THE RELIABILITY OF COMMERCIAL WEARABLE BIOSENSORS IN MONITORING TRAINING LOAD AND RECOVERY IN RUNNERS: A REVIEW OF CURRENT EVIDENCE

Authors

DOI:

https://doi.org/10.31435/ijitss.3(51).2026.6518

Keywords:

Wearable Technology, Biosensors, Heart Rate Variability, Heart Rate, Training Load, Recovery, Overreaching, Runners

Abstract

Introduction: Wearable devices have become increasingly popular among runners for monitoring physiological and training-related parameters, including heart rate (HR), heart rate variability (HRV), resting heart rate, sleep, and training load. However, the reliability and practical interpretation of commercially derived metrics remain important considerations.

Objective: This review aims to evaluate the reliability and practical utility of commercial wearable biosensors for monitoring training load, recovery, and potential signs of overreaching in runners. A secondary aim was to compare scientific evidence with information provided by device manufacturers and the way wearable-derived metrics are presented in popular online content.

Methods: A review of scientific literature indexed in PubMed between 2016 and 2026 was conducted using keywords related to wearable technology, physiological monitoring, running, training load, overtraining, and endurance performance. Scientific evidence was considered alongside information provided on the official websites of selected wearable manufacturers and publicly available content from popular science sources and social media platforms, including YouTube, Instagram, and TikTok. Particular attention was given to the reliability of optical measurements, HR and HRV monitoring, and commercially derived training and recovery metrics.

Results: The reviewed evidence indicates that commercial wearable devices can provide useful information for monitoring physiological responses to exercise and changes in training load. However, measurement accuracy varies according to the device, measurement method, and conditions of use. Commercial algorithms and derived metrics should therefore be interpreted cautiously, as they may not fully account for individual and contextual factors such as sleep, psychological stress, illness, or other sources of fatigue. The available evidence supports the use of wearable-derived data as an adjunct to, rather than a replacement for, subjective assessment of fatigue and recovery.

Conclusions: Commercial wearable biosensors represent a useful and accessible tool for monitoring training load and recovery in runners. Their measurements and proprietary metrics should not be interpreted in isolation or regarded as diagnostic indicators of overreaching or overtraining. A comprehensive approach combining wearable-derived data with training history, subjective symptoms, sleep, recovery, and individual context may provide a more appropriate basis for training decisions and injury prevention.

References

Maltagliati, S., Sarrazin, P., Fessler, L., Lebreton, M., & Cheval, B. (2024). Why people should run after positive affective experiences instead of health benefits. Journal of Sport and Health Science, 13(4), 445–450. https://doi.org/10.1016/j.jshs.2022.10.005

Naderi, A., Alizadeh, N., Calmeiro, L., & Degens, H. (2024). Predictors of running-related injury among recreational runners: A prospective cohort study of the role of perfectionism, mental toughness, and passion in running. Sports Health, 16(6), 1038–1049. https://doi.org/10.1177/19417381231223475

Schuster Brandt Frandsen, J., Hulme, A., Parner, E. T., Møller, M., Lindman, I., Abrahamson, J., Sjørup Simonsen, N., Sandell Jacobsen, J., Ramskov, D., Skejø, S., Malisoux, L., Bertelsen, M. L., & Nielsen, R. O. (2025). How much running is too much? Identifying high-risk running sessions in a 5200-person cohort study. British Journal of Sports Medicine, 59(17), 1203–1210. https://doi.org/10.1136/bjsports-2024-109380

Viljoen, C. T., Janse van Rensburg, D. C., Verhagen, E., van Mechelen, W., Korkie, E., & Botha, T. (2021). Epidemiology, clinical characteristics, and risk factors for running-related injuries among South African trail runners. International Journal of Environmental Research and Public Health, 18(23), Article 12620. https://doi.org/10.3390/ijerph182312620

Casado, A., Foster, C., Bakken, M., & Tjelta, L. I. (2023). Does lactate-guided threshold interval training within a high-volume low-intensity approach represent the “next step” in the evolution of distance running training? International Journal of Environmental Research and Public Health, 20(5), 3782. https://doi.org/10.3390/ijerph20053782

Stöggl, T. L., Strepp, T., Wiesinger, H. P., & Haller, N. (2024). A training goal-oriented categorization model of high-intensity interval training. Frontiers in Physiology, 15, Article 1414307. https://doi.org/10.3389/fphys.2024.1414307

Bellenger, C. R., Thomson, R. L., Davison, K., Robertson, E. Y., & Buckley, J. D. (2021). The impact of functional overreaching on post-exercise parasympathetic reactivation in runners. Frontiers in Physiology, 11, Article 614765. https://doi.org/10.3389/fphys.2020.614765

Bellenger, C. R., Fuller, J. T., Thomson, R. L., Davison, K., Robertson, E. Y., & Buckley, J. D. (2016). Monitoring athletic training status through autonomic heart rate regulation: A systematic review and meta-analysis. Sports Medicine, 46(10), 1461–1486. https://doi.org/10.1007/s40279-016-0484-2

Bellinger, P. (2020). Functional overreaching in endurance athletes: A necessity or cause for concern? Sports Medicine, 50(6), 1059–1073. https://doi.org/10.1007/s40279-020-01269-w

Shcherbina, A., Mattsson, C. M., Waggott, D., Salisbury, H., Christle, J. W., Hastie, T., Wheeler, M. T., & Ashley, E. A. (2017). Accuracy in wrist-worn, sensor-based measurements of heart rate and energy expenditure in a diverse cohort. Journal of Personalized Medicine, 7(2), Article 3. https://doi.org/10.3390/jpm7020003

Ajmal, Boonya-Ananta, T., Rodriguez, A. J., Du Le, V. N., & Ramella-Roman, J. C. (2021). Monte Carlo analysis of optical heart rate sensors in commercial wearables: The effect of skin tone and obesity on the photoplethysmography (PPG) signal. Biomedical Optics Express, 12(12), 7445–7457. https://doi.org/10.1364/BOE.439893

Cosoli, G., Antognoli, L., & Scalise, L. (2023). Methods for the metrological characterization of wearable devices for the measurement of physiological signals: State of the art and future challenges. MethodsX, 10, Article 102038. https://doi.org/10.1016/j.mex.2023.102038

Yu, H., Kotlyar, M., Dufresne, S., Thuras, P., & Pakhomov, S. (2023). Feasibility of using an armband optical heart rate sensor in naturalistic environment. Pacific Symposium on Biocomputing, 28, 43–54.

Cosoli, G., Antognoli, L., & Scalise, L. (2023). Wearable electrocardiography for physical activity monitoring: Definition of validation protocol and automatic classification. Biosensors, 13(2), Article 154. https://doi.org/10.3390/bios13020154

Nelson, B. W., & Allen, N. B. (2019). Accuracy of consumer wearable heart rate measurement during an ecologically valid 24-hour period: Intraindividual validation study. JMIR mHealth and uHealth, 7(3), Article e10828. https://doi.org/10.2196/10828

Cosoli, G., Antognoli, L., Veroli, V., & Scalise, L. (2022). Accuracy and precision of wearable devices for real-time monitoring of swimming athletes. Sensors, 22(13), Article 4726. https://doi.org/10.3390/s22134726

Muggeridge, D. J., Hickson, K., Davies, A. V., Giggins, O. M., Megson, I. L., Gorely, T., & Crabtree, D. R. (2021). Measurement of heart rate using the Polar OH1 and Fitbit Charge 3 wearable devices in healthy adults during light, moderate, vigorous, and sprint-based exercise: Validation study. JMIR mHealth and uHealth, 9(3), Article e25313. https://doi.org/10.2196/25313

Esco, M. R., Fields, A. D., Mohammadnabi, M. A., & Kliszczewicz, B. M. (2026). Monitoring training adaptation and recovery status in athletes using heart rate variability via mobile devices: A narrative review. Sensors, 26(1), Article 3. https://doi.org/10.3390/s26010003

Gronwald, T., Schaffarczyk, M., & Hoos, O. (2024). Orthostatic testing for heart rate and heart rate variability monitoring in exercise science and practice. European Journal of Applied Physiology, 124(12), 3495–3510. https://doi.org/10.1007/s00421-024-05601-4

Nuuttila, O. P., Schäfer Olstad, D., Martinmäki, K., Uusitalo, A., & Kyröläinen, H. (2025). Monitoring sleep and nightly recovery with wrist-worn wearables: Links to training load and performance adaptations. Sensors, 25(2), Article 533. https://doi.org/10.3390/s25020533

Nuuttila, O. P., Kyröläinen, H., Kokkonen, V. P., & Uusitalo, A. (2024). Morning versus nocturnal heart rate and heart rate variability responses to intensified training in recreational runners. Sports Medicine - Open, 10(1), Article 120. https://doi.org/10.1186/s40798-024-00779-5

Lacey, A., Whyte, E., O'Keeffe, S., O'Connor, S., & Moran, K. (2022). A qualitative examination of the factors affecting the adoption of injury focused wearable technologies in recreational runners. PLOS ONE, 17(7), Article e0265475. https://doi.org/10.1371/journal.pone.0265475

Van Hooren, B., Plasqui, G., & Meijer, K. (2024). The effect of wearable-based real-time feedback on running injuries and running performance: A randomized controlled trial. The American Journal of Sports Medicine, 52(3), 750–765. https://doi.org/10.1177/03635465231222464

Düking, P., Forster, A., Wicker, P., Van Hooren, B., Masur, L., Zanini, M., & Sperlich, B. (2025). Global insights on wearable technology adoption by coaches: Determinants of current use, decision making, and future intention to use. Sports Medicine - Open, 11(1), Article 131. https://doi.org/10.1186/s40798-025-00919-5

Neal, B. S., Bramah, C., McCarthy-Ryan, M. F., Moore, I. S., Napier, C., Paquette, M. R., & Gruber, A. H. (2024). Using wearable technology data to explain recreational running injury: A prospective longitudinal feasibility study. Physical Therapy in Sport, 65, 130–136. https://doi.org/10.1016/j.ptsp.2023.12.010

Muniz-Pardos, B., Sutehall, S., Gellaerts, J., Falbriard, M., Mariani, B., Bosch, A., Asrat, M., Schaible, J., & Pitsiladis, Y. P. (2018). Integration of wearable sensors into the evaluation of running economy and foot mechanics in elite runners. Current Sports Medicine Reports, 17(12), 480–488. https://doi.org/10.1249/JSR.0000000000000550

Chowdhary, K., Crockett, Z., Chua, J., & Soo Hoo, J. (2024). Exploring the relationship between running-related technology use and running-related injuries: A cross-sectional study of recreational and elite long-distance runners. Healthcare, 12(6), Article 642. https://doi.org/10.3390/healthcare12060642

Walker, K., Phillips, N., & Sheeran, L. (2025). Exploring the use of digital technology for injury prevention and self-management among recreational runners. Physical Therapy in Sport, 71, 85–91. https://doi.org/10.1016/j.ptsp.2024.12.004

Linton, L., Culpan, J., & Lane, J. (2025). Running-centred injury prevention support: A scoping review on current injury risk reduction practices for runners. Translational Sports Medicine, 2025, Article 3007544. https://doi.org/10.1155/tsm2/3007544

Wang, C., Tang, M., Xiao, K., Wang, D., & Li, B. (2024). Optimization system for training efficiency and load balance based on the fusion of heart rate and inertial sensors. Preventive Medicine Reports, 41, Article 102710. https://doi.org/10.1016/j.pmedr.2024.102710

Dial, M. B., Hollander, M. E., Vatne, E. A., Emerson, A. M., Edwards, N. A., & Hagen, J. A. (2025). Validation of nocturnal resting heart rate and heart rate variability in consumer wearables. Physiological Reports, 13(16), Article e70527. https://doi.org/10.14814/phy2.70527

https://www.garmin.com/pl-PL/garmin-technology/health-science/

https://www.whoop.com/pl/en/how-it-works/

https://ouraring.com/heart-health

https://www.youtube.com/watch?v=H1RAtR3PSG4

https://www.youtube.com/watch?v=WjzHrYUnG-4

https://www.youtube.com/watch?v=D9u3Y5J4iqI

https://www.youtube.com/watch?v=nrddUv8-7HI

https://www.youtube.com/watch?v=ulKEUGyh040

https://www.youtube.com/watch?v=BS9yzjtUw8M&t=75s

https://www.youtube.com/watch?v=_M71ac5kme8

https://www.youtube.com/watch?v=laVqSEZ2D4Y

https://www.instagram.com/p/DUxvlpDkd7Q/?utm_source=ig_web_copy_link&igsh=MzRlODBiNWFlZA==

https://www.instagram.com/p/DVlSrjYEcic/?utm_source=ig_web_copy_link&igsh=MzRlODBiNWFlZA==

https://www.instagram.com/p/DU74Ww6jcLN/?utm_source=ig_web_copy_link&igsh=MzRlODBiNWFlZA==

https://www.tiktok.com/@niezgodaaa_/video/7631270496331386144?is_from_webapp=1&sender_device=pc&web_id=7667545704009844246

https://www.instagram.com/p/C7zRYnzvgg0/?utm_source=ig_web_copy_link&igsh=MzRlODBiNWFlZA==

https://www.tiktok.com/@3lliekman/video/7621122312523320598?is_from_webapp=1&sender_device=pc&web_id=7667545704009844246

https://www.tiktok.com/@imakesss_/video/7627150719862181150?is_from_webapp=1&sender_device=pc&web_id=7667545704009844246

https://www.instagram.com/p/DYgmSiPDf6B/?utm_source=ig_web_copy_link&igsh=MzRlODBiNWFlZA==

https://www.instagram.com/p/DYJK2dOksmc/?utm_source=ig_web_copy_link&igsh=MzRlODBiNWFlZA==

https://www.instagram.com/p/DZS7yW1DUvq/?utm_source=ig_web_copy_link&igsh=MzRlODBiNWFlZA==

https://www.instagram.com/p/DUNULBYDBhz/?utm_source=ig_web_copy_link&igsh=MzRlODBiNWFlZA==

https://www.tiktok.com/@morninkaufy/video/7655318202704006431?is_from_webapp=1&sender_device=pc&web_id=7667545704009844246

https://www.tiktok.com/@daniel_biega/photo/7302447043446836512?is_from_webapp=1&sender_device=pc&web_id=7667545704009844246

Downloads

Published

2026-09-17

How to Cite

Niepokój, J., Kacer, J., Jabłoński, M., Kobaka, L., Chołast, J., Łuniewska, W., Kacer, J., Jurga, K., & Modrzyk, M. (2026). THE RELIABILITY OF COMMERCIAL WEARABLE BIOSENSORS IN MONITORING TRAINING LOAD AND RECOVERY IN RUNNERS: A REVIEW OF CURRENT EVIDENCE. International Journal of Innovative Technologies in Social Science, 4(3(51). https://doi.org/10.31435/ijitss.3(51).2026.6518

Most read articles by the same author(s)