Journal of Medical and Biological Engineering

, Volume 39, Issue 1, pp 139–150 | Cite as

Localised Model-Based Active Controlling of Blood Flow During Chemotherapy to Prevent Nail Toxicity and Onycholysis

  • Ali Youssef
  • Maarten D’Haene
  • Jochen Vleugels
  • Guido De Bruyne
  • Jean-Marie AertsEmail author
Original Article


Chemotherapy-induced nail toxicity is a widely spread phenomenon. Cooling the patient’s hands can reduce blood flow to the fingers and consequently reducing the amount of chemical agents reaching the nails. This paper is aiming at developing a model-based controller of the finger’s skin temperatures and blood flow to reduce the risk of nail toxicity during chemotherapy. Experiments were conducted to model the dynamic response of the fingers skin temperature and blood flow using an ad hoc experimental device. The device was designed to provide a localised cooling of the fingers. The experiments were performed on a homogeneous test group of 11 middle-aged women. The fingers’ skin temperatures and blood flow were measured continuously. A second order discrete time transfer function model was suitable (R2 = 0.91 ± 0.18) in all the cases to model the dynamic responses of the fingers’ skin temperatures. The model estimation results have shown that the a- and b-parameters were varying among different test subjects and within the same subject. The resulted models were employed in designing a model-based proportional-integral-plus controller. Simulations of the closed-loop systems were performed based on the identified models for each test subject. The simulation results have shown that the designed controller is able to regulate the finger’s skin temperatures tightly about the desired level and yet, is still quite simple to implement in practice. Controlled active cooling with an online parameter estimation algorithm and continuous feedback of the patient finger temperatures is a promising solution to reduce nail toxicity during chemotherapy.


Nail-toxicity Onycholysis Chemotherapy Model-based-controlling Proportional-integral-plus (PIP) 


  1. 1.
    Nicolopoulos, J., & Howard, A. (2002). Docetaxel-induced nail dystrophy. The Australasian journal of dermatology, 43(4), 293–296.CrossRefGoogle Scholar
  2. 2.
    Roh, M. R., Cho, J. Y., & Lew, W. (2007). Docetaxel-induced onycholysis: the role of subungual hemorrhage and suppuration. Yonsei Medical Journal, 48(1), 124.CrossRefGoogle Scholar
  3. 3.
    Minisini, A. M. (2003). Taxane-induced nail changes: incidence, clinical presentation and outcome. Annals of Oncology, 14(2), 333–337.CrossRefGoogle Scholar
  4. 4.
    Scotte, F. (2005). Multicenter study of a frozen glove to prevent docetaxel-induced onycholysis and cutaneous toxicity of the hand. Journal of Clinical Oncology, 23(19), 4424–4429.CrossRefGoogle Scholar
  5. 5.
    Can, G., Aydiner, A., & Cavdar, I. (2012). Taxane-induced nail changes: predictors and efficacy of the use of frozen gloves and socks in the prevention of nail toxicity. European Journal of Oncology Nursing, 16(3), 270–275.CrossRefGoogle Scholar
  6. 6.
    Katsimbri, P., Bamias, A., & Pavlidis, N. (2000). Prevention of chemotherapy-induced alopecia using an effective scalp cooling system. European Journal of Cancer (Oxford, England : 1990), 36(6), 766–771.CrossRefGoogle Scholar
  7. 7.
    Ridderheim, M., Bjurberg, M., & Gustavsson, A. (2003). Scalp hypothermia to prevent chemotherapy-induced alopecia is effective and safe: a pilot study of a new digitized scalp-cooling system used in 74 patients. Supportive Care in Cancer, 11(6), 371–377.Google Scholar
  8. 8.
    Lewis, T. (1930). Observations upon the reactions of the vessels of the human skin to cold. Heart, 15, 177–208.Google Scholar
  9. 9.
    Tang, F., Yu, C., Li, S., Ni, K., & Wang, X. (2015). Measurement of peripheral blood flow volume with new heat transfer method. Journal of Medical and Biological Engineering, 35(5), 677–684.CrossRefGoogle Scholar
  10. 10.
    Daanen, H. A. M. (2003). Finger cold-induced vasodilation: a review. European Journal of Applied Physiology, 89(5), 411–426.CrossRefGoogle Scholar
  11. 11.
    Marzencki, M., Tavakolian, K., Chuo, Y., Hung, B., Lin, P., & Kaminska, B. (2010). Miniature wearable wireless real-time health and activity monitoring system with optimized power comsumption. Journal of Medical and Biological Engineering, 30(4), 227–235.CrossRefGoogle Scholar
  12. 12.
    Bladt, L., Clercq, J., Janssens, T., Hulle, J., Vleugels, J., Aerts, J.-M., et al. (2015). Cold-induced vasoconstriction for preventing onycholysis during cancer treatment. Extreme Physiology and Medicine, 4(Suppl 1), A60.CrossRefGoogle Scholar
  13. 13.
    Steckel, J., Goethijn, F., & De Bruyne, G. (2013). A research platform using active local cooling directed at minimizing the blood flow in human fingers. In Pervasive Computing Technologies for Healthcare (pp. 81–84). IEEE.Google Scholar
  14. 14.
    Aerts, J. M., Berckmans, D., Saevels, P., Decuypere, E., & Buyse, J. (2000). Modelling the static and dynamic responses of total heat production of broiler chickens to step changes in air temperature and light intensity. British Poultry Science, 41(5), 651–659.CrossRefGoogle Scholar
  15. 15.
    Young, P. C. (1989). In C.T. Leondes (ed), Control and Dynamic Systems: Advances in Theory and Applications. Elsevier.Google Scholar
  16. 16.
    Young, P. C. (1998). Data-based mechanistic modelling of environmental, ecological, economic and engineering systems. Environmental Modelling and Software, 13(2), 105–122.CrossRefGoogle Scholar
  17. 17.
    Youssef, A., Dekock, J., Ozcan, S. E., & Berckmans, D. (2011). Data-based approach to model the dynamic behaviour of greenhouse temperature. Acta Horticulturae (ISHS), 893, 931–938.CrossRefGoogle Scholar
  18. 18.
    Youssef, A., Exadaktylos, V., & Berckmans, D. (2014). Modelling and quantification of the thermoregulatory responses of the developing avian embryo: electrical analogies of a physiological system. Journal of Thermal Biology, 44, 14–19.CrossRefGoogle Scholar
  19. 19.
    Youssef, A., Exadaktylos, V., Ozcan, S. E., & Berckmans, D. (2011). Proportional-integral-plus (PIP) control system for individual thermal zones in a small ventilated space. ASHRAE Transactions, 117, 48–56.Google Scholar
  20. 20.
    Youssef, A., Yen, H., Özcan, S. E., & Berckmans, D. (2011). Data-based mechanistic modelling of indoor temperature distributions based on energy input. Energy and Buildings, 43(11), 2965–2972.CrossRefGoogle Scholar
  21. 21.
    Young, P. C., & Jakeman, A. (1980). Refined instrumental variable methods of recursive time-series analysis part III. Extensions. International Journal of Control, 31(4), 741–764.CrossRefzbMATHGoogle Scholar
  22. 22.
    Young, P. C. (2011). Recursive Estimation and Time-Series Analysis: An Introduction for the Student and Practitioner. Berlin: Springer.CrossRefzbMATHGoogle Scholar
  23. 23.
    Young, P. C., Chotai, A., & Tych, W. (1991). Identification, estimation and control of continuous-time systems described by delta operator models. Dordrecht: Kluwer Academic Publishers.CrossRefzbMATHGoogle Scholar
  24. 24.
    Young, P. C., Lees, M. J., Chotai, A., Tych, W., & Chalabi, Z. S. (1994). Modelling and PIP control of a glasshouse micro-climate. Control Engineering Practice, 2(4), 591–604.CrossRefGoogle Scholar
  25. 25.
    Taylor, C. J., Chotai, A., & Young, P. C. (1998). Proportional-integral-plus (PIP) control of time delay systems. Proceedings of the Institution of Mechanical Engineers, Part I: Journal of Systems and Control Engineering, 212(1), 37–48.Google Scholar
  26. 26.
    Taylor, C. J. (1998). Continuous time Proportional-Integral-Plus (PIP) control with filtering polynomials. In UKACC International Conference on Control (CONTROL’98) (Vol. 1998, pp. 1391–1396). IEEE.Google Scholar
  27. 27.
    Taylor, C. J., Young, P. C., & Chotai, A. (2013). True Digital Control: Statistical Modelling and Non-Minimal State Space Design. Chichester: Wiley.CrossRefzbMATHGoogle Scholar
  28. 28.
    Levine, D. M., Ramsey, P. P., & Smidt, R. K. (2001). Applied Statistics for Engineers and Scientists: Using Microsoft Excel and Minitab. New Jersey: Prentice Hall.zbMATHGoogle Scholar
  29. 29.
    Young, P. C., Behzadi, M. A., & Chotai, A. (1988). Self-tuning and self-adaptive PIP control systems. IET Digital Library.Google Scholar

Copyright information

© Taiwanese Society of Biomedical Engineering 2018

Authors and Affiliations

  • Ali Youssef
    • 1
  • Maarten D’Haene
    • 1
  • Jochen Vleugels
    • 2
  • Guido De Bruyne
    • 2
  • Jean-Marie Aerts
    • 1
    Email author
  1. 1.Division of Animal and Human Health Engineering (A2H), Biosystems Engineering Department, Laboratory of Measure-Model and Manage Biorespsones (M3-BIORES)KU LeuvenLeuvenBelgium
  2. 2.Department of Product DevelopmentUniversity of AntwerpAntwerpBelgium

Personalised recommendations