Model predictive control of hemodynamics during intravenous general anesthesia


Farbakhsh H., Yumuk E., Othman G. B., De Keyser R., Copot D., Birs I., ...More

27th International Conference on System Theory, Control and Computing, ICSTCC 2023, Timisoara, Romania, 11 - 13 October 2023, pp.362-367 identifier

  • Publication Type: Conference Paper / Full Text
  • Doi Number: 10.1109/icstcc59206.2023.10308441
  • City: Timisoara
  • Country: Romania
  • Page Numbers: pp.362-367
  • Keywords: Anesthesia, Control, Higher-Order Approximation, Model Predictive Control
  • Istanbul Technical University Affiliated: Yes

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.