Enhancing The Security Of Heart Rate Variability Analysis In Athletes Via Two-Factor Authentication

Abstract

This paper presents an innovative two-factor authentication (2FA) algorithm designed to protect sensitive biomedical data obtained from heart rate variability (HRV) analysis in athletes. HRV is a non-invasive marker reflecting the balance of the autonomic nervous system and is influenced not only by physical exertion but also by environmental factors such as air quality, climate conditions, and overall lifestyle. The study included 20 athletes examined before, immediately, and 1 hour after training, using electrocardiogram recordings analyzed through linear (time and frequency) and nonlinear (Poincaré) methods. The observed changes in HRV parameters illustrate physiological adaptation to exertion and recovery, which is essential for maintaining sustainable health and preventing overtraining. The innovative aspect of the work lies in its combined approach: secure data protection integrated with advanced physiological monitoring. Graphical visualization of results facilitates personalized training programs, while the developed 2FA algorithm ensures data integrity and confidentiality. Such solutions can be incorporated into intelligent systems for sports medicine and population health monitoring, contributing to sustainable health management in the context of environmental and social challenges.