yang, S.-H., & Lee, J. M. (2024) · Sensors · doi:10.3390/s24144658 · Cited by 14 · see citing works
Changes in physical activity during the initial stages of the COVID-19 pandemic
Mason, M. R., Hudgins, J. H., Campbell, M. S., Biddle, M., Ickes, M. J., Dugan, A. J., & Bollinger, L. M. (2021) · Journal of Sports Sciences · doi:10.1080/02640414.2021.1976569 · Cited by 14 · see citing works
Diba, M. A., Sarraf, V. S., Amirsasan, R., & Nikoukheslat, S. D. (2024) · JMIR Research Protocols · doi:10.2196/51599 · Cited by 4 · see citing works
Rockette‐Wagner, B., & Aggarwal, R. (2024) · Rheumatology · doi:10.1093/rheumatology/keae004 · Cited by 4 · see citing works
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Santofimia, M. J., Villanueva, F. J., Dorado, J., Rubio, A., Ruiz, J. F.-B., Llumiguano, H., del Toro, X., Wiratunga, N., & López, J. C. (2022) · Lecture notes in computer science · doi:10.1007/978-3-031-13321-3_5 · Cited by 3 · see citing works
Lutz, L., Veltmann, P., Meisterhans, R., & Giurgiu, M. (2025) · Frontiers in Psychology · doi:10.3389/fpsyg.2025.1623886 · Cited by 2 · see citing works
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Wu, Y.-F., Chen, M., Ye, J., Hong, J., Ye, J.-N., & Wu, Y.-T. (2022) · Frontiers in Psychology · doi:10.3389/fpsyg.2022.847602 · Cited by 1 · see citing works
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Ni, G., Cai, Y., Wang, Z., Kong, W., Jiang, J., Feng, L., Zhao, R., & Wang, D. (2022) · doi:10.2196/preprints.36726
Warner, A., Vanicek, N., Benson, A. C., Myers, T., & Abt, G. (2025) · Digital Health · doi:10.1177/20552076251326225
Self-citationLiu, F., & Spira, A. P. (2026) · SLEEP · doi:10.1093/sleep/zsag045
- Authors
- Abt, G., Bray, J., & Benson, A. C.
- Affiliations
- University of Hull (GB)
- Swinburne University of Technology (AU)
- Corresponding author
- Abt, Grant
- Venue
- JMIR Cardio
- Publisher
- JMIR Publications Inc.
- Published
- 2018-02-28
- Volume
- 2
- Issue
- 1
- Pages
- e6
- ISSN
- 2561-1011 (ISSN-L)
- PMC
- PMC6834212
- OpenAlex
- W2789999811
- Cited by
- 21
- References
- 27
- Citations by year
- 2026: 1 · 2025: 2 · 2024: 5 · 2023: 2 · 2022: 6 · 2021: 1 · 2020: 2 · 2019: 1 · 2018: 1
- FWCI
- 0.86
- Type
- journal article
- Language
- en
- Open access
- gold
- doi.org
- Licence
- cc-by
- Locations
- JMIR Cardio (publishedVersion, cc-by)
- Europe PMC (PubMed Central) (publishedVersion, cc-by)
- PubMed Central (publishedVersion, cc-by)
- PubMed (publishedVersion)
- Repository@Hull (Worktribe) (University of Hull) (submittedVersion, cc-by)
- Swinburne figshare (Swinburne University of Technology) (submittedVersion)
- Funders
- British Heart Foundation
- Topics
- Health Sciences › Medicine › Physiology › Physical Activity and Health
- Health Sciences › Medicine › Complementary and alternative medicine › Cardiovascular and exercise physiology
- Health Sciences › Health Professions › General Health Professions › Mobile Health and mHealth Applications
- Keywords
- Apple Watch, moderate-intensity exercise, exercise intensity monitoring, wearable devices, VO2max, treadmill walking, device validation, reliability statistics, exercise prescription, personalized medicine
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