Modeling and model predictive control of hemodynamic variables during hemodialysis

Autor: James D. Mackie, Faizan Javed, Gregory S. H. Chan, Andrey V. Savkin
Rok vydání: 2010
Předmět:
Zdroj: CDC
Popis: Fluid removal during hemodialysis leads to relative hypovolemia that may cause hemodynamic instability in end-stage renal failure patients. To maintain the hemodynamic stability of patients, this paper proposes a linear parameter-varying (LPV) system based model predictive control (MPC) approach to regulate the hemodynamic variables during hemodialysis. The system uses ultrafiltration rate (UFR) as the control input and tracks the changes in relative blood volume (RBV) and percentage change in heart rate (ΔHR(%)) during hemodialysis while maintaining the UFR as well as the percentage change in systolic blood pressure (ΔSBP(%)) within certain bounds. MPC based approach is utilized to account for system variability and to explicitly handle the constraints on the control input as well as the system output. To model the hemodynamic variables, multiple LPV systems are introduced. The control algorithm tracks the changes in RBV and ΔHR to follow reference trajectories. The system parameters are updated at each control interval to get the best fitting into the parameterized model. The simulation results show that while keeping the control input as well as the output within a practically realizable bounds, the system is able to regulate RBV and ΔHR to pre-defined trajectories as well as maintaining ΔSBP within bounds by adjusting the UFR. Such systems can help to ensure the stability of patient undergoing hemodialysis by avoiding sudden change in hemodynamic variables.
Databáze: OpenAIRE