Integral-based identification of patient specific parameters for a minimal cardiac model (2006)
Type of ContentJournal Article
PublisherUniversity of Canterbury. Mechanical Engineering.
A minimal cardiac model has been developed which accurately captures the essential dynamics of the cardiovascular system (CVS). However, identifying patient specific parameters with the limited measurements often available, hinders the clinical application of the model for diagnosis and therapy selection. This paper presents an integral based parameter identification method for fast, accurate identification of patient specific parameters using limited measured data. The integral method turns a previously non-linear and non-convex optimization problem into a linear and convex identification problem. The model includes ventricular interaction and physiological valve dynamics. A healthy human state and two disease states, Valvular Stenosis and Pulmonary Embolism, are used to test the method. Parameters for the healthy and disease states are accurately identified using only discretized flows into and out of the two cardiac chambers, the minimum and maximum volumes of the left and right ventricles, and the pressure waveforms through the aorta and pulmonary artery. These input values can be readily obtained non-invasively using echo-cardiography and ultra-sound, or invasively via catheters that are often used in Intensive Care. The method enables rapid identification of model parameters to match a particular patient condition in clinical real time (3-5 minutes) to within a mean value of 4 – 8% in the presence of 5 – 15% uniformly distributed measurement noise. The specific changes made to simulate each disease state are correctly identified in each case to within 5% without false identification of any other patient specific parameters. Clinically, the resulting patient specific model can then be used to assist medical staff in understanding, diagnosis and treatment selection.
CitationHann, C.E., Chase, J.G., Shaw, G.M. (2006) Integral-based identification of patient specific parameters for a minimal cardiac model. Computer Methods and Programs in Biomedicine, 81(2), pp. 181-192.
This citation is automatically generated and may be unreliable. Use as a guide only.
Showing items related by title, author, creator and subject.
Hann, C.E.; Chase, Geoff; Shaw, Geoff; Smith, B.W. (University of Canterbury. Mechanical Engineering., 2004)A minimal cardiac model has been developed which accurately captures the essential dynamics of the cardio-vascular system (CVS). This paper develops an integral based parameter identification method for fast and accurate ...
Integral-based parameter identification for long-term dynamic verification of a glucose-insulin system model Hann, C.E.; Chase, Geoff; Lin, J.; Lotz, T.; Doran, C.V.; Shaw, Geoff (University of Canterbury. Mechanical Engineering., 2005)Hyperglycaemia in critically ill patients increases the risk of further complications and mortality. This paper introduces a model capable of capturing the essential glucose and insulin kinetics in patients from retrospective ...
Hann, C.E.; Revie, J.; Stevenson, D.; Heldmann, S.; Desaive, T.; Froissart, C.B.; Lambermont, B.; Ghuysen, A.; Kolh, P.; Shaw, Geoff; Chase, Geoff (University of Canterbury. Electrical and Computer EngineeringUniversity of Canterbury. Mechanical Engineering, 2011)The cardiac muscle activation or driver function, is a major determinant of cardiovascular dynamics, and is often approximated by the ratio of the left ventricle pressure to the left ventricle volume. In an intensive care ...