PREDICTION AND CLOSED-LOOP CONTROL OF BLOOD PRESSURE FOR HEMORRHAGE RESUSCITATION

dc.contributor.advisorHahn, Jin-Ohen_US
dc.contributor.authorHohenhaus, Drew Xavieren_US
dc.contributor.departmentMechanical Engineeringen_US
dc.contributor.publisherDigital Repository at the University of Marylanden_US
dc.contributor.publisherUniversity of Maryland (College Park, Md.)en_US
dc.date.accessioned2023-06-23T06:15:14Z
dc.date.available2023-06-23T06:15:14Z
dc.date.issued2023en_US
dc.description.abstractHemorrhage 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 factors such as exhaustion, distraction, and inexperience of the physician, this method 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 (EKF), 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 (LMI) 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 accuracy superior to conventional assumptions. The controller tracked the given setpoint with an accuracy and performance comparable to more complex adaptive methods. 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 high-speed applications, suggesting further study is required to increase its situational flexibility.en_US
dc.identifierhttps://doi.org/10.13016/dspace/fqsh-zoz3
dc.identifier.urihttp://hdl.handle.net/1903/30046
dc.language.isoenen_US
dc.subject.pqcontrolledBiomedical engineeringen_US
dc.subject.pqcontrolledMechanical engineeringen_US
dc.subject.pquncontrolledclosed-loopen_US
dc.subject.pquncontrolledEKFen_US
dc.subject.pquncontrolledhemorrhageen_US
dc.subject.pquncontrolledpredictionen_US
dc.subject.pquncontrolledresuscitationen_US
dc.titlePREDICTION AND CLOSED-LOOP CONTROL OF BLOOD PRESSURE FOR HEMORRHAGE RESUSCITATIONen_US
dc.typeThesisen_US

Files

Original bundle
Now showing 1 - 1 of 1
Loading...
Thumbnail Image
Name:
Hohenhaus_umd_0117N_23401.pdf
Size:
2.5 MB
Format:
Adobe Portable Document Format