PPG-based Windkessel model parameter identification via unscented Kalman filtering

Abstract

Modelling of arterial system is helpful in understanding the cardiovascular system and related ailments. Among various methods, Windkessel model is one approach which plays significant role in understanding the working principle of natural arterial system. The Windkessel models describe the hydraulic properties of arterial system. In this paper, PPG-based Windkessel model has been suggested which utilises PPG signal as measurement. State dynamics of proposed model has also been developed. The main contribution of this work lies on the identification of model parameters using extended Kalman filter (EKF) and unscented Kalman filter (UKF). Estimated parameters are compared with nominal values to validate model structures. The comparative analysis has been carried out with the pre-existing method. Execution time taken to simulate the proposed model for modelling a single PPG pulse is approximately one second.