Personalized Lumped Parameter Model for Healthy Adults Using Genetic Algorithm

This paper proposed a method to optimize the lumped parameter model of a cardiovascular model of healthy adults by utilizing a genetic algorithm framework. As more attention is directed to precision medicine and individualized health care, this study aims to be the proof-of-concept by using a flexible computational method optimized based on each individual physiological parameter. The lumped parameter model represents a simplified heart model together with the systemic and pulmonary system. The genetic algorithm is used to generate the optimized parameters values that minimizes the differences between the simulated systolic blood pressure with the clinical systolic blood pressure for four (4) healthy adults that have no history of cardiovascular disease and diabetes. The optimization process demonstrated that the genetic algorithm is effective in personalizing the lumped parameter model. This research presents a positive direction for improving health care by providing a simple, fast, and low-cost method for personalized medicine that could be used to enhance health management strategies.