Improving breathing effort estimation in mechanical ventilation via optimal experiment design

Lars van de Kamp*, Bram Hunnekens, Nathan van de Wouw, Tom Oomen

*Corresponding author for this work

Research output: Contribution to journalArticleScientificpeer-review

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Abstract

Estimation of the breathing effort and relevant lung parameters of a ventilated patient is essential to keep track of a patient's clinical condition. The aim of this paper is to increase estimation accuracy through experiment design. The main method is an experiment design approach across multiple breaths within a linear regression framework to accurately identify the patient's condition. Identifiability and persistence of excitation are used to formulate an estimation problem with a unique solution. Furthermore, Fisher information is used for assessing the parameters sensitivity to slight changes of the ventilator settings to improve the variance of the estimation. The estimation method is applied to simulated patients who breathe regularly but also to patients who have variable breathing patterns. A virtual experiment is conducted for both situations to generate estimation results. The results are analyzed using mathematical tools and show that uniquely estimating the lung parameters and breathing effort over multiple breaths for both regularly and variably breathing patients is possible in the presented framework. The proposed estimation method obtains clinically relevant estimates for a large set of breathing disturbances from the simulation case-study.

Original languageEnglish
Article number100270
Number of pages10
JournalIFAC Journal of Systems and Control
Volume29
DOIs
Publication statusPublished - 2024

Keywords

  • Breathing effort estimation
  • Experiment design
  • Identification
  • Linear regression
  • Mechanical ventilation

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