| Description |
Biomedical engineering has advanced technology and improved patient care but alone is not specific enough to personalize medicine. These technological advances can only deliver individualized therapy by combining engineering with mathematical modeling and scientific computation. Preparing a mathematical model for clinical use is an extensive process, and various factors must be considered. These factors include the difficulty of obtaining measurements, appropriate complexity of the model, and the efficacy of using the model clinically. Also, any instrumentation developed during the process must be validated. This work's primary objective is to provide instrumentation, methods, understanding, and efficacy for a mathematical model of oxygenation and gas transport. Three phases of research were required to accomplish the components of this objective. This work conducted three phases of research to prepare the mathematical model for clinical use. These phases included developing and evaluating lesscostly methods for measuring exhaled oxygen and carbon dioxide, determining the most rewarding model parameters to measure, and demonstrating the clinical efficacy of modeling patient-specific oxygen saturation response. Modeling saturation response required designing an automated oxygen system which was validated clinically. This work has shown that error is clinically insignificant when measuring exhaled oxygen and carbon dioxide using the less-costly methods developed here. It has also shown that when determining saturation response measuring the concentration of hydrogen ions in the blood is most rewarding while measuring 2,3- diphosphoglycerate is not useful. Determining best-fit model parameters improves the model fit of saturation response significantly. The instrumentation designed here provided all of these benefits without sacrificing oxygen therapy capability. In conclusion, this work has made significant progress toward individualizing oxygen therapy. These advances include less-costly measurement, reduced model complexity, and proven clinical efficacy and were made without sacrificing the quality of oxygen therapy. This progress has identified future areas of research which, when accomplished, may lead to basing clinical decision-making on subject-specific oxygen saturation response and to administering individualized oxygen therapy to patients in a clinical setting. |
