Nonlinear dynamics of the patient’s response to drug effect during general anesthesia

•Wavelet time–frequency analysis is used to extract useful information from the clinical signals.•Model based predictive control algorithms are employed to regulate the depth of sedation.•Two manipulating drugs are used.•The results of identification from real data suggest that the proposed approach...

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Bibliographic Details
Published inCommunications in nonlinear science & numerical simulation Vol. 20; no. 3; pp. 914 - 926
Main Authors Ionescu, Clara, Tenreiro Machado, Jose, De Keyser, Robin, Decruyenaere, Johan, Struys, Michel M.R.F.
Format Journal Article
LanguageEnglish
Published Elsevier B.V 01.03.2015
Subjects
Anesthesia
Bispectral index
Computer simulation
Depth of anesthesia
Drug delivery
Drugs
EEC
Identification
Mathematical models
Optimization
Patients
Predictive control
Robustness
Wavelet analysis
Wavelet analysis
Bispectral index
Drug delivery
Identification
Depth of anesthesia
Predictive control
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Summary:•Wavelet time–frequency analysis is used to extract useful information from the clinical signals.•Model based predictive control algorithms are employed to regulate the depth of sedation.•Two manipulating drugs are used.•The results of identification from real data suggest that the proposed approach is suitable for clinical practice. In today’s healthcare paradigm, optimal sedation during anesthesia plays an important role both in patient welfare and in the socio-economic context. For the closed-loop control of general anesthesia, two drugs have proven to have stable, rapid onset times: propofol and remifentanil. These drugs are related to their effect in the bispectral index, a measure of EEG signal. In this paper wavelet time–frequency analysis is used to extract useful information from the clinical signals, since they are time-varying and mark important changes in patient’s response to drug dose. Model based predictive control algorithms are employed to regulate the depth of sedation by manipulating these two drugs. The results of identification from real data and the simulation of the closed loop control performance suggest that the proposed approach can bring an improvement of 9% in overall robustness and may be suitable for clinical practice.
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ISSN:1007-5704
1878-7274
DOI:10.1016/j.cnsns.2014.05.014