Author: Drew Hohenhaus
Title: Prediction and Closed-Loop Control of Blood Pressure for Hemorrhage Resuscitation
Date/Time: April 17th at 11:00 am
Location: EGR 2162
Committee:
Dr. Jin-Oh Hahn, Chair
Dr. Hosam Fathy
Dr. Yancy Diaz-Mercado
Abstract:
Hemorrhage is responsible for a large percentage of mortality worldwide and the majority of fatalities on the battlefield. Resuscitation procedures for hemorrhage trauma patients are critical for their recovery. Currently, during resuscitation physicians manually monitor blood pressure and use intuition to determine when fluid should be administered and how much. Due to many factors such as exhaustion, distraction, and inexperience, this method of resuscitation has often been reported as fallible. This thesis proposes two methods to assist in automating hemorrhage resuscitation. The first is a blood pressure prediction algorithm for decision support systems. The algorithm individualizes itself to different subjects using extended Kalman filtering, to account for high inter-subject variability, before accurately forecasting future blood pressure. The second method is an observer-based feedback controller which regulates blood pressure from a hypotensive state back to a healthy setpoint. The controller was designed using linear matrix inequality techniques to ensure it was absolutely stable, which let a portion of the hemodynamic plant model remain unspecified and allowed for performance over a range of physiologies. Both strategies were evaluated in-silico on a cohort of 100 virtual patients generated from an experimental dataset. The prediction algorithm showed superior accuracy to conventional assumptions. The controller tracked the given setpoint with an accuracy and performance comparable to more complex adaptive methods while outperforming empirical controllers. Further work, with respect to the prediction algorithm, includes developing it into a full decision-support system and incorporating disturbance rejecting components to account for common issues such as rebleed. The controller’s performance deteriorates for low setpoints, suggesting further study is required to increase its situational flexibility.