Medical & Biological Engineering & Computing

, Volume 48, Issue 4, pp 389–397 | Cite as

Model predictive control of relative blood volume and heart rate during hemodialysis

  • Faizan JavedEmail author
  • Andrey V. Savkin
  • Gregory S. H. Chan
  • Paul M. Middleton
  • Philip Malouf
  • Elizabeth Steel
  • James Mackie
  • Teddy M. Cheng
Original Article


To maintain the hemodynamic stability of patient undergoing hemodialysis, this article proposes a novel model-based control methodology to regulate the changes in relative blood volume (RBV) and percentage change in heart rate (∆HR(%)) during hemodialysis by adjusting the ultrafiltration rate (UFR). The control algorithm uses model predictive control (MPC) to account for system variability and to explicitly handle the constraints on UFR. Linear state-space system with time-varying parameters is introduced to model the RBV and ∆HR. MPC was used to track the change in RBV and ∆HR to pre-defined reference trajectories. At each sampling instant, the system parameters are updated to get the best fitting into the parameterized model. Simulation results demonstrate that the system is able to regulate RBV and ∆HR to the reference by adjusting UFR while keeping it within practically realizable bounds. The results show that adjusting UFR may improve the stability of patient during dialysis when compared to conventional hemodialysis with constant UFR.


Model predictive control Hemodialysis System identification 



We wish to thank the staff at the Renal Dialysis Unit, Prince of Wales Hospital, Sydney for their permission to conduct this research at their unit and assistance with the collection of data.


  1. 1.
    Andrulli S, Colzani S, Mascia F, Lucchi L, Stipo L, Bigi MC, Crepaldi M, Redaelli B, Albertazzi A, Locatelli F (2002) The role of blood volume reduction in the genesis of intradialytic hypotension. Am J Kidney Dis 40(6):1244–1254CrossRefGoogle Scholar
  2. 2.
    Barbieri R, Triedman JK, Saul JP (2002) Heart rate control and mechanical cardiopulmonary coupling to assess central volume: a systems analysis. Am J Physiol Regul Integr Comp Physiol 283(5):R1210–R1220Google Scholar
  3. 3.
    Barth C, Boer W, Garzoni D, Kuenzi T, Ries W, Schaefer R, Schneditz D, Tsobanelis T, van der Sande F, Wojke R, Schilling H, Passlick-Deetjen J (2003) Characteristics of hypotension-prone haemodialysis patients: is there a critical relative blood volume? Nephrol Dial Transplant 18(7):1353–1360CrossRefGoogle Scholar
  4. 4.
    Cheng TM, Savkin AV, Celler BG, Su SW, Wang L (2008) Nonlinear modeling and control of human heart rate response during exercise with various work load intensities. IEEE Trans Biomed Eng 55(11):2499–2508CrossRefGoogle Scholar
  5. 5.
    Cheryan M (1998) Ultrafiltration and microfiltration handbook. Technomic Publishing Co., Lancaster, pp 305–307Google Scholar
  6. 6.
    Converse RLJ, Jacobsen TN, Jost CM, Toto RD, Grayburn PA, Obregon TM, Fouad-Tarazi F, Victor RG (1992) Paradoxical withdrawal of reflex vasoconstriction as a cause of hemodialysis-induced hypotension. J Clin Invest 90(5):1657–1665CrossRefGoogle Scholar
  7. 7.
    Dasselaar JJ, Huisman RM, De Jong PE, Franssen CF (2007) Relative blood volume measurements during hemodialysis: comparisons between three noninvasive devices. Hemodial Int 11(4):448–455CrossRefGoogle Scholar
  8. 8.
    Dasselaar JJ, Lub-de Hooge MN, Pruim J, Nijnuis H, Wiersum A, de Jong PE, Huisman RM, Franssen CF (2007) Relative blood volume changes underestimate total blood volume changes during hemodialysis. Clin J Am Soc Nephrol 2(4):669–674CrossRefGoogle Scholar
  9. 9.
    DeCarlo R, Meirina C (2000) Parameter identification and adaptive control of an ultrafiltration process in hemodialysis. In: Proceedings of the 2000 American control conference, vol 5, pp 2967–2971Google Scholar
  10. 10.
    Franssen CF, Dasselaar JJ, Sytsma P, Burgerhof JG, de Jong PE, Huisman RM (2005) Automatic feedback control of relative blood volume changes during hemodialysis improves blood pressure stability during and after dialysis. Hemodial Int 9(4):383–392CrossRefGoogle Scholar
  11. 11.
    Goodwin GC, Graebe SF, Salgado ME (2001) Control system design. Prentice Hall, Upper Saddle River, pp 739–765Google Scholar
  12. 12.
    Ishihara T, Igarashi I, Kitano T, Shinzato T, Maeda K (1993) Continuous hematocrit monitoring method in an extracorporeal circulation system and its application for automatic control of blood volume during artificial kidney treatment. Artif Organs 17(8):708–716Google Scholar
  13. 13.
    Javed F, Savkin AV, Chan GSH, Middleton PM, Malouf P, Steel E, Mackie JD, Lovell NH (2009) Assessing the blood volume and heart rate responses during haemodialysis in fluid overloaded patients using support vector regression. Physiol Meas 30:1251–1266CrossRefGoogle Scholar
  14. 14.
    Kitamura M (2000) Application of automatic ultrafiltration controller with blood monitor for home hemodialysis patients. J Artif Organs 3:117–119CrossRefGoogle Scholar
  15. 15.
    Maciejowski JM (2002) Predictive control with constraints. Prentice Hall, Upper Saddle RiverGoogle Scholar
  16. 16.
    Mancini E, Santoro A, Spongano M, Paolini F, Rossi M, Zucchelli P (1993) Continuous on-line optical absorbance recording of blood volume changes during hemodialysis. Artif Organs 17(8):691–694CrossRefGoogle Scholar
  17. 17.
    Mancini E, Mambelli E, Irpinia M, Gabrielli D, Cascone C, Conte F, Meneghel G, Cavatorta F, Antonelli A, Villa G, Dal Canton A, Cagnoli L, Aucella F, Fiorini F, Gaggiotti E, Triolo G, Nuzzo V, Santoro A (2007) Prevention of dialysis hypotension episodes using fuzzy logic control system. Nephrol Dial Transplant 22(5):1420–1427CrossRefGoogle Scholar
  18. 18.
    Moissl U, Wabel P, Isermann R (2001) Model-based control of hemodialysis. Proceedings of the 2001 American control conference, vol 5, pp 3809–3810Google Scholar
  19. 19.
    Paolini F, Mancini E, Bosetto A, Santoro A (1995) Hemoscan: a dialysis machine-integrated blood volume monitor. Int J Artif Organs 18(9):487–494Google Scholar
  20. 20.
    Pelosi G, Emdin M, Carpeggiani C, Morales MA, Piacenti M, Dattolo P, Cerrai T, Macerata A, L’Abbate A, Maggiore Q (1999) Impaired sympathetic response before intradialytic hypotension: a study based on spectral analysis of heart rate and pressure variability. Clin Sci 96(1):23–31CrossRefGoogle Scholar
  21. 21.
    Petersen IR, Savkin AV (1999) Robust Kalman filtering for signals and systems with large uncertainties. Birkhäuser, BostonGoogle Scholar
  22. 22.
    Rao RR, Aufderheide B, Bequette BW (2003) Experimental studies on multiple-model predictive control for automated regulation of hemodynamic variables. IEEE Trans Biomed Eng 50(3):277–288CrossRefGoogle Scholar
  23. 23.
    Saitoh T, Ogawa Y, Aoki K, Shibata S, Otsubo A, Kato J, Iwasaki K (2008) Bell-shaped relationship between central blood volume and spontaneous baroreflex function. Auton Neurosci 143(1–2):46–52CrossRefGoogle Scholar
  24. 24.
    Santoro A, Mancini E, Paolini F, Cavicchioli G, Bosetto A, Zucchelli P (1998) Blood volume regulation during hemodialysis. Am J Kidney Dis 32(5):739–748CrossRefGoogle Scholar
  25. 25.
    Schmidt R, Roeher O, Hickstein S, Korth S (2001) Blood pressure guided profiling of ultrafiltration during hemodialysis. Saudi J Kidney Dis Transpl 12(3):337–344Google Scholar
  26. 26.
    Su SW, Wang L, Celler BG, Savkin AV, Guo Y (2007) Identification and control for heart rate regulation during treadmill exercise. IEEE Trans Biomed Eng 54(7):1238–1246CrossRefGoogle Scholar
  27. 27.
    Task Force of the European Society of Cardiology and the North American Society of Pacing Electrophysiology (1996) Heart rate variability: standards of measurement, physiological interpretation and clinical use. Eur Heart J 17(3):354–381Google Scholar

Copyright information

© International Federation for Medical and Biological Engineering 2010

Authors and Affiliations

  • Faizan Javed
    • 1
    Email author
  • Andrey V. Savkin
    • 1
  • Gregory S. H. Chan
    • 1
  • Paul M. Middleton
    • 2
  • Philip Malouf
    • 2
  • Elizabeth Steel
    • 2
  • James Mackie
    • 2
  • Teddy M. Cheng
    • 1
  1. 1.School of Electrical Engineering and TelecommunicationsThe University of New South WalesSydneyAustralia
  2. 2.Prince of Wales Hospital SydneyRandwickAustralia

Personalised recommendations