MATHEMATICAL MODEL FOR SELECTING RESPIRATORY MODES FOR ARTIFICIAL VENTILATION OF THE LUNGS

Q3 Engineering
N. Aralova
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引用次数: 0

Abstract

COVID-19 mainly affects the lower respiratory tract, and in 20 % of people infected with the SARS-CoV-2 virus, it penetrates deep into the lungs. At the same time, the patient's condition quickly becomes critical, and the most severe patients must be urgently placed in the intensive care unit and connected to artificial lung ventilation (IVL) devices. Artificial ventilation is necessary when the lungs can no longer breathe in enough oxygen and breathe out the carbon dioxide that has been collected in them. In this case, ventilators take over the functions of the respiratory system. The methods of carrying out artificial ventilation of the lungs require not only experimental, but also theoretical justification. For the study, it is proposed to apply a mathematical model of the functional respiratory system, in which the breathing process is represented as a controlled dynamic system and which allows predicting the gas exchange process in the lung structures in the dynamics of the respiratory cycle under various disturbing influences. To expand the area of applicability, the process features characteristic of the conditions under consideration are taken into account. It is proposed to supplement the model with equations that take into account the elasticity and resistance of pulmonary structures. Since the possibility of obtaining quantitative and qualitative characteristics of the process of mass transfer of gases with various types of artificial ventilation of the lungs is essential, equations are proposed to describe different types of pulmonary respiration. Implementation of the proposed model will allow obtaining results on the study of the process of dynamics of respiratory gases during artificial ventilation of the lungs, contributing to the solution of practical problems on the optimization of the parameters of technical devices for artificial ventilation. The subsequent combination of the proposed model with the model of the development of a viral disease can, in the presence of an array of individual data, be of significant assistance in choosing mechanical ventilation modes in a complicated course of a viral disease.
肺人工通气呼吸方式选择的数学模型
COVID-19主要影响下呼吸道,在20%的SARS-CoV-2病毒感染者中,它会深入肺部。与此同时,患者的病情迅速变得危急,最严重的患者必须紧急进入重症监护病房,并连接人工肺通气(IVL)设备。当肺部不能再吸入足够的氧气并呼出其中收集的二氧化碳时,人工通气是必要的。在这种情况下,呼吸机接管了呼吸系统的功能。进行人工肺通气的方法不仅需要实验证明,而且需要理论证明。在这项研究中,我们提出了一个功能性呼吸系统的数学模型,其中呼吸过程被表示为一个受控的动态系统,可以预测在各种干扰影响下呼吸循环动力学中肺结构中的气体交换过程。为了扩大适用范围,考虑了所考虑条件的工艺特征。建议用考虑肺结构弹性和阻力的方程来补充模型。由于有可能获得各种类型的肺人工通气气体传质过程的定量和定性特征是必不可少的,因此提出了描述不同类型肺呼吸的方程。该模型的实现将有助于获得肺部人工通气过程中呼吸气体动力学过程的研究结果,有助于解决人工通气技术装置参数优化方面的实际问题。在存在一系列个体数据的情况下,随后将所提出的模型与病毒性疾病发展模型相结合,对于在病毒性疾病的复杂病程中选择机械通气模式具有重要的帮助。
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来源期刊
Journal of Automation and Information Sciences
Journal of Automation and Information Sciences AUTOMATION & CONTROL SYSTEMS-
自引率
0.00%
发文量
0
审稿时长
6-12 weeks
期刊介绍: This journal contains translations of papers from the Russian-language bimonthly "Mezhdunarodnyi nauchno-tekhnicheskiy zhurnal "Problemy upravleniya i informatiki". Subjects covered include information sciences such as pattern recognition, forecasting, identification and evaluation of complex systems, information security, fault diagnosis and reliability. In addition, the journal also deals with such automation subjects as adaptive, stochastic and optimal control, control and identification under uncertainty, robotics, and applications of user-friendly computers in management of economic, industrial, biological, and medical systems. The Journal of Automation and Information Sciences will appeal to professionals in control systems, communications, computers, engineering in biology and medicine, instrumentation and measurement, and those interested in the social implications of technology.
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