Glucose Forecasting using a physiological model and state estimation

Accurate glucose forecasting algorithms have been proven to be an effective solution for reducing the risk of hypo- and hyperglycaemia events when combined with glucose alarms and/or low-insulin suspension systems. • Effective glucose forecasting algorithms can be applied tocontrolinsulindeliveryinautomaticsystems. • Daily routine information (e.g. meal intake, insulin injection, physical exercises) of person with diabetes can be included into forecasting algorithms to improve predictionaccuracy. • Inthiswork,weintroduceanovelmodel-basedglucose prediction algorithm which uses deconvolution of the continuous glucose monitoring (CGM) signal to estimate some of the model states in order to improve predictionaccuracy.