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Robustness of closed-loop glucose control systems

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Języki publikacji
EN
Abstrakty
EN
The main purpose of this work is to provide an extensive, simulation-based comparison of robustness of PID and MPC algorithms in control of blood glucose levels in patients with type 1 diabetes and thus answer the question of their safety. Cohort testing, with 1000 simulated, randomized patients allowed to analyze specific control quality indicators, such as number of hypoglycemic events, and length of hypo- and hyperglycemia periods. Results show that both algorithms provide a reasonable safety level, taking into account natural changes of patients’ physiological parameters. At the same time, we point out drawbacks of each solution, as well as general problems arising in close-loop control of blood glucose level.
Rocznik
Strony
681--705
Opis fizyczny
Bibliogr. 32 poz., rys., tab., wzory
Twórcy
  • Department of Biology and Systems Engineering, Silesian University of Technology, Gliwice, Poland
  • Department of Biology and Systems Engineering, Silesian University of Technology, Gliwice, Poland
Bibliografia
  • [1] 6. Glycemic Targets. Diabetes Care, 40 (Supplement_1), (2016), S48-S56. DOI: 10.2337/dc17-s009.
  • [2] G. Aleppo, T. Battelino, R. Bergenstal, J. Chamberlain, I. Hirsch and A. Peters: Role of Continuous Glucose Monitoring in Diabetes Treatment. American Diabetes Association, 2018.
  • [3] A.-L. Alshalalfah, G.B. Hamad and O.A. Mohamed: Towards safe and robust closed-loop artiffcial pancreas using improved PID-based control strategies. IEEE Transactions on Circuits and Systems I: Regular Papers, 68(8), (2021), 3147-3157. DOI: 10.1109/TCSI.2021.3058355.
  • [4] A. P. Belmon and J. Auxillia: An adaptive technique based blood glucose control in type-1 diabetes mellitus patients. International Journal for Numerical Methods in Biomedical Engineering, 36(8), (2020), e3371. DOI: 10.1002%2Fcnm.3371.
  • [5] A. Bemporad, M. Morari and N.L. Ricker: Model Predictive Control Toolbox™ Getting Started Guide. The MathWorks, Inc. 2015.
  • [6] R. Bergman: The minimal model: yesterday, today and tomorrow. In: R. Bergman, J. Lovejoy (eds.), The Minimal Model Approach and Determinants of Glucose Tolerance, Louisiana University Press, 1997.
  • [7] A. Bertachi, C.M. Ramkissoon, J. Bondia and J. Vehí: Automated blood glucose control in type 1 diabetes: A review of progress and challenges. Endocrinología, Diabetes y Nutrición, 65(3), (2018), 172-181. DOI: 10.1016/j.endinu.2017.10.011.
  • [8] H. Blauw, A.J. Onvlee, M. Klaassen, A.C. van Bon and J.H. DeVries: Fully closed loop glucose control with a bihormonal artificial pancreas in adults with type 1 diabetes: An outpatient, randomized, crossover trial. Diabetes Care, 44(3), (2021), 836-838. DOI: 10.2337/dc20-2106.
  • [9] C.K. Boughton and R. Hovorka: New closed-loop insulin systems. Diabetologia, 44(3), (2021), 1007-1015. DOI: 10.1007/s00125-021-05391-w.
  • [10] J.F. Brun, R. Guintrand-Hugret, C. Boegner, O. Bouix and A. Orsetti: Influence of short-term submaximal exercise on parameters of glucose assimilation analyzed with the minimal model. Metabolism, 44(7), (1995), 833-840. DOI: 10.1016/0026-0495(95)90234-1.
  • [11] P.H. Colmegna, F.D. Bianchi and R.S. Sanchez-Pena: Automatic glucose control during meals and exercise in type 1 diabetes: Proof-of-concept in silico tests using a switched LPV approach. IEEE Control Systems Letters, 5(5), (2021), 1007-1015. DOI: 10.1109/lcsys.2020.3041211.
  • [12] V.D. Funtanilla, P. Candidate, T. Caliendo and O. Hilas: Continuous glucose monitoring: A review of available systems. Pharmacy and Therapeutics, 44(9), (2019), 550-553.
  • [13] R. Gessing: Principles of Automatic Control. Wydawnictwo Politechniki Śląskiej, 2001, (in Polish).
  • [14] I.B. Hirsch: Type 1 diabetes mellitus and the use of flexible insulin regimens. American family physician, 60(8), (1990), 2343-2356.
  • [15] R. Hovorka: Closed-loop insulin delivery: from bench to clinical practice. Nature Reviews Endocrinology, 7(7), (2021), 385-395. DOI: 10.1038/nrendo.2011.32.
  • [16] V.J. Briscoe and S.N. Davis: Hypoglycemia in type 1 diabetes. In: S. Jabbour and E.A. Stephens (eds.), Type 1 Diabetes in Adults. Principles and Practice, CRC Press, 2008.
  • [17] E.D. Lehmann and T. Deutsch: A physiological model of glucose-insulin interaction in type 1 diabetes mellitus. Journal of Biomedical Engineering, 14(3), (1992), 235-242. DOI: 10.1016/0141-5425(92)90058-s.
  • [18] S.M. Lynch and B.W. Bequette: Estimation-based model predictive control of blood glucose in type I diabetics: A simulation study. In: Proceedings of the IEEE 27th Annual Northeast Bioengineering Conference, (2001). DOI: 10.1109/NEBC.2001.924729.
  • [19] D.M. Maahs, B.A. Buckingham, J.R. Castle, A. Cinar, E.R. Damiano, E. Dassau, J.H. DeVries, F.J. Doyle, S.C. Griffen, A. Haidar, L. Heinemann, R. Hovorka, T.W. Jones, C. Kollman, B. Kovatchev, B.L. Levy, R. Nimri, D.N. O’Neal, M. Philip, E. Renard, S.J. Russell, S.A. Weinzimer, H. Zisser and J.W. Lum: Outcome measures for artificial pancreas clinical trials: A consensus report. Diabetes Care, 39(7), (2016), 1175-1179. DOI: 10.2337/dc15-2716.
  • [20] L. Magni, D. M. Raimondo, C. Dalla Man, M. Breton, S. Patek, G. De Nicolao, C. Cobelli and B.P. Kovatchev: Evaluating the Efficacy of Closed-Loop Glucose Regulation via Control-Variability Grid Analysis. Journal of Diabetes Science and Technology, 2(4), (2008), 630-635. DOI: 10.1177/193229680800200414.
  • [21] G. Marchetti, M. Barolo, L. Jovanovic, H. Zisser and D.E. Seborg: An improved PID switching control strategy for type 1 diabetes. IEEE Transactions on Biomedical Engineering, 55(3), (2008), 857-865. DOI: 10.1109/tbme.2008.915665.
  • [22] B. Matejko, A. Kukułka, B. Kieć-Wilk, A. Stapór, T. Klupa and M.T. Malecki: Basal insulin dose in adults with type 1 diabetes mellitus on insulin pumps in real-life clinical practice: A single-center experience. Advances in Medicine, 2008, (2008), 1-5. DOI: 10.1155/2018/1473160.
  • [23] H.M. Paiva, W.S. Keller and L.G.R. da Cunha: Blood-glucose regulation using fractional-order PID control. Journal of Control, Automation and Electrical Systems, 31(1), (2019), 1-9. DOI: 10.1007/s40313-019-00552-0.
  • [24] R.S. Parker, F.J. Doyle and N.A. Peppas: A model-based algorithm for blood glucose control in type I diabetic patients. IEEE Transactions on Biomedical Engineering, 46(2), (1999), 148-157. DOI: 10.1109/10.740877.
  • [25] D. Radomski and J. Gowacka: Sensitivity analysis of the insulin-glucose mathematical model. In: E. Pietka, P. Badura, J. Kawa and W. Wieclawek (eds.), Information Technology in Biomedicine, Springer International Publishing, 2019. DOI: 10.1007/978-3-319-91211-0_40.
  • [26] J. Śmieja and A. Gałuszka: Rule-based PID control of blood glucose level. In: A. Świerniak and J. Krystek (eds.), Teoria i Zastosowania. T. 2, Wydawnictwo Politechniki Śląskiej, 2018.
  • [27] G.M. Steil, K. Rebrin, C. Darwin, F. Hariri and M.F. Saad: Feasibility of automating insulin delivery for the treatment of type 1 diabetes. Diabetes, 55(12), (2006), 3344-3350. DOI: 10.2337/db06-0419.
  • [28] M.F. Tabassum, M. Farman, P.A. Naik, A. Ahmad, A.S. Ahmad and S.M. Ul Hassan: Modeling and simulation of glucose insulin glucagon algorithm for artificial pancreas to control the diabetes mellitus. Network Modeling Analysis in Health Informatics and Bioinformatics, 10(1), (2021). DOI: 10.1007/s13721-021-00316-4.
  • [29] N. Taleb, A. Emami, C. Suppere, V. Messier, L. Legault, M. Ladouceur, J.-L. Chiasson, A. Haidar and R. Rabasa-Lhoret: Efficacy of single-hormone and dual-hormone artificial pancreas during continuous and interval exercise in adult patients with type 1 diabetes: Randomised controlled crossover trial. Diabetologia, 59(12), (2016), 2561-2571. DOI: 10.1007/s00125-016-4107-0.
  • [30] Guidelines on second- and third-line medicines and type of insulin for the control of blood glucose levels in non-pregnant adults with diabetes mellitus. World Health Organization, 2018.
  • [31] Global Report on Diabetes. World Health Organization, 2016.
  • [32] S. Zavitsanou, A. Mantalaris, M.C. Georgiadis and E.N. Pistikopoulos: In silico closed-loop control validation studies for optimal insulin delivery in type 1 diabetes. IEEE Transactions on Biomedical Engineering, 62(10), (2015), 2369-2378. DOI: 10.1109/tbme.2015.2427991.
Typ dokumentu
Bibliografia
Identyfikator YADDA
bwmeta1.element.baztech-008b87e3-bbfa-4568-a652-4258ac7ef030
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