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Automation in clinical anesthesia

University of British Columbia

This thesis investigates the design and performance of a controller for the maintenance of anesthesia [i.e. anaesthesia] during surgery. The controller is designed to be robustly stable for a large population of patients. Even though anesthetic drugs [i.e. anaesthetic drugs] are amongst the most dangerous drugs used in today’s clinical setting, anesthesia procedures are known to be very safe. Hence, the impact of automation in anesthesia in terms of patients’ safety cannot be clearly established. However, there are a number of significant clinical advantages to be gained by closing the loop: (1) Recent evidences suggest that most patients undergoing anesthesia procedures are overdosed. This is one of the main reasons for patients’ discomfort and slow recovery. Literature suggests that closed-loop systems can significantly reduce drug consumption and lessen recovery times, thus improving the patient outcome while reducing drug-associated costs and bed occupancy. (2) Anesthesiologists [i.e. Anaesthesiologists] have access to intravenous agents with fast onset of action and fast metabolism. Using a closed-loop controller would allow for an infusion-type titration that provides smoother transitions, thus avoiding the respiratory and hemodynamic depression observed in a bolus-based manual regimen. (3) Closed-loop controllers are also particularly well-suited for solving complex optimization problems. The profound synergy that exists between intravenous anesthetics and opioids could then be fully exploited. This could be a significant factor contributing to a reduction in drug usage and the improvement of patients’ comfort. This project is particularly challenging. In particular: (1) There is no accepted measure of depth of anesthesia. Hence, it is necessary to work at the conceptual and sensor levels in order to define adequate feedback measures. (2) Drug effect modeling suffers from many shortcomings. In particular, published studies are often not in agreement regarding model parameters. (3) Uncertainty of dose/response models is daunting. Measuring this uncertainty is necessary in order to ensure stability of the control design. While the anesthesia closed-loop concept has already been investigated in the past, no breakthrough has yet been achieved. We feel it is necessary to investigate the anesthesia system from a control engineering perspective. This thesis is divided into two distinct parts. Part A contains the first 4 chapters and presents a thorough introduction to clinical anesthesia. The main concepts, terminology and issues are covered, including anesthesia monitors and basic pharmacology principles. A review of the prior closed-loop control attempts is presented in Chapter 4. Part B contains the chapters 5 to 8. In these chapters, we investigate a new sensor technology to quantify both cortical and autonomic activity. This technology is used to derive drug effect models, from which uncertainty bounds are derived. Based on this uncertainty analysis, we derive robustly stable controllers achieving clinically adequate performances. Finally, we invite the readers to refer to Chapter 9 for a complete synopsis and summary of this thesis.

Text

2010-01-16

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http://hdl.handle.net/2429/18422

Electrical and Computer Engineering

University of British Columbia

UBCV

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