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

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.