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Feedback Control of Hypnosis and Analgesia in Humans


A. Gentilini

vol. Diss. ETH Nr. 14070

The main contribution of this thesis is the design and the application of two novel feedback control systems to the practice of general anesthesia. Both improve the patient care during and after general surgery. The first aims at regulating the patient's degree of unconsciousness by continuous administration of volatile hypnotics. The second aims at regulating the patient's analgesic state by means of continuous opiates infusion. Another contribution of the thesis consists in the development of a new modeling framework to quantify anesthetic drug synergies.

In the introduction we thoroughly analyze all the potential benefits of automation in anesthesia. In particular, we discuss the mandatory safety measures that cope with the clinical safety standards and the software architecture.

Chapter 2 describes the model-based closed-loop system which delivers isoflurane to guarantee unconsciousness as assessed through Bispectral Index (BIS). This has been the first model-based closed-loop controller of hypnosis with volatile agents ever tested on humans. The results of the clinical validation of the controller on humans are presented. The patent for the control strategy to regulate BIS is pending in both the European Community and the United States of America.

Chapter 3 describes a model-based closed-loop system for the intraoperative administration of analgesics. This has been the first model-based closed-loop control strategy to regulate analgesia ever tested on humans.

In chapter 4 the problem of anesthetic drug interaction is addressed. Precisely, we present a modeling framework which is suitable to quantify and test anesthetic drug synergies. Even though several synergy models were already presented in other medical fields such as cancer therapy, they are not adequate in anesthesia. The novel modeling framework is able to describe mixtures of two and three anesthetic drugs. Further, single drug parameters can be embedded in the model equation without the need to be re-estimated.

In chapter 5 we summarize the main achievements of the thesis and outline future research directions.


Type of Publication:

(03)Ph.D. Thesis

M. Morari

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% Autogenerated BibTeX entry
@PhDThesis { Xxx:2001:IFA_425,
    author={A. Gentilini},
    title={{Feedback Control of Hypnosis and Analgesia in Humans}},
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