Model predictive control of hemodynamics during intravenous general anesthesia

Hamed Farbakhsh, Erhan Yumuk, Ghada Ben Othman, Robin De Keyser, Dana Copot, Isabela Birs, Clara M. Ionescu

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

2 Citations (Scopus)

Abstract

In the operating rooms and the intensive care unit, it is crucial to manage the patient's hemodynamic status, which includes factors like cardiac output and mean arterial pressure. Anesthesiologists confront a difficult task while monitoring high-risk patients. Cardiac output optimization has been found to enhance the result of high-risk patients in terms of hospital stay, mortality rate, post-operative problems, etc. The application of standard control approaches is restricted because the mean arterial pressure response of a patient using vasoactive medicines is modeled by a first-order dynamical system with time-varying parameters and a time-varying delay in the control input. In order to circumvent implementation challenges, this work develops an approximation technique that describes the system using a higher-order model. Predictive control is therefore used to comprehend the practical application of higher-order hemodynamic systems. The effectiveness of this strategy is demonstrated by the simulations and outcomes that are given.

Original languageEnglish
Title of host publication2023 27th International Conference on System Theory, Control and Computing, ICSTCC 2023 - Proceedings
EditorsRadu-Emil Precup
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages362-367
Number of pages6
ISBN (Electronic)9798350337983
DOIs
Publication statusPublished - 2023
Event27th International Conference on System Theory, Control and Computing, ICSTCC 2023 - Timisoara, Romania
Duration: 11 Oct 202313 Oct 2023

Publication series

Name2023 27th International Conference on System Theory, Control and Computing, ICSTCC 2023 - Proceedings

Conference

Conference27th International Conference on System Theory, Control and Computing, ICSTCC 2023
Country/TerritoryRomania
CityTimisoara
Period11/10/2313/10/23

Bibliographical note

Publisher Copyright:
© 2023 IEEE.

Keywords

  • Anesthesia
  • Control
  • Higher-Order Approximation
  • Model Predictive Control

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