基于流体网络的人体血液体循环分析

doi:10.3969/j.issn.0258-8021.2017.05.010

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Abstract Hemodynamic parameters will be studied under the changes of different organs flow resistances, based on the principles of traditional Chinese medicine pulse diagnosis. A fluid network model of systemic circulation of human blood is established. Utilizing a 10 times harmonic hemodynamics expression of cardiac output and the average method of adaptive control, the model is solved when η is respectively set to 0.5, 1.0, 1.5, 2.0, 2.5 and 3.0. With the cardiac index keeping constant, the results show that the average flow rate decreases with the increase of flow resistance of corresponding branch. The aortic mean pressure increases with the rise of flow resistance of organ branch. When η is setted to 3.0, the aortic mean pressure increases 23.29%, 16.42%, 14.67%, 9.69%, 9.59% and 7.82% higher than normal by the flow resistance increase of brain, liver, kidney, stomach, intestine and spleen branch respectively. The flow resistance of liver and kidney branch has the great effect on the radial artery mean pressure, which respectively increases 22.85% and 11.17% when η is setted to 3.0. While the other organ branches have less influence. For the harmonic amplitude of the radial artery pressure, the biggest affecting factor is the brain branch flow. The liver and kidney branch have less influence than the brain. The stomach, intestine and spleen branch have little impact on it. In this paper, we have found the relationships between the hemodynamic parameters and the changes of different organs flow resistances by the simulation method, and it can provide some theoretical basis for traditional Chinese medicine pulse diagnosis.

Key words： systemic circulation fluid network model hemodynamics average method

Received: 17 August 2016

PACS:

R318

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	Xu Ke
	Zhao Liangju
	Li Mingyang

Cite this article:

Xu Ke,Zhao Liangju,Li Mingyang. The Analysis of the Systemic Circulation of Human Blood Based on Fluid Network[J]. Chinese Journal of Biomedical Engineering, 2017, 36(5): 580-588.

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http://cjbme.csbme.org/EN/10.3969/j.issn.0258-8021.2017.05.010 OR http://cjbme.csbme.org/EN/Y2017/V36/I5/580

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