Optimization of Multiple Control Parameters of Mathematical Model of Cardiopulmonary Resuscitation Based on Genetic Algorithm

Abstract

The objective of the study is to improve the aortic pressure and myocardial perfusion pressure during cardiac arrest through optimized control parameters of external force for cardiopulmonary resuscitation (CPR). The CPR technology described in this paper was active compression-decompression CPR with enhanced external counter-pulsation and inspiratory impedance threshold valve (AEI-CPR). A genetic algorithm (GA) was applied on an established mathematical model of human circulatory system to obtain optimum control parameters of external force for AEI-CPR. Three groups of optimal control parameters were found after running the algorithm for three times. The average number of model running was 149. Obvious hemodynamic effect was attained when the frequency of compression was about 110 min -1 and the lower limbs compression began at the end of chest compression.