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EPSAC‐controlled anesthesia with online gain adaptation
Author(s) -
Niño J.,
De Keyser R.,
Syafiie S.,
Ionescu C.,
Struys M.
Publication year - 2009
Publication title -
international journal of adaptive control and signal processing
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.73
H-Index - 66
eISSN - 1099-1115
pISSN - 0890-6327
DOI - 10.1002/acs.1073
Subject(s) - bispectral index , dosing , target controlled infusion , sigmoid function , control theory (sociology) , propofol , controller (irrigation) , anesthesia , model predictive control , control (management) , set (abstract data type) , computer science , medicine , artificial intelligence , remifentanil , artificial neural network , agronomy , biology , programming language
This paper presents the application of predictive control to drug dosing during anesthesia in patients undergoing surgery. A single‐input (propofol) single‐output (bispectral index (BIS)) model of the patient has been assumed for prediction. The performance of our previous strategy in drug dosing control has been improved to tackle inter‐patient variability. A set of 12 patient models was studied and, in order to ensure the applicability of the proposed controller, gain adaptation in the controller is proposed. Preliminary studies have shown that due to static nonlinearity in the sigmoid curve of the patient model, feedback control is not feasible in the first part of the induction phase. Therefore, the control strategy applied in this study consists of controlling the effect site concentration ( C e ) during the first phase and controlling BIS once the relation BIS/ C e has been identified. The policy of switching and adapting the control strategies shows a good performance during the induction phase in simulation studies. Clinical tests have been scheduled at the Ghent University Hospital for the coming months. Copyright © 2008 John Wiley & Sons, Ltd.