METHODOLOGICAL AND PHYSIOLOGICAL ASPECTS OF HEART RATE VARIABILITY APPLICATION IN TRAINING PROCESS MANAGEMENT: A CRITICAL ANALYSIS OF DIGITAL SMART DEVICE DATA

Abstract

This critical analysis examines the integration of Heart Rate Variability (HRV) monitoring from consumer wearables into athletic training. HRV, a non-invasive biomarker of autonomic nervous system balance, has become a "gold standard" for assessing functional state. However, the proliferation of smart devices (Apple, Garmin, Polar, Samsung) has created a paradox of accessibility versus interpretative clarity. The study deconstructs the core physiology, contrasting the rapid parasympathetic metric RMSSD (used for recovery assessment in performance-focused ecosystems like Garmin) with the broader adaptive-capacity metric SDNN (common in wellness-focused systems like Apple). A central finding is the critical algorithmic heterogeneity across platforms, which renders direct comparison of absolute values between different device ecosystems fundamentally flawed. The work highlights significant methodological pitfalls, most notably the dangerous condition of parasympathetic overreaching, where paradoxically high HRV can mask severe fatigue and imminent performance decline. Furthermore, HRV is profoundly confounded by non-training stressors (sleep, diet, illness), emphasizing its role as a sensitive but non-specific marker of homeostatic disturbance. Consequently, effective application requires a paradigm shift from isolated daily readings to longitudinal trend analysis against an individual baseline. The study concludes that HRV is a facultative, not primary, tool. It must be integrated via a "triangulation" principle, where its objective data is consistently verified against subjective athlete feedback (well-being, sleep quality) and quantitative training load metrics to inform robust, individualized coaching decisions and avoid the risks of misinterpreting simplified commercial readiness scores.