Estimation of cardiac function from computer analysis of the arterial pressure waveform

• Published in: IEEE transactions on biomedical engineering Vol. 45; no. 12; pp. 1420 - 1428
• Main Authors: Guarini, M., Urzua, J., Cipriano, A., Gonzalez, W.
• Format: Journal Article
• Language: English
• Published: New York, NY IEEE 01.12.1998; Institute of Electrical and Electronics Engineers
• Subjects: Algorithms; Animals; Biological and medical sciences; Blood Flow Velocity - physiology; Blood pressure; Blood Pressure - physiology; Cardiology; Cardiovascular system; Computational modeling; Computer aided diagnosis; Computer Simulation; Dogs; Fundamental and applied biological sciences. Psychology; Heart; Humans; Least squares approximation; Least squares approximations; Least-Squares Analysis; Load modeling; Models, Cardiovascular; Parameter estimation; Physiological models; Quadratic programming; Testing; Ventricular Function, Left - physiology; Vertebrates: cardiovascular system; Waveform analysis; Waveform; Human; Fissipedia; Carnivora; Parameter estimation; Functional analysis; Modeling; Vertebrata; Mammalia; Wavelet transformation; Animal; Equivalent circuit; Arterial pressure; Circulatory system; Left ventricle performance; Dog; Computer aided analysis
• ISSN: 0018-9294
• DOI: 10.1109/10.730436

This 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.