A novel approach in adjustment of total daily insulin dosage for type 2 diabetes patients using a fuzzy logic based system


  • Ahmed Masud Chowdhury Department of Electrical & Computer Engineering, North South University, Dhaka, Bangladesh
  • Rubayat Islam Khan Department of Pharmacy, BRAC University, Dhaka, Bangladesh
  • Saif Shahriar Rahman Nirzhor Department of Pharmacy, BRAC University, Dhaka, Bangladesh
  • Jafrina Jabin Department of Pharmacy, BRAC University, Dhaka, Bangladesh
  • Arafat Islam Khan Department of Aerospace Engineering, San Diego State University, San Diego, California, USA


The aim of this study is to adjust the total daily insulin dosage for type 2 diabetes patients, who are already on an insulin treatment regimen, by using a fuzzy-based system. The dose is adjusted by taking into account three patient-related linguistic factors (PRFs) for 39 patients i.e. weight, body mass index (BMI), and average daily carbohydrate intake and utilizing this data to develop rules for a fuzzy-based system in MATLAB. The system was then made to generate an output which was compared to the prescribed doses of insulin by the patients’ respective physicians. The fuzzy based system was seen to bring a better regulation to the insulin treatment regimen for a particular patient as compared to the traditional non-fuzzy based methods which calculate total daily insulin dose based on each individual factor discretely. According to the output generated, the reasonable changes that this system suggested may evince better control on patient blood glucose levels. The usage of this system will allow fewer instances of hyperglycemic and hypoglycemic events among type 2 diabetes patients and may be further be translated  to type 1 diabetics.


Insulin, Fuzzy, MATLAB, Type 2 Diabetes, Dose Adjustment, Drug Dosing


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How to Cite

Ahmed Masud Chowdhury, Rubayat Islam Khan, S. S. R. Nirzhor, Jafrina Jabin, and Arafat Islam Khan. “A Novel Approach in Adjustment of Total Daily Insulin Dosage for Type 2 Diabetes Patients Using a Fuzzy Logic Based System”. Journal of Innovations in Pharmaceutical and Biological Sciences, vol. 4, no. 4, Oct. 2017, pp. 65-72, https://jipbs.com/index.php/journal/article/view/259.



Research Article