title: A Kalman filtering approach to estimation of maximum ventricle elastance.
abstract: In this paper a method for estimating maximum ventricular elastance through an extended Kalman filter is proposed, based on measurement of ventricular volume and aortic pressure. The Kalman filter is particularly well suited to this task, since it produces an optimal estimate (in the sense that the error is statistically minimized) given noise corrupted data. The EKF model is derived from an electrical-analog model of the left ventricle and systemic load. An observability study was a priori conducted on the model, restricted to the ejection phase, to validate the estimation procedure. The method has been evaluated with simulated data and produced good results (the estimate error was 7.14%).
authors.affiliation: Department of Electronic and Information Engineering, University of Perugia, Via G. Duranti, 93 - Perugia, Italy.
authors.forename: Benedetta
authors.initials: B
authors.lastname: Borella
authors.forename: Elena
authors.initials: E
authors.lastname: Lucchi
authors.forename: Salvatore
authors.initials: S
authors.lastname: Nicosia
authors.forename: Paolo
authors.initials: P
authors.lastname: Valigi