Universal Modeling Method of Electrical Impedance Response During Respiration

doi:10.1007/s12204-023-2593-z

Abstract

Abstract: In recent years, significant progress has been made through impedance pneumography (IP) in diagnosing pulmonary function. Since there is no need to measure inhalation and exhalation air flow through a pipeline, IP does not increase respiratory resistance and poses no risk of cross-infection, which makes it superior to existing gas flowmeter-based spirometers in clinics. However, the changes in thoracic impedance caused by pulmonary ventilation present significant individual variability. The ratio between pulmonary ventilation volume change (ΔV ) and thoracic impedance change (ΔZ), noted as kΔV/ΔZ , differs among people. IP has to be calibrated for each person by flowmeter-type spirometer before it can be used for quantitative diagnosis. This study aimed to develop a universal model for kΔV/ΔZ using individual parameters such as body height, body mass, body mass index, body fat rate, and chest circumference. The experimental procedure, the way to identify factors for multiple regression via significance analysis and the comparison among different models are presented. This paper demonstrates the possibility of establishing a universal regression model for kΔV/ΔZ , to lay the foundation for the clinical application of IP-based pulmonary function test.

Key words: impedance pneumography, pulmonary function test, multiple regression

摘要： 近年来，阻抗呼吸描记法（IP）在肺功能诊断方面取得重大进展。由于不需要通过检测管道测量呼吸过程的气体流量，IP不增加呼吸阻力、无交叉感染的风险，比临床上既有的基于气体流量计的方法具有显著的优越性。然而，肺通气量改变引起的胸阻抗变化存在显著的个体依赖性，肺通气量变化（ΔV）与胸阻抗变化之比（ΔZ），记作kΔV/ΔZ ，因人而异，因此IP在用于定量的肺功能诊断前，必须使用流量计式肺量计对每个个体进行校准。本研究旨在利用身高、体重、身体质量指数、体脂率和胸围等个体生理参数，建立kΔV/ΔZ的普适性模型，介绍了实验过程以及通过显著性分析确定多元回归因子的方法，并对比了多种模型。本文论证了建立kΔV/ΔZ普适性回归模型的可能性，为基于IP的肺功能检测的临床应用奠定基础。

关键词: 阻抗呼吸描记法，肺功能检查，多元回归分析

CLC Number:

LIU Enkang¹ (刘恩康), MA Yixin^{1, 2∗} (马艺馨), BAI Zixuan¹ (白子轩), ZHOU Xing¹(周星), ZHANG Mingzhu¹ (张明珠), JIANG Zeyi¹ (江泽裔). Universal Modeling Method of Electrical Impedance Response During Respiration[J]. J Shanghai Jiaotong Univ Sci, 2024, 29(6): 967-978.

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