Page 77 - Glucose Monitoring Devices
P. 77

References     75




                  [55] Freckmann G, Schmid C, Baumstark A, Rutschmann M, Haug C, Heinemann L.
                      Analytical performance requirements for systems for self-monitoring of blood glucose
                      with focus on system accuracy: relevant differences among ISO 15197:2003, ISO
                      15197:2013, and current FDA recommendations. Journal of Diabetes Science and Tech-
                      nology 2015;9(4):885e94.
                  [56] Parkes JL, Slatin SL, Pardo S, Ginsberg BH. A new consensus error grid to evaluate the
                      clinical significance of inaccuracies in the measurement of blood glucose. Diabetes
                      Care 2000;23(8):1143e8.
                  [57] Raine ICH, Pardo S, Parkes JL. Predicted blood glucose from insulin administration
                      based on values from miscoded glucose meters. Journal of Diabetes Science and Tech-
                      nology 2008;2(4):557e62.
                  [58] Kollman C, Wilson DM, Wysocki T, Tamborlane WV, Beck RW. Limitations of statis-
                      tical measures of error in assessing the accuracy of continuous glucose sensors. Dia-
                      betes Technology and Therapeutics 2005;7(5):665e72.
                  [59] Bergman RN. Toward physiological understanding of glucose tolerance: minimal-
                      model approach. Diabetes 1989;38(12):1512e27.
                  [60] Cobelli C, Man CD, Pedersen MG, Bertoldo A, Toffolo G. Advancing our understand-
                      ing of the glucose system via modeling: a perspective. IEEE Transactions on Biomed-
                      ical Engineering May 2014;61(5):1577e92.
                  [61] Man CD, Camilleri M, Cobelli C. A system model of oral glucose absorption: validation
                      on gold standard data. IEEE Transactions on Biomedical Engineering December, 2006;
                      53(12):2472e8.
                  [62] Dobbins RL, Davis SN, Neal DW, Cobelli C, Jaspan J, Cherrington AD. Compartmental
                      modeling of glucagon kinetics in the conscious dog. Metabolism 1995;44(4):452e9.
                  [63] Nucci G, Cobelli C. Models of subcutaneous insulin kinetics. A critical review. Com-
                      puter Methods and Programs in Biomedicine 2000;62(3):249e57.
                  [64] Lv D, Breton MD, Farhy LS. Pharmacokinetics modeling of exogenous glucagon in
                      type 1 diabetes mellitus patients. Diabetes Technology and Therapeutics 2013;
                      15(11):935e41.
                  [65] Lv D, et al. Pharmacokinetic model of the transport of fast-acting insulin from the sub-
                      cutaneous and intradermal spaces to blood. Journal of Diabetes Science and Technology
                      2015;9(4):831e40.
                  [66] Visentin R, et al. Improving efficacy of inhaled technosphere insulin (Afrezza) by post-
                      meal dosing: in-silico clinical trial with the University of Virginia/Padova type 1 dia-
                      betes simulator. Diabetes Technology and Therapeutics 2016;18(9):574e85.
                  [67] Dalla Man C, Rizza R, Cobelli C. Meal simulation model of the glucose-insulin system.
                      IEEE Transactions on Bio-Medical Engineering Nov. 2007;54:1740e9.
                  [68] Man CD, Micheletto F, Lv D, Breton M, Kovatchev B, Cobelli C. The UVA/PADOVA
                      type 1 diabetes simulator: new features. Journal of Diabetes Science and Technology
                      2014;8(1):26e34.
                  [69] Visentin R, et al. The UVA/PADOVA type 1 diabetes simulator goes from single meal to
                      single day. Journal of Diabetes Science and Technology 2018;12(2):273e81.
                  [70] Wilinska ME, Chassin LJ, Acerini CL, Allen JM, Dunger DB, Hovorka R. Simulation
                      environment to evaluate closed-loop insulin delivery systems in type 1 diabetes. Journal
                      of Diabetes Science and Technology 2010;4(1):132e44.
                  [71] Magni L, et al. Model predictive control of type 1 diabetes: an in silico trial. Journal of
                      Diabetes Science and Technology 2007;1(6):804e12.
   72   73   74   75   76   77   78   79   80   81   82