Heart rate complexity changes during bicycle ergometry

Abstract

Introduction Over the past decade, the non-linear dynamics methods based on deterministic chaos and the complex system theories to analyse the complex physiological systems have been introduced. The traditional methods based on self-regulation and statistics appear to be insufficient for the analysis of non-linear and non-stationary signals generated by the living organism. The main feature of the physiological systems – their complexity is ’hidden’ in the biomedical signals. Human body adaptation to physical load is an actual task of sports and clinical medicine. During bicycle ergometry work we can evaluate the functionality of the human body. The main task was to find the complexity measure for ECG RR interval, which could integrally evaluate body reaction to physical load. Methods There were used the standard stress test method of provocative incremental bicycle ergometry work. For evaluation of cardiovascular system reactions the ECG analysis system “Kaunas – Load” was used. The investigated contingent consisted of 21 asymptomatic women (20-50 years old), participating in aerobics exercise program. We divided these group according age (20-30 years old group, 11 women, and 31 – 50 years old group, 10 women), analyzed load and recovery data separate. We used RR intervals (ms) during every cardio-cycle, divided data to the same size intervals and calculated averages and variances. We hypothesized that the algebraic form of the dependence variance (average) is the power function. All our data satisfied this hypothesis (p<0.05). The relation between averages and variances is called allometric. The slope of logarithmic dependence we called the allometric complexity measure. According to Bruce J. West, we hypothesized, that if the absolute value of the slope is less than 1, the complexity of the process is low and body reaction to load is inadequate, if more than 1 – the complexity is high- the higher value of complexity means better [...].