14th IFAC Symposium on System Identification, SYSID 2006

SYSID-2006 Paper Abstract

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Paper FrB3.5

Kanae, Shunshoku (Kyushu Univ.), Maeda, Kouji (Kyushu Univ.), Yang, Zi-Jiang (Kyushu Univ.), Wada, Kiyoshi (Kyushu Univ.)

Parameter Estimation of Nonlinear Differential Equation Models of Respiratory System by Using Numerical Integration Technique

Scheduled for presentation during the Invited Session "Application Results of Continuous-Time Model Identification" (FrB3), Friday, March 31, 2006, 16:50−17:10, Hunter Room

14th IFAC Symposium on System Identification, March 29 - 31, 2006, Newcastle, Australia

This information is tentative and subject to change. Compiled on July 17, 2018

Keywords Continuous Time System Estimation, Biological Systems, Nonlinear System Identification

Abstract

Pulmonary elastance provides an important basis for deciding air pressure parameters of mechanical ventilators, and airway resistance is an important parameter in the diagnosis of respiratory diseases. The authors have proposed two types of second order nonlinear differential equation models of respiratory system. In the first type of model, elastic coefficient is expressed as polynomial function of air-volume, while in the second type of model, elastic coefficient is expressed by RBF network. In this paper, the polynomial expression based model and the RBF network expression based model are compared firstly. Secondly, a unified estimation algorithm is derived based on numerical integration technique. According to the proposed algorithm, the pulmonary elastance and the airway resistance can be directly estimated from sampled measurement data of airway pressure, air-flow and air-volume. Then, the proposed algorithm is validated by some examples of application to practical clinical data.