Proceedings of the ISCIE International Symposium on Stochastic Systems Theory and its Applications
Online ISSN : 2188-4749
Print ISSN : 2188-4730
The 47th ISCIE International Symposium on Stochastic Systems Theory and Its Applications (Dec. 2015, Honolulu)
Estimation of the Fuzzy Pulmonary Elastance Model in Consideration of the Data’s Weight
Masanori NakamichiShunshoku KanaeKiyoshi Wada
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2016 Volume 2016 Pages 61-66

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Abstract

Artificial respirators are widely used in various scenes. Doctors are required to pay scrupulous attention for the use of the artificial respirators. The ideal setting method of artificial respirator is a setting method in consideration of the pulmonary characteristic of the patient. However, we cannot know the pulmonary characteristic of the patient by the measurement of data. Therefore, we must depend on the experience and the intuition of the doctor for the setting of the artificial respirator now. Purpose of this study are to develop a method to estimate the static P-V curve and the pulmonary elastance of the patient and to set a ventilation condition of the artificial respirator. The static P-V curve and the pulmonary elastance expresses the important feature of the lung, and the static P-V curve is a basis for deciding the air-way pressure limit value. In our previous work, we suggested the estimation method of the pulmonary elastance using a recursive parameter estimation. In this study, a parameter estimation of the fuzzy rule’s in estimation technique is improved. The patient data used for parameter estimation are weighted by a conformity degree of the fuzzy variables. Therefore, the data of big conformity degree become important in parameter estimation. In the experiment, a estimation example using real patient data is given to illustrate the superiority of the proposed method.

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© 2016 ISCIE Symposium on Stochastic Systems Theory and Its Applications
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