A Parameter Identification Approach towards Analyzing Hemodynamics Based on Capnography.

During cardiopulmonary resuscitation (CPR), end-tidal $CO_{2}$ (et $CO_{2})$ is often used as a surrogate parameter for systemic blood flow and a sudden rise in et $CO_{2}$ is regularly associated with a return of spontaneous circulation (ROSC). We model this transportation of metabolic $CO_{2}$ from the tissues via systemic perfusion to the lungs, and its exhalation through the alveoli, in a simple compartment-based ODE model. The aim is to determine a slowly time-dependent scalar describing the level of systemic perfusion based on tidal flow, airway pressure and capnography data in a multishooting parameter identification approach. We test our model on synthetically generated data as well as on data from a porcine model of cardiac arrest. In the porcine model, we compare the estimated level of systemic perfusion with invasively measured mean arterial blood pressure as a surrogate of blood flow. First experiments on both synthetic and real-world data show good identifiability for the level of systemic perfusion based on the capnography data. A validated simple ODE model for $CO_{2}$ -extraction during CPR could help to quantify the effects of tidal volumes and ventilation rates on et $CO_{2}$ and furthermore assist physicians to detect a ROSC more reliably during out-of-hospital cardiac arrest.