Fractal fluctuations in the cardiovascular dynamical system : from the autonomic control to the central nervous system influence
thesisposted on 24.05.2021, 13:55 by Asif Hasan Sharif
The fractal component in the complex fluctuations of the human heart rate represents a dynamic feature that is widely observed in diverse fields of natural and artificial systems. It is also of clinical significance as the diminishing of the fractal dynamics appears to correlate with heart disease processes and adverse cardiac events in old age. While the autonomic nervous system directly controls the pacemaker cells of the heart, it does not provide an immediate characterization of the complex heart rate variability (HRV). The central nervous system (CNS) is known to be an important modulator for various cardiac functions. However, its role in the fractal HRV is largely unclear. In this research, human experiments were conducted to study the influence of the central nervous system on fractal dynamics of healthy human HRV. The head up tilt (HUT) maneuver is used to provide a perturbation to the autonomic nervous system. The subsequent fractal effect in the simultaneously recorded electroencephalography and beat-to-beat heart rate data was examined. Using the recently developed multifractal factorization technique, the common multifractality in the data fluctuation was analyzed. An empirical relationship was uncovered which shows the increase (decrease) in HRV multifractality is associated with the increase (decrease) in multifractal correlation between scale-free HRV and the cortical expression of the brain dynamics in 8 out of 11 healthy subjects. This observation is further supported using surrogate analysis. The present findings imply that there is an integrated central-autonomic component underlying the cortical expression of the HRV fractal dynamics. It is proposed that the central element should be incorporated in the fractal HRV analysis to gain a more comprehensive and better characterization of the scale-free HRV dynamics. This study provides the first contribution to the HRV multifractal dynamics analysis in HUT. The multivariate fractal analysis using factorization technique is also new and can be applied in the more general context in complex dynamics research.