ABSTRACT
This paper built the mathematical model of a centrifugal blood pump, which was designed by ourselves, combined it with that of the human cardiovascular system and simulated the coupling system using Matlab. Then we set up the experiment platform, linked the blood pump to mock human cardiovascular system in case of three-stage heart failure, and measured aortic pressure and flow under different speed. The comparison between experiment results and simulation results not only indicates the coupling model is correct and the blood pump works well, but also shows that with the increase of blood pump speed, the pulsation of aortic pressure and flow will be reduced, this situation will affect the structure and function of blood vessels.
Subject(s)
Humans , Cardiovascular System , Heart-Assist Devices , Hemodynamics , Models, TheoreticalABSTRACT
The purpose of this paper is to achieve a measurement of temperature prediction for artificial heart without sensor, for which the research briefly describes the application of back propagation neural network as well as the optimized, by genetic algorithm, BP network. Owing to the limit of environment after the artificial heart implanted, detectable parameters out of body are taken advantage of to predict the working temperature of the pump. Lastly, contrast is made to demonstrate the prediction result between BP neural network and genetically optimized BP network, by which indicates that the probability is 1.84% with the margin of error more than 1%.