Sharif Digital Repository

Background: Glucose sensors have been extensively researched in patent studies and manufactured a tool for clinical diabetes diagnosis. Although some kinds of electrochemical enzymatic glucose sensors have been commercially successful, there is still room for improvement, in selectivity and reliability of these sensors. Because of the intrinsic disadvantages of enzymes, such as high fabrication cost and poor stability, non-enzymatic glucose sensors have recently been promoted as next generation diagnostic tool due to their relatively low cost, high stability, prompt response, and accuracy. Objective: In this research, a novel free standing and binder free non-enzymatic electrochemical sensor... 

Background: Type-2 diabetes mellitus is characterized by insulin resistance and impaired insulin secretion in the human body. Many endeavors have been made in terms of controlling and reducing blood glucose via the medium of automated controlling tools to increase precision and efficiency and reduce human error. Recently, reinforcement learning algorithms are proved to be powerful in the field of intelligent control, which was the motivation for the current study. Methods: For the first time, a reinforcement algorithm called normalized advantage function (NAF) algorithm has been applied as a model-free reinforcement learning method to regulate the blood glucose level of type-2 diabetic...