基于BP神经网络的旋转血泵生理控制

doi:10.3969/j.issn.0258-8021.2019.05.009

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Abstract In this study, a physiological controller of rotary blood pumps based on BP neural networks was proposed, which realized the adaptive adjustment of the controller while the states of the recipients are changing. Choosing the mean arterial pressure as the control object, the controller adopted a three-layer neural network to optimize the PID parameters of the blood pump controller online when the physiological state of the circulatory system changed. This method was verified numerically on the mathematical model of blood circulation system. The controller was carried out under different conditions including left ventricle failure, physiological changing in systemic resistance and dynamic changing in left ventricular contractility. Results showed that in all of the cases the BP neural network based controller could overcome the disturbances well and the mean arterial pressure was stabilized at 100 mmHg after about 150 s since the controller took effect, with the steady-state error of 0 mmHg. This control method could adapt to the changes of various physiological states of the circulatory system and provide an effective control method of rotary blood pump for the subsequent in vitro and animal experiments.

Key words： blood pump BP neural networks PID physiological control

Received: 28 March 2018

PACS:

R318

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	Articles by authors
	Zhu Zhuoling
	Zhao Weiguo
	Huang Feng

Cite this article:

Zhu Zhuoling,Zhao Weiguo,Huang Feng. Physiological Control of Rotary Blood Pumps Based on BP Neural Networks[J]. Chinese Journal of Biomedical Engineering, 2019, 38(5): 581-589.

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http://cjbme.csbme.org/EN/10.3969/j.issn.0258-8021.2019.05.009 OR http://cjbme.csbme.org/EN/Y2019/V38/I5/581

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