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Development of an Intelligent System to Predict and Control Blood Glucose Level in Type 1 Diabetic Patients

Afsharpour, Alireza | 2011

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  1. Type of Document: M.Sc. Thesis
  2. Language: Farsi
  3. Document No: 43112 (06)
  4. University: Sharif University of Technology
  5. Department: Chemical and Petroleum Engineering
  6. Advisor(s): Bozorgmehri, Ramin
  7. Abstract:
  8. All living entities requires energy to continue their lives. In human beings this energy is provide through consumption of food, at first the consumed food gets converted to glucose and the produced glucose enters the blood and then goes to the body cells in which it is used to produce the required energy. The essential hormone which makes it possible to use Glucose for energy production is INSULIN. In the patients suffering from Type 1 Diabetes, lack of Insulin production makes it impossible for the cells to use Glucose for the production of their required energy. In these patients due to the fact that the blood Glucose is not used by the cells, the Blood Glucose Level (BGL) increases, this can cause serious health problems and even might lead to the patient death. In this type of diabetes the patients have to provide the required insulin through injection, that’s why this type of Diabetes is called Insulin Dependent Diabetes Mellitus (IDDM). In this work an intelligent Fuzzy model has been developed whose main advantage is the fact that it takes into account the effects of various parameters (affecting the blood glucose level in patients suffering from IDDM) which have not been taken into account in various mathematical models proposed IDDM. In the existing mathematical models the effects of carbohydrate consumption, body weight and injected Insulin have been considered. However, there are other parameters such as activity and sport, Illness, stress, oxygen intake that are affecting BGL and have not been considered in the existing mathematical models. The proposed Fuzzy model takes into account the effect of these parameters in a quantitative manner. The proposed model fulfills most of the practical rules that exist among medical practitioners. Furthermore the comparison of its results with those obtained by Cinar Model shows that despite its simple structure it can predict the BGL fairly accurately
  9. Keywords:
  10. Blood Glucose ; Fuzzy Logic ; Fuzzy Model ; Diabetes Mellitus Type 1

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