Sensika Niyathapala

UC Santa Barbara
Chemical Engineering

Analysis and Development of Meal Detection Algorithm for the Artificial Pancreas

Type 1 diabetes is a disease where no insulin is produced in the body, making it necessary for subjects to continuously monitor blood glucose levels and inject insulin several times a day. The artificial pancreas uses a closed-loop system that consists of a combination of monitoring (subcutaneous sensing, finger stick, and insulin insertion) and computer programming (algorithms using MATLAB) to be able to detect the change in continuous glucose monitor (CGM) levels and a response for the event.5 Meal detection in particular poses a problem due to rapid increase in blood glucose and the risk of hyperglycemia. The challenge that faces meal detection is being able to respond within an appropriate time and with the correct amount of insulin to compensate for the meal.1 The previous developments of the artificial pancreas have all used meal announcement to compensate for a meal.2-4 The Doyle group is one of the few groups working on the development of an artificial pancreas without the need for a meal announcement, creating a fully automatic system.6 To aid in responding to meal, an algorithm is being developed that uses different parameters to assist in identifying when a meal has been consumed alerts the system of a meal and inform the controller to respond to the meal in order to maintain the ideal glucose levels of 80-140 mg/dL. Using data from recent clinical trials, the response of the controller without meal detection to the meal was analyzed by qualitatively identifying an increase in insulin delivery due to a post-prandial rise in glucose to assist in the development of the artificial pancreas. 

UC Santa Barbara Center for Science and Engineering Partnerships UCSB California NanoSystems Institute