DocumentCode :
173895
Title :
A combined estimation and multi-parametric model predictive control approach for intravenous anaesthesia
Author :
Nascu, Ioana ; Lambert, Romain S. C. ; Pistikopoulos, Efstratios N.
Author_Institution :
Dept. of Chem. Eng., Centre for Process Syst. Eng., London, UK
fYear :
2014
fDate :
5-8 Oct. 2014
Firstpage :
2458
Lastpage :
2463
Abstract :
This paper describes a strategy for the control of intravenous depth of anaesthesia (DOA). Based on a mathematical model of the system, global sensitivity analysis is first presented to determine the relative influence of the uncertain pharmacokinetic and pharmacodynamic parameters and variables. Then estimation techniques are applied for the key parameters that cannot be measured directly, combined with a multi-parametric/explicit model predictive control strategy. The two estimation strategies: a Kalman filter and multi-parametric moving horizon estimation are employed and tested on a set of twelve patients.
Keywords :
Kalman filters; estimation theory; patient treatment; predictive control; sensitivity analysis; DOA; Kalman filter; combined estimation; estimation techniques; global sensitivity analysis; intravenous depth of anaesthesia; mathematical model; multiparametric model predictive control; multiparametric moving horizon estimation; pharmacodynamic parameters; pharmacokinetic parameters; Anesthesia; Drugs; Estimation; Kalman filters; Mathematical model; Sensitivity analysis; anaesthesia; inter-patient variability; mp-MHE; mp-MPC; sensitivity analysis;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Systems, Man and Cybernetics (SMC), 2014 IEEE International Conference on
Conference_Location :
San Diego, CA
Type :
conf
DOI :
10.1109/SMC.2014.6974295
Filename :
6974295
Link To Document :
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