Improving model-based cardiac diagnosis with an ECG

Abstract

A method for improving the model-based diagnostic capability of an existing and clinically validated cardiovascular system model is developed. The improvement is based on the addition of an ECG to obtain diastolic and systolic timing. This extra data constrains the model generated left and right ventricular volume waveforms, and is shown to remove the need for invasive maximum and minimum volume measurements. The model and methods are clinically validated on a porcine model of pulmonary embolism. All errors in the matching of the clinical data are within 8% including the left ventricular pressure which was not used in the parameter identification procedure. When the maximum and minimum volumes were removed from the porcine data set, the identified parameters changed by at most 17% with the majority of errors less than 10%. These results show the clinical potential of adding an ECG to reduce the data set and improve model-based diagnosis in an Intensive Care Unit.Keywordsmodel-based cardiac diagnosiscardiovascular systemintegral-based parameter identificationECGIntensive Care Unit