Aging changes complexity of heart rate dynamics assessed by entropy and Lyapunov exponent analysis

In recent years, many research groups are trying to quantify the physiological signals of an individual, proposing new models to assess the complex dynamics of biological control systems. Indeed, life coincides with the good handling of the structures in the organism and of physiological control mechanisms, while disease and death coincide with the loss of structure and of coordinated functions. The homeodynamic systems which normally govern health are the same that cause pathological events when activated inadequately, or rather, when the balance between order and chaos of the elementary physiological processes is no longer effectively controlled in relation to any type of stress, both external and internal to the body. In a complex system, loss or alteration of communication between physiological signals means pathology. In this paper a signal analysis method based on Entropy (E), Lyapunov exponent (1), Median Absolute Deviation (MAD), Multiscale Entropy (MSE), is proposed to estimate the complexity of long-range temporal correlation heart rate (HR) time series for an elderly person and a young person both healthy. These new methods could improve overall understanding of the physiological system of the human organism, by adopting new models and experimental paradigms, such as those of fractality and entropy, who have the ability to direct from an organ medicine to a modern systemic medicine.