Document Type thesis Author Name Hawkins, Kevin Michael URN etd-0424103-105500 Title Development of an Automated Anesthesia System for the Stabilization of Physiological Parameters in Rodents Degree MS Department Biomedical Engineering Advisors Professor Ross D. Shonat, Ph.D., Advisor Professor Yitzhak Mendelson, Ph.D., Committee Member Professor Fred J. Looft, Ph.D., Committee Member Keywords LabVIEW Fuzzy Logic Control Anesthesia Date of Presentation/Defense 2003-04-21 Availability unrestricted
The testing of any physiological diagnostic system in-vivo depends critically on the stability of the anesthetized animal used. That is, if the systemic physiological parameters are not tightly controlled, it is exceedingly difficult to assess the precision and accuracy of the system or interpret the consequence of disease. In order to ensure that all measurements taken using the experimental system are not affected by fluctuations in physiological state, the animal must be maintained in a tightly controlled physiologic range. The main goal of this project was to develop a robust monitoring and control system capable of maintaining the physiological parameters of the anesthetized animal in a predetermined range, using the instrumentation already present in the laboratory, and based on the LabVIEWR software interface. A single user interface was developed that allowed for monitoring and control of key physiological parameters including body temperature (BT), mean arterial blood pressure (MAP) and end tidal CO2 (ETCO2). Embedded within this interface was a fuzzy logic based control system designed to mimic the decision making of an anesthetist. The system was tested by manipulating the blood pressure of a group of anesthetized animal subjects using bolus injections of epinephrine and continuous infusions of phenylephrine (a vasoconstrictor) and sodium nitroprusside (a vasodilator). This testing showed that the system was able to significantly reduce the deviation from the set pressure (as measured by the root mean square value) while under control in the hypotension condition (p < 0.10). Though both the short-term and hypertension testing showed no significant improvement, the control system did successfully manipulate the anesthetic percentage in response to changes in MAP. Though currently limited by the control variables being used, this system is an important first step towards a fully automated monitoring and control system and can be used as the basis for further research.
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