Non-invasive measurements based model predictive control of pulsatile flow in an implantable rotary blood pump for heart failure patients

In this paper, firstly, we propose a linear time-variant (LTV) model to estimate the mean pulsatile flow (Q_p) in an implantable rotary blood pump (RBP). Non-invasive measurement of mean pulse-width modulation (PWM) signal acquired from the pump controller was used as an input to estimate the mean pulsatility index of pump rotational speed (PI_ω) with this subsequently used to estimate the mean Q_p. Secondly, the proposed LTV model was used to develop a controller to regulate and track the variations in the mean Q_p and PI_ω We used a model predictive control (MPC) approach to develop the controller where this allowed us to explicitly apply pre-defined practical constraints to control input PWM as well as the output and the states of the system including; Q_p and PI_ω The model and the controller were tested using a parameter optimized model of the cardiovascular system-rotary blood pump under wide ranges of speed ramp experiments carried out under different operating conditions such as variations in afterload, preload and heart contractility.