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Towards the control of depth of anaesthesia: identification of patient variability
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Advisor(s)
Abstract(s)
Depth of anaesthesia (DOA) is usually assessed
through the Bispectral Index (BIS) and State Entropy (SE),
which derived EEG signals. Studying the effect of drug interaction on these signals is of great importance for the development
of a suitable drug infusion system designed to control DOA. In
this paper, two renowned pharmacokinetic (PK) models for the
anaesthetic drug propofol are considered, and their influence on
the fitting and prediction abilities of a drug interaction model
for BIS and SE is assessed. This interaction model is fitted
to the individual patient data during anaesthesia induction and
tested for prediction during surgery. Two identification methods
are considered for the fitting purpose: a hybrid method and
a nonlinear least squares curve-fitting algorithm. The results
obtained for 7 patients show that the choice of the PK model has
influence on the overall performance of the interaction model;
in particular, only one PK model leads to good results in the
prediction phase. The choice of the identification method is
equally important, being the hybrid method the better suited.
The successful identification of patient variability here obtained
is a key step towards the control of DOA.
Description
Keywords
Citation
C. S. Nunes, H. Alonso, A. Castro, P. Amorim and T. Mendonça, "Towards the control of depth of anaesthesia: Identification of patient variability," 2007 European Control Conference (ECC), Kos, Greece, 2007, pp. 3109-3115
Publisher
IEEE