Literature DB >> 22711777

System identification and closed-loop control of end-tidal CO2 in mechanically ventilated patients.

Jin-Oh Hahn, Guy A Dumont, J Mark Anersmino.   

Abstract

This paper presents a systematic approach to system identification and closed-loop control of end-tidal carbon dioxide partial pressure (PETCO2) in mechanically ventilated patients. An empirical model consisting of a linear dynamic system followed by an affine transform is proposed to derive a low-order and high-fidelity representation that can reproduce the positive and inversely proportional dynamic input-output relationship between PETCO2 and minute ventilation (MV) in mechanically ventilated patients. The predictive capability of the empirical model was evaluated using experimental respiratory data collected from eighteen mechanically ventilated human subjects. The model predicted PETCO2 response accurately with a root-mean-squared error (RMSE) of 0.22+/-0.16 mmHg and a coefficient of determination (r2) of 0.81+/-0.18 (mean+/-SD) when a second-order rational transfer function was used as its linear dynamic component. Using the proposed model, a closedloop control method for PETCO2 based on a proportionalintegral (PI) compensator was proposed by systematic analysis of the system root locus. For the eighteen mechanically ventilated patient models identified, the PI compensator exhibited acceptable closed-loop response with a settling time of 1.27+/- 0.20 min and a negligible overshoot (0.51+/-1.17%), in addition to zero steady-state PETCO2 set point tracking. The physiologic implication of the proposed empirical model was analyzed by comparing it with the traditional multi-compartmental model widely used in pharmacological modeling.

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Year:  2012        PMID: 22711777     DOI: 10.1109/TITB.2012.2204067

Source DB:  PubMed          Journal:  IEEE Trans Inf Technol Biomed        ISSN: 1089-7771


  4 in total

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Authors:  Amirehsan Sarabadani Tafreshi; Jan Okle; Verena Klamroth-Marganska; Robert Riener
Journal:  Med Biol Eng Comput       Date:  2017-02-10       Impact factor: 2.602

2.  Automatic Detection of Endotracheal Intubation During the Anesthesia Procedure.

Authors:  Ali Jalali; Mohamed Rehman; Arul Lingappan; C Nataraj
Journal:  J Dyn Syst Meas Control       Date:  2016-08-09       Impact factor: 1.372

3.  A Comparative Data-Based Modeling Study on Respiratory CO2 Gas Exchange during Mechanical Ventilation.

Authors:  Chang-Sei Kim; J Mark Ansermino; Jin-Oh Hahn
Journal:  Front Bioeng Biotechnol       Date:  2016-02-03

4.  Practical Use of Regularization in Individualizing a Mathematical Model of Cardiovascular Hemodynamics Using Scarce Data.

Authors:  Ali Tivay; Xin Jin; Alex Kai-Yuan Lo; Christopher G Scully; Jin-Oh Hahn
Journal:  Front Physiol       Date:  2020-05-26       Impact factor: 4.566

  4 in total

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