The DOI matches its Crossref record; 15 of the 15 references it cites were found in a registry or an index.
Variable Accuracy of Wearable Heart Rate Monitors during Aerobic Exercise
Abstract
PURPOSE: Athletes and members of the public increasingly rely on wearable HR monitors to guide physical activity and training. The accuracy of newer, optically based monitors is unconfirmed. We sought to assess the accuracy of five optically based HR monitors during various types of aerobic exercise. METHODS: Fifty healthy adult volunteers (mean ± SD age = 38 ± 12 yr, 54% female) completed exercise protocols on a treadmill, a stationary bicycle, and an elliptical trainer (±arm movement). Each participant underwent HR monitoring with an electrocardiogaphic chest strap monitor (Polar H7), forearm monitor (Scosche Rhythm+), and two randomly assigned wrist-worn HR monitors (Apple Watch, Fitbit Blaze, Garmin Forerunner 235, and TomTom Spark Cardio), one on each wrist. For each exercise type, HR was recorded at rest, light, moderate, and vigorous intensity. Agreement between HR measurements was assessed using Lin's concordance correlation coefficient (rc). RESULTS: Across all exercise conditions, the chest strap monitor (Polar H7) had the best agreement with ECG (rc = 0.996) followed by the Apple Watch (rc = 0.92), the TomTom Spark (rc = 0.83), and the Garmin Forerunner (rc = 0.81). Scosche Rhythm+ and Fitbit Blaze were less accurate (rc = 0.75 and rc = 0.67, respectively). On treadmill, all devices performed well (rc = 0.88-0.93) except the Fitbit Blaze (rc = 0.76). While bicycling, only the Garmin, Apple Watch, and Scosche Rhythm+ had acceptable agreement (rc > 0.80). On the elliptical trainer without arm levers, only the Apple Watch was accurate (rc = 0.94). None of the devices was accurate during elliptical trainer use with arm levers (all rc < 0.80). CONCLUSION: The accuracy of wearable, optically based HR monitors varies with exercise type and is greatest on the treadmill and lowest on elliptical trainer. Electrode-containing chest monitors should be used when accurate HR measurement is imperative.
Overview
Integrity signals
Registry
Cites
Statistics
Verification
Claims the paper makes
Claims other papers make about this one
Each is checked against this paper’s own text: does it say what the citing paper says it does?
In the citing paper
“other studies have used suboptimal reference methods, such as the chest straps45–47 or pulse oximeters48, which themselves have a degree of error (varying between 0 and 40 bpm when compared to ECGs44).”
From Guidelines for wrist-worn consumer wearable assessment of heart rate in biobehavioral research (2020) · cites this paper as [46]
In the citing paper
“two related factors identified as influencing wearable HR accuracy are motion artifacts23 and level of physical activity46.”
From Guidelines for wrist-worn consumer wearable assessment of heart rate in biobehavioral research (2020) · cites this paper as [46]
Citations
Cites
STATISTICAL METHODS FOR ASSESSING AGREEMENT BETWEEN TWO METHODS OF CLINICAL MEASUREMENT
Martin Bland, J., & Altman, D. (1986) · The Lancet · doi:10.1016/s0140-6736(86)90837-8 · Cited by 47,965
Beckett, A. H., Rowland, M., & TURNER, P. (1965) · The Lancet · doi:10.1016/s0140-6736(65)91037-8 · Cited by 16,917
A concordance correlation coefficient to evaluate reproducibility.
Lin, L. I.-K. (1989) · Biometrics · doi:10.2307/2532051 · Cited by 8,785
Wearable Devices as Facilitators, Not Drivers, of Health Behavior Change
Patel, M. S., Asch, D. A., & Volpp, K. G. (2015) · JAMA · doi:10.1001/jama.2014.14781 · Cited by 808
Swan, M. (2009) · International Journal of Environmental Research and Public Health · doi:10.3390/ijerph6020492 · Cited by 730
Accuracy of Smartphone Applications and Wearable Devices for Tracking Physical Activity Data
Case, M. A., Burwick, H. A., Volpp, K. G., & Patel, M. S. (2015) · JAMA · doi:10.1001/jama.2014.17841 · Cited by 694
Fitbit®: An accurate and reliable device for wireless physical activity tracking
Diaz, K. M., Krupka, D. J., Chang, M. J., Peacock, J., Ma, Y., Goldsmith, J., Schwartz, J. E., & Davidson, K. W. (2015) · International Journal of Cardiology · doi:10.1016/j.ijcard.2015.03.038 · Cited by 405
Validity of Consumer-Based Physical Activity Monitors
LEE, J.-M., KIM, Y., & WELK, G. J. (2014) · Medicine & Science in Sports & Exercise · doi:10.1249/mss.0000000000000287 · Cited by 401
Accuracy of wrist-worn heart rate monitors
Wang, R., Blackburn, G., Desai, M., Phelan, D., Gillinov, L., Houghtaling, P., & Gillinov, M. (2017) · JAMA Cardiology · doi:10.1001/jamacardio.2016.3340 · Cited by 386
Self-citationEl-Amrawy, F., & Nounou, M. I. (2015) · Healthcare Informatics Research · doi:10.4258/hir.2015.21.4.315 · Cited by 287
Cited by
Sorted by citations
Items 301–346 of 346
Wearable Sensors and Telemedicine Strategies for Cystic Fibrosis Patients
Elce, A. (2021) · American Journal of Biomedical Science & Research · doi:10.34297/ajbsr.2021.12.001774
Sibhiraja, S., & Dey, N. (2021) · Revista Gestão Inovação e Tecnologias · doi:10.47059/revistageintec.v11i2.1695
Preparation of P(MePEGGCA-co-HDCA) nanoparticles loaded with doxorubicin: mixing issues
Lince, F., Marchisio, D. L., Stella, B., Bolognesi, S., Dosio, F., & Barresi, A. (2009) · PORTO@Iris
Enplegu, interés eta diruari buruzko teoria orokorra
Keynes, J. M. (1998) · Dialnet (Universidad de la Rioja)
Somville, F. J. M. P., Bogaert, P. V., Cauwer, H. G. D., Olmen, D. V., & Franck, E. (2021) · doi:10.2196/preprints.36002
Mukaino, M., Ogasawara, T., Matsuura, H., Aoshima, Y., Suzuki, T., Yamaguchi, M., Nakashima, H., Saitoh, E., Tsukada, S., & Otaka, Y. (2021) · Research Square · doi:10.21203/rs.3.rs-1148576/v1
Validation of heart rate measurement of Fitbit Charge 4 and Xiaomi Mi Band 5 (Preprint)Preprint
Jachymek, M., Jachymek, M., Kiedrowicz, R., Kaźmierczak, J., & Peregud‐Pogorzelska, M. (2021) · doi:10.2196/preprints.30893
Mental Health Insights from Individual Physiologic and Lifestyle Continuous SensingPreprint
Nag, N., Sultan, T., Lin, M., & Richardson, A. (2022) · PsyArXiv (OSF Preprints) · doi:10.31234/osf.io/5qhrc
Kishon, L., & Bahat, H. S. (2023) · Applied Sciences · doi:10.3390/app13053018
New Deconstruct Elliptical sports machine and Elliptical machine
Elvira-Aranda, C., Terol-Sanchis, M., Gomis-Gomis, M. J., & Llorca, C. S. (2023) · Scientific Journal of Sport and Performance · doi:10.55860/zwdl2353
Rusterholz, F., Rodriguez, A., Ortiz, V., & Peacock, C. A. (2023) · Research Directs in Health Sciences · doi:10.53520/rdhs2023.10475
Exercise and physiological variability: analysis and applications
Biltz, G. R., & Lundstrom, C. J. (2023) · Oxford University Press eBooks · doi:10.1093/med/9780192843968.003.0006
Little, K., Sieverdes, J. C., Thomas, D., Lineberger, M. B., Bornsteind, D., Bergamine, M., & Dudgeon, W. D. (2023) · American Journal of Undergraduate Research · doi:10.33697/ajur.2023.088
Sibhiraja, S., & Dey, N. (2023) · AIP conference proceedings · doi:10.1063/5.0150493
Ransom, D. M. E., Tudor, B. H., Irani, S., Rehman, M., Mularoni, P. P., & Ahumada, L. M. (2023) · doi:10.2196/preprints.54630
Definition, Scope, and Applications of Physiotherapy Biofeedback: Systematic Reviews
Oh, J.-S., Lee, K.-J., & Kim, S.-G. (2023) · Journal of the Korean Society of Physical Medicine · doi:10.13066/kspm.2023.18.4.109
Ceugniez, M., Devanne, H., & Hermand, É. (2023) · doi:10.2196/preprints.54871
Yao, L., Pan, X., Yang, Y., Zhong, W., Li, J., Wang, Z., & Xu, L. (2024) · Neurology Asia · doi:10.54029/2024mui
de Miranda, L. R. A., Reis, C. B. F., Bergantini, T. C., Neto, V. H. G., Carletti, L., & Leite, R. D. (2024) · Revista Brasileira de Fisiologia do Exercício · doi:10.33233/rbfex.v23i1.5580
Ajjimaporn, A., Buaprapahn, P., Senwandee, P., Sirisoonthorn, N., Chalermthamrong, P., & Ramyarangsi, P. (2024) · SSRN Electronic Journal · doi:10.2139/ssrn.4844934
Bearing witness: Early detection of cardiac arrhythmias using a modified wearable ECG monitor
Santi, A. D., Liang, K. W., Jadotte, M., & Fishberger, S. B. (2024) · Heart Rhythm · doi:10.1016/j.hrthm.2024.07.001
Neal, F. K., Bordonie, N. C., Miller, M. D., Agostinelli, P. J., & Sefton, J. M. (2024) · International Journal of Occupational and Environmental Safety · doi:10.24840/2184-0954-008.002-002379
Fitness Yapan Bireylerin Giyilebilir Teknolojilerin Kullanımına İlişkin Görüşleri
Parlakyıldız, S., Avan, S. K., & Sözüer, O. H. (2024) · Sportive · doi:10.53025/sportive.1500801
Bae, M., Lee, Y., & Jin, J. (2024) · European Journal of Adapted Physical Activity · doi:10.5507/euj.2024.009
Giyilebilir Cihazlardan Gelen Sağlık Verilerinin Kimliksizleştirilmesi Yeterince Güvenli mi?
Durmuş, V. (2024) · İstanbul Gelişim Üniversitesi Sağlık Bilimleri Dergisi · doi:10.38079/igusabder.1326830
The effect of materials in photoplethysmography-enabled mouthguards
Bueno, L. D. A. E., & Bergmann, J. (2025) · Sensors and Actuators A Physical · doi:10.1016/j.sna.2025.116269
Ransom, D. M. E., Tudor, B. H., Irani, S., Rehman, M., Suskauer, S. J., Mularoni, P. P., & Ahumada, L. M. (2025) · doi:10.2196/preprints.73214
Limited Validity of the Low-Cost Coospo H808S Heart-Rate Monitor Compared to the Polar H10
Protzen, G. V., Riesco-Villar, J., González-Fernández, A., Escribano-Pascual, A., & Boullosa, D. A. (2025) · International Journal of Sports Physiology and Performance · doi:10.1123/ijspp.2025-0126
Sirisunhirun, P., Bandidniyamanon, W., Jrerattakon, Y., Muangsomboon, K., Pramyothin, P., Nimanong, S., Tanwandee, T., Charatcharoenwitthaya, P., Chainuvati, S. P., & Chotiyaputta, W. (2022) · Figshare · doi:10.6084/m9.figshare.19174040
İŞE BAĞLI DİNLENME SÜRELERİNİN MAKİNE ÖĞRENMESİ İLE TAHMİN EDİLMESİ
TÜRKSEVER, M., Kahya, E., & Özkan, N. F. (2025) · Endüstri Mühendisliği · doi:10.46465/endustrimuhendisligi.1733882
Smartwatch-Based Heart Rate Tracking
Francisti, J., Fodor, K., & Balogh, Z. (2026) · Communications in computer and information science · doi:10.1007/978-3-032-17020-0_8
Kautsar, H. M., Syahid, A. M., & Novian, G. (2026) · Pedagogy of Physical Culture and Sports · doi:10.15561/26649837.2026.0210
Exploring stress-coupling dynamics in fatigue development among high-speed railway drivers
Chen, Y. L., Li, Y., Wei, L., Jin, Y., Yamamoto, T., Wu, G., & Jiang, C. (2026) · Safety Science · doi:10.1016/j.ssci.2026.107258
Tan, C., Tamei, T., Ishii, A., Arimoto, N., & Shiotani, H. (2026) · Chronobiology International · doi:10.1080/07420528.2026.2669593
Schipper, R. M., Djibrillah, F. O., Roosink, M., Winkens, L. H. H., John, A., Hazebroek, E. J., Witteveen, A., & Berendsen, A. A. M. (2026) · JMIR mhealth and uhealth · doi:10.2196/87324 · Cited by 1
(2022) · Elsevier eBooks · doi:10.1016/b978-3-437-24041-6.00002-7
Shaikh, W. A., Kiri, S., Bohra, S., Desai, K., Desai, D., & Buddhdev, S. (2026) · Research Square · doi:10.21203/rs.3.rs-10566086/v1
Berlik, M., & Broda, M. (2026) · Central European Journal of Operations Research · doi:10.1007/s10100-026-01037-7
Yang, Y., Qing, J., Cui, B., Zhao, X., & Yu, J. (2026) · Frontiers in Physiology · doi:10.3389/fphys.2026.1740055
Ghazzal, B., Hasan, I., Hasan, N., Ghazzal, Z. B., & Refaat, M. M. (2026) · Frontiers in Cardiovascular Medicine · doi:10.3389/fcvm.2026.1949249 · Cited by 1
Using In-Situ Physiological Measures to Assess Engagement in a Healthy Eating Program
Melton, K. K., Johns, S., & Stull, A. J. (2026) · American Journal of Evaluation · doi:10.1177/10982140261488409
Validity of the garmin Forerunner 265 to predict VO2max and race performance times
Howard, J., Ellis, R., Fortner, C. K., Doyle, J. A., & Otis, J. S. (2026) · Journal of Medical Engineering & Technology · doi:10.1080/03091902.2026.2741912
Shah, S. T. A., Santos, J. P. O., Fernandes, J. M., Pereira, A. B., & Constantinescu, G. (2026) · Sensors · doi:10.3390/s26196334
Metadata
- Authors
- GILLINOV, S., ETIWY, M., WANG, R., BLACKBURN, G., PHELAN, D., GILLINOV, A. M., HOUGHTALING, P., JAVADIKASGARI, H., & DESAI, M. Y.
- Affiliations
- Cleveland Clinic (US)
- ORCID
- Venue
- Medicine & Science in Sports & Exercise
- Published
- 2017-08
- Volume
- 49
- Issue
- 8
- Pages
- 1697-1703
- ISSN
- 0195-9131 (ISSN-L)
- OpenAlex
- W2597782088
- Cited by
- 345
- References
- 15
- Citations by year
- 2026: 23 · 2025: 30 · 2024: 28 · 2023: 52 · 2022: 42 · 2021: 52 · 2020: 49 · 2019: 35 · 2018: 28 · 2017: 4
- FWCI
- 14.27
- Type
- journal article
- Language
- en
- Open access
- closed
- Locations
- Medicine & Science in Sports & Exercise (publishedVersion)
- PubMed (publishedVersion)
- Topics
- Physical Sciences › Engineering › Biomedical Engineering › Non-Invasive Vital Sign Monitoring
- Health Sciences › Medicine › Physiology (medical) › Cardiovascular and exercise physiology
- Health Sciences › Medicine › Public Health, Environmental and Occupational Health › Physical Activity and Health
- Keywords
- wearable heart rate monitor, heart rate accuracy, aerobic exercise, wrist-worn devices, treadmill exercise, stationary cycling, elliptical trainer, exercise intensity, Apple Watch, Fitbit
- MeSH terms
- Adult, Equipment Design, Female, Heart, Humans, Male, Prospective Studies, Exercise, Electrocardiography, Ambulatory, Optical Phenomena
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 ›
Are you an author, or do you see a problem with this page? Request a review