Modeling the ECG and blood pressure time series of oncological patients exposed to an external source of electromagnetic waves

Heart Rate Variability (HRV) is a measure of the variations in time intervals between consecutive heartbeats, reflecting the dynamic interplay between the sympathetic and parasympathetic branches of the autonomic nervous system. Beginning with an overview of the physiological basis of cardiac system, this master's thesis explores the most widespread technique to assess the heart rate variability, i.e., the ECG. Given that the patient data used to carry out the computational analysis derive from cancer patients, the research was carried out on the cardiac variability of people suffering from this disease and on new treatment option with exposure to low-energy amplitude-modulated radiofrequency electromagnetic fields. Moreover, this master's thesis investigated innovative methods for analyzing HRV data, including nonlinear dynamics, frequency-domain analysis, and time-domain measures. There are several models that assess the cardiac variability. In the present study, the Van der Pol oscillator model has been selected to describe oscillations in a system with nonlinear damping. The Van der Pol heart model serves as a valuable tool for studying cardiac electrophysiology and understanding the mechanisms underlying heart rhythm disorders. Its ability to capture nonlinear dynamics and reproduce physiological phenomena makes it a useful framework for both theoretical analysis and computational simulations in cardiovascular research. The analysis of the parameter sensitivity of the solutions obtained from the Van der Pol model was carried out. It included the examination of changes of amplitude, frequency and shape through construction of time series graphs, phase maps and power spectrum plots. Then the analysis was done on the data of patients, which hemodynamic system was treated with external electromagnetic fields. The evaluation comprised time series, phase plots and recursive maps. On the other hand, the Windkessel mathematical model has been used used to explain how the cardiovascular system behaves, particularly the pulsatile blood flow in arteries. Mathematically, the Windkessel model can be described using differential equations that capture the relationships between pressure, flow, and volume within the arterial system. These equations can be solved to simulate various aspects of cardiovascular physiology, such as arterial pressure waveforms. The analysis of the blood pressure waves obtained from patient data, using phase maps and Poincaré maps was conducted.