• M Guarini, J Urzúa, A Cipriano, and W González.
• Department of Electrical Engineering, Catholic University of Chile, Chile. mguarini@ing.puc.cl
• IEEE Trans Biomed Eng. 1998 Dec 1; 45 (12): 1420-8.

AbstractThis paper presents a method for estimating parameters of a cardiovascular model, including the left-ventricular function, using the sequential quadratic programming (SQP) and the least minimum square (LMS) algorithms. In a first stage, a radial arterial-pressure waveform with corresponding cardiac output are used to automatically seek the set of parameters of the diastolic model. Computer simulation of the model using these parameters generate a pressure waveform and a cardiac output very close to those used for the estimation. In a second stage, the estimated arterial load parameters are used to select the best left-ventricular model function, from four different possibilities, and to estimate its optimum parameter values. The method has been tested numerically and applied to real cases, using data obtained from cardiovascular patients. It has also been subjected to preliminary validation using data obtained from laboratory dogs, in which cardiovascular function was artificially altered.

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