Accuracy of Wearable Heart Rate Monitors under Static and High-Intensity Activity Conditions

Balogh, János Dávid and Adamkó, Attila (2026) Accuracy of Wearable Heart Rate Monitors under Static and High-Intensity Activity Conditions. In: Proceedings of the 13th International Conference on Applied Informatics. Líceum Kiadó, Eger, pp. 48-54. ISBN 9789634963271

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Abstract

The widespread adoption of wearable devices has created new opportunities for continuous monitoring of physical activity, cardiovascular health, and sleep patterns. However, it remains an open question to what extent the physiological and kinematic data provided by commercial smartwatches can be considered accurate and clinically interpretable under different conditions. The aim of this study is to compare heart rate (HR), heart rate variability (HRV), step count, and sleep parameters measured by four commercial smartwatches against clinical-grade reference devices under both static/resting and dynamic activity conditions. In a controlled study involving 30 participants, we evaluated four popular device models: Apple Watch Series 8, Garmin Forerunner 265, Samsung Galaxy Watch 6, and Xiaomi Smart Band 8. For heart rate in a static environment, the devices showed high correlation with the reference (r > 0.92) and low Mean Absolute Error (MAE < 3 bpm). During high-intensity physical activity, the HR error rate increased significantly across all models (MAE = 8–16 bpm). Step count accuracy was generally high during steady-state walking (error < 3%), but variability increased during running. Regarding sleep parameters, the devices estimated Total Sleep Time (TST) with moderate accuracy, but sleep stage determination showed poor reliability compared to clinical polygraphy. The results suggest that smartwatches are highly suitable for detecting long-term health trends and tracking general physical activity. However, their use for critical clinical decision-support requires careful interpretation, particularly regarding dynamic heart rate tracking and sleep architecture analysis. The study highlights the need for standardized multi-parameter validation protocols.

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