Abstract
This paper investigates the influence of physical stress on the physiological parameters of the cardiovascular system (CVS). The work aims at estimating the physiological variables such as the Heart Rate (HR), Blood Pressure (BP), Total Peripheral Resistance (TPR) and respiration in a subject underging physical workload. The core of the model was based on the model architecture previously developed by Luczak and his coworkers. Luczak's model was first reconstructed and the original published figure plots were used to identify some of the missing parameters via Genetic Algorithms (GA). The model was then modified using real experimental data extracted from healthy subjects who underwent two-session experiments of cyclic loading based physical stress. Neuro-Fuzzy models were elicited via the data in order to describe the nonlinear components of the model. The model response has also been significantly improved by including a dynamics-based component represented by 'time' as an extra input. The final model, as well as being of a 'hybrid' nature, was found to generalize better, to be more amenable to expansions and to also lead to better predictions.