Design and validation of an extended Kalman filter for estimating hemodynamic variables

The paper presents an extended Kalman filter framework for the real-time estimation of hemodynamic variables. A simplified, first-order time-delayed dynamic model is considered to describe blood pressure response due to drug injection. The problem of a priori unknown and time varying model parameters are handled by state augmentation, which serves as basis of the developed a multiple-model extended Kalman filter configuration. Experimental animal study is given to validate the proposed approach, providing a valuable tool for computerized decision support of drug administration.