Modeling Lung Functionality in Volume-Controlled Ventilation for Critical Care Patients

Husam Y. Al-Hetari, Y. Alginahi, M. Kabir, Noman Q. Al Naggar, Mahmoud A. Al-Rumaima, M. Hasan
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引用次数: 1

Abstract

Mechanical ventilators are the instruments that assist breathing of the patients having respiratory diseases e.g., pneumonia and coronavirus disease 2019 (COVID-19). This paper presents a modified lung model under volume-controlled ventilation to describe the lung volume and air flow in terms of air pressure signal from the ventilator. A negative feedback is incorporated in the model to balance the lung volume that is influenced by a lung parameter called positive end expiration pressure. We partially solved the lung model equation which takes the form of a first-order differential equation and then unknown parameters associated with the model were computed using a nonlinear least-squares method. Experimental data required for parameter identification and validation of the lung model were obtained by running a volume-controlled ventilator connected to a reference device and an artificial lung. The proposed model considering negative feedback achieves a better accuracy than that without feedback as demonstrated by test results. The developed model can be used in intensive care units (ICU) to evaluate mechanical ventilation performance and lung functionality in real-time.
危重病人在容量控制通气中的肺功能建模
机械呼吸机是辅助呼吸系统疾病(如肺炎和2019冠状病毒病)患者呼吸的仪器。本文提出了一种改进的容积控制通气肺模型,用呼吸机的气压信号来描述肺的容积和空气流量。模型中加入了负反馈,以平衡受肺参数(称为正末端呼气压力)影响的肺体积。对一阶微分方程形式的肺模型方程进行了部分求解,并利用非线性最小二乘法计算了模型的未知参数。通过运行连接参考装置和人工肺的容量控制呼吸机,获得肺模型参数识别和验证所需的实验数据。实验结果表明,考虑负反馈的模型比不考虑反馈的模型具有更好的精度。该模型可用于重症监护病房(ICU)实时评估机械通气性能和肺功能。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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