第一型糖尿病患者必須依賴外加長效胰島素來控制基本的血糖的濃度，再配合短效胰島素來控制病患進食後所造成的高血糖現象，以維持生命，因此血糖控制對於此類型的病患是相當重要的。

最近在血糖監測硬體方面已經有連續式血糖偵測器 (CGMS) ，提供更為詳盡的病患血糖監測資料；本研究以連續式血糖偵測器 (CGMS) 為工具探討此類型病患體內血糖的動態模式、血糖控制的方式以及血糖的預測。

第一部份透過連續式血糖偵測器 (CGMS) 紀錄病人的血糖連續變化，針對陳永論 (2007) 所提出的第一型糖尿病增補模式，透過四位病患的臨床紀錄數據來建立屬於各個病患的血糖動態模式參數。在確定病人的模式參數後，即可透過增補Hovorka 模式得到長效胰島素的用量與基本血糖值的關係。

第二部份提供兩種短效胰島素的用藥策略給醫生作為用藥參考，第一種為陳永論 (2007) 所提出的用藥策略：短效胰島素加上長效胰島素的注射，並配合血糖上限及下限的規範來控制血糖；第二種為短效胰島素加上長效胰島素的注射，並配合用餐後六小時的平均血糖值與血糖下限的規範來控制血糖。本研究將比較兩種用藥策略下，體內血糖的變化，並討論其優劣。

第三部份利用四套不同的類神經網路架構與兩種不同訓練類神經網路的方法 (Direct Model and Indirect Model) ，探討何種架構與訓練方法可以準確的預測病患的血糖值。

Type 1 diabetes mellitus must live on exogenous long efficacy insulin for control of basal blood glucose and short acting insulin for control of high blood glucose after meal. It is important for control of blood glucose for type Ⅰ diabetes mellitus.

Recently, there is a continuous glucose monitoring system (CGMS) for blood monitor. In this research, modeling the blood glucose using the clinical data of a type Ⅰ patient from CGMS, control the blood glucose, and predicting the blood glucose are studied.

First part is using CGMS to record continuous blood glucose variation.
To build four patients model of blood glucose by an extended model for type Ⅰ diabetes mellitus which is published by Chen (2007). After development of the model, this model is used to simulate the relation between long efficacy insulin and basal blood glucose.

Second part is supply to the doctor two strategies of the dosage plan for short acting insulin. One strategy is published by Chen (2007) using long acting insulin and short acting insulin to match up the upper and low limit to control the blood glucose. The second one is using long acting insulin and short acting insulin to match up the average blood glucose value in six hours after the meal and the low limit to control the blood glucose. In this research, comparison of these two strategies in terms of blood glucose is made.

The last part is using four different artificial neural networks (ANN) structures and two different ways (direct model and indirect model) of training artificial neural networks to predict the blood glucose value after thirty minutes when the patient takes the meal. Then discussion will be made on which method to obtain the ANN model can predict to all value of blood glucose.

[中文]
【1】 黃俊銘「數值方法─使用MATLAB程式語言」全華科技圖書有限公司 (2003)
【2】 洪維恩「Matlab 7 程式設計」旗標出版股份有限公司 (2005)
【3】 羅華強「類神經網路─MATLAB的應用」高立圖書有限公司 (2008)
【4】 陳永論「第一型糖尿病之血糖動態模式與胰島素用藥策略的研究」國立台灣大學化學工程研究所 (2007)
【5】 羅啟豪「含不確定性之程序最適化探討」私立東海大學化學工程研究所 (2006)

[英文]
【1】 A. Ackerman, C. Gatewood, J. W. Rosevear, and G. D. Molnar, “Model studies of blood glucose regulation” Bull. Math. Biophys., vol.27, pp. 21-37, 1965.
【2】 A. Albisser. “An artificial endocrine pancreas “, Diabetes, vol.23, pp.389-404, 1974.
【3】 R. Bellazzi, G. Nucci, and C. Cobelli, “The subcutaneous route to insulin - dependent diabetes therapy” IEEE Eng. Med. Biol. Mag, vol.20(1) pp.54~64, 102, 2001.
【4】 R. N. Bergman, C. R. Bowden, and C. Cobelli,” The minimal model approach to quanti-cation of factors controlling glucose disposal in man ”in: C. Cobelli, R. N. Bergman (Eds.), Carbohydrate Metabolism, John Wiley & Sons Ltd., 103 Ch. 13, pp. 269-293, 1981.

【5】 R. N. Bergman, Finegood, D.T., and Ader, M.,” Assessment of insulin sensitivity in vivo ” . Endocr. Rev. vol.6, 45–86, 1985.
【6】 R. N. Bergman, Finegood, D.T., Kahn, S.E., “The evolution of betacell dysfunction and insulin resistance in type 2 diabetes” Eur. J. Clin. Invest. vol. 32 (Suppl. 3), pp.35–45, 2002.
【7】 R. N. Bergman, “ Pathogenesis and prediction of diabetes mellitus: lessons from integrative physiology “. Irving L. Schwartz Lecture, Mount Sinai J. Med. Vol.60, pp.280–290, 2002.
【8】 B. Candas and J. Radziuk, “An adaptive plasma glucose controller based on a nonlinear insulin/glucose model”, IEEE Trans Biomed Eng. vol.41(2), pp.116-24, 1994.
【9】 J.F. Casanova Domingo, R. Ruiz, F. Aldana, and M. Serrano-Rios, “Adaptation drift suppression in blood glucose self-tuning control＂, Artif Organs, Apr, 21(4), 272-277, 1991.
【10】 F. Chiarelli, S. Tumini, G. Morgese, and A.M. Albisser,“Controlled study in diabetic children comparing insulin-dosage adjustment by manual and computer algorithms” , Diabetes Care. Oct, vol.13(10), pp.1080-1084, 1990.
【11】 A. H. Clements, P. H. Chang, and R.W. Meyer, “The development of biostator, a glucose controlled insulin infusion system”, Horm. Metab. Res. vol. 9, pp.23-33, 1977.
【12】 C. Cobelli, A. Caumo, P. Vicini, J.Z. Jeffrey, A. Angelo, Y. Kevin, and M. B. Dennis” Undermodeling affects minimal model indexes: insights from a two-compartment model” Am J Physiol Endocrinol Metab.vol. 276, pp.1171-1193, 1999.

【13】 C. Cobelli, G. Pacini, G. Toffolo, and L. Sacca “Estimation of insulin sensitivity and glucose clearance from minimal model: new insights from labeled IVGTT” Am J Physiol Endocrinol Metab, pp.E591~E598, 1986.
【14】 Diwekar U.M., Introduction to applied Optimization, Springer, 2003.
【15】 Diwekar U.M., “A Novel Sampling Approach to Combinatorial Opti,ization under Uncertainty,” Comput’l Optim % Appl., 24(2-3), 335, 2003.
【16】 Frank Doyle, Lois Jovanovic, Dale Seborg,” Glucose control strategies for treating type 1 diabetes mellitus,” Journal of Process Control, vol. 17, pp.571-594, 2007.
【17】 Siti Farhanah Bt Jaafar and Dannawaty Mohd Ali, ” Diabetes Mellitus Forecast Using Artificial Neural Network (ANN)” 2005 Asian Conference on 5-7 Page(s):135 – 139, 2005.
【18】 M. E. Fisher, “A semiclosed-loop algorithm for the control of blood glucose levels in diabetics＂, IEEE Trans Biomed Eng. Jan, vol.38(1),pp.57-61, 1991.
【19】 L.C. Gatewood, Ackerman E., J. W. Rosevear,, G. D. Molnar, “Test of Mathematical model of the blood-glucose regulatory system”, Comput. Biol. Med., vol.2, pp. 1-14, 1968.
【20】 L.C. Gatewood, Ackerman E., J. W. Rosevear, and G. D. Molnar, ” Simulation studies of blood-glucose regulation: Effect of intestinal glucose absorption”. Comput. Biol. Med., vol.2, pp.15-27, 1968.
【21】 F. Pier Giorgio, C. Valentina, F. Marco Orsini, B. Massimo Massi, and S. Eugenio,” Control oriented model of insulin and glucose dynamics in type 1 diabetics,” Medical and Biological Engineering and Computing, vol. 44, n 1-2, pp. 69-78, 2006

【22】 T. E. Guttinger and M. Morari, “Predicting Multiple Steady States in Equilibrium Reactive Distillation. 1. Analysis of Nonhybrid Systems.” Ind. Eng. Chem. Res., vol.38(4), pp.1633, 1999.
【23】 Moira Harrison, Amer Siddiq, Anna Guildford, Adrian Bone, and Matteo Santin” Stent material surface and glucose activate mononuclear cells of control, type 1 and type 2 diabetes subjects” Wiley InterScience, 2007.
【24】 Roman Hovorka, F. Shojee-Moradie, P.V. Carroll,” Partitioning glucose distribution/transport, disposal ,and endogenous production during IVGTT ”Am J Physiol Endocrinol Metab, vol.282, pp.992-1007, 2002.
【25】 R. Hovorka, L. J. Chassin, M. E. Wilinska, V. Canonico, J. A. Akwi, M. O. Federici, M. Massi-Benedetti, I. Hutzli, C. Zaugg, H. Kaufmann, M. Both, T. Vering, H. C. Schaller, L. Schaupp, M. Bodenlenz, and T. R. Pieber, “Closing the loop: the ADICOL experience” Diabetes Technol Ther vol.6(3), pp.307-318, 2004.
【26】 Roman Hovorka, Valentina Canonico, Ludovic J Chassin, Ulrich Haueter, Massimo Massi-Benedetti, Marco Orsini Federici, Thomas R Pieber, Helga C Schaller, Lukas Schaupp, Thomas Vering, and Malgorzata EWilinska,” Nonlinear model predictive control of glucose concentration in subjects with type 1 diabetes” Physiol. Meas.vol.25, pp.905–920, 2004.
【27】 Roman Hovorka, “Management of diabetes using adaptive control” Int. J. Adapt. Control Signal Process. vol.9(5), pp.309~325, 2005.
【28】 Roman Hovorka,”Continuous glucose monitoring and closed-loop systems ” Diabete Med. vol.23, pp.1-12, 2006.
【29】 S. Kan, H. Onodera, E. Furutani, T. Aung, M. Araki, H. Nishimura, S. Maetani, and 101 M. Imamura., ”Novel control system for blood glucose using a model predictive method”, ASAIO J. Nov-Dec, vol.46(6), pp.657-62, 2000.

【30】 K.H. Kienitz, and T. Yoneyama,“A robust controller for insulin pumps based on H-infinity theory＂, IEEE Trans Biomed Eng. vol.40(11), pp.1133 ,1993.
【31】 S.Kirkpatrick, C. Gelatt, and M. Vecchi, “Optimization by Simulated Annealing,” Science, 220(4598), 671, 1983
【32】 Jiaxu Li, Yang Kuang, and Clinton C. Mason,” Modeling the glucose–insulin regulatory system and ultradian insulin secretory oscillations with two explicit time delays” Journal of Theoretical Biology, vol.242, pp.722–735, 2006.
【33】 S. M. Lynch and B. W. Bequette, “ Model predictive control of blood glucose in type I diabetics using subcutaneous glucose measurements ” Proceedings of the American Control Conference, pp. 4039-4043, 2002.
【34】 A. Makroglou, Jiaxu Li, and Yang Kuang” Mathematical models and software tools for the glucose-insulin regulatory system and diabetes: an overview＂Applied Numerical Mathematics vol. 56, pp. 559–573, 2006.
【35】 E. W. Malgorzata, J. C. Ludovic, C. S. Helga, S. Lukas, R.P. Thomas, and R. Hovorka;” Insulin Kinetics in Type-1 Diabetes: Continuous and Bolus Delivery of Rapid Acting Insulin” IEEE. Trans. On Biomedical Enginering, vol.52, No.1, January, 2005.
【36】 Chiara Dalla Man, Robert A. Rizza, and Claudio Cobelli.” Meal Simulation Model of the Glucose-Insulin System ” IEEE vol. 54, NO. 10, 2007
【37】 Gianni Marchetti, Massimiliano Barolo, Lois Jovanovic, Howard Zisser, Dale E. Seborg,” A feedforward–feedback glucose control strategy for type 1 diabetes mellitus” Journal of Process Control vol.18, pp149–162, 2008.

【38】 Gianni Marchetti, Massimiliano Barolo, Lois Jovanovic, Howard Zisser, and Dale E. Seborg,” An Improved PID Switching Control Strategy for Type 1 Diabetes” IEEE TRANSACTIONS ON BIOMEDICAL ENGINEERING, vol. 55, NO. 3, 2008.
【39】 G. Marchetti, M. Barolo, L. Jovanovic, H. Zisser, and Dale E. Seborg, “An Improved PID Switching Control Strategy for Type-1 Diabetes” IEEE EMBS Annual Int. Conf, 2006.
【40】 E. F. Michael and L. T. Kok, “Optimal insulin infusion resulting from a mathematical model of blood glucose dynamics” IEEE. Trans. On Biomedical Enginering, vol. 36, no.4, pp.479-486, 1989.
【41】 Nilam, Murray E. Alexander, Ruchi Mathur, Seyed M. Moghadas,and Pappur N. Shivakumar” Modelling the effect of CSII on the control of glucose concentration in type 1 diabetes” Applied Mathematics and Computation, vol.187, pp.1476–1483, 2007
【42】 Camelia Owens, Howard Zisser, Lois Jovanovic, Bala Srinivasan, Dominque, and Francis J. Doyle III,” Run-to-Run Control of Blood Glucose Concentrations for People With Type 1 Diabetes Mellitus,” IEEE Transctions on Biomedical Engineering, vol 35, 2006.
【43】 Painton, L.A. and U.M. Diwekar, “Synthwsizing Optimal Design Configuration for a Brayton Cycle Power Plant,” Comput. Chem. Eng., 18(5), 369, 1994.
【44】 Painton, L.A. and U.M. Diwekar, “Stochatic annealing for Synthesis under Uncertainty,” Euro. J. Oper. Res., 83(14), 489, 1995.
【45】 R. S. Parker, F. J. Doyle, and III, N. A. Peppas, “ A model-based algorithm for blood glucose control in type I diabetic patients ” IEEE Trans. Biomed. Eng. vol.46 (2), pp.148-157, 1999.

【46】 R. S. Parker, F. J. Doyle III, and N. A. Peppas, “The intravenous route to blood glucose control” IEEE Eng. Med. Biol. Mag. vol.20 (1), pp.65~73, 2001.
【47】 P. Palazzo and V. Viti, ＂ A new glucose-clamp algorithm—theoretical considerations and computer simulations,＂IEEE Trans Biomed Eng, vol.37(5), pp.535-543, 1990..
【48】 Cesar C. Palerm, Howard Zisser, Lois Jovanovic, and Francis J. Doyle III,” A run-to-run control strategy to adjust basal insulin infusion rates in type 1 diabetes” Journal of Process Control vol.18,pp 258–265, 2008.
【49】 Rebrin K, Fischer U, von Woedtke T, Abel P, Brunstein E., “Automated feedback control of subcutaneous glucose concentration in diabetic dogs”, Diabetologia., vol 32(8), pp.573-576, 1989.
【50】 T.F. Pfeiffer, C. Thum, and A.H. Clements, “The artificial beta cell—a continuous control of blood sugar be external regulation of insulin infusion”, Horm. Metab. Res. vol.6, pp. 339-342, 1974.
【51】 G..P. Reboldi, P.D. Home, G.. Calabrese, P.G. Fabietti, Brunetti, P. Massi. M. Benedetti., “Time delay compensation for closed-loop insulin delivery systems: a simulation study＂, Int J Artif Organs. Jun, vol.14(6), pp.350-358, 1991.
【52】 G. Schlotthauer, G.A. Nicolini, L.G. Gamero, M.E. Torres,” Type-1 Diabetes: Modeling, Identification, Non-linear model predict control” IEEE Trans Biomed Eng. vol.33, pp.2261-2271, 2002.
【53】 J. T. Sorensen, “A Physiologic Model of Glucose Metabolism in Man and its Use to Design and Assess Improved Insulin Therapies for Diabetes,” PhD Thesis, Dept. of Chemical Engineering. MIT, 1985.

【54】 J. Sturis, K.S. Polonsky, E. Mosekilde, and E. Van Cauter, “Computer model for mechanisms underlying ultradian oscillations of insulin and glucose” Am. J. Physiol. 260, E801–E809, 1991.
【55】 T. Yipintsoi, L.C. Gatewood, E. Ackerman, P.L., Spivak, G. D. Molnar, G. W. Rosevear, and F.C. Service, “Mathematical analysis of blood glucose and plasma insulin responses to insulin infusion in healthy and diabetes subjects”, Comput. Biol. Med., vol.3, pp.71-78, 1973.
【56】 Konstantia Zarkogianni, Stavroula G. Mougiakakou, Aikaterini Prountzou, Andriani Vazeou, Christos S. Bartsocas, and Konstantina S. Nikita” An Insulin Infusion Advisory System for Type 1 Diabetes Patients based on Non-Linear Model Predictive Control Methods” Proceedings of the 29th Annual International Conference of the IEEE EMBS Cité Internationale, Lyon, France, 2007.
【57】 H. Zisser, L. Jovanovic, F. Doyle, P. Ospina, and C. Owens, “Run–to–run control of meal–related insulin dosing,” Diabetes Technol Ther, vol. 7, no. 1, pp. 48–57, 2005.