Predicting Nocturnal Hypoglycemia Using a Non-parametric Insulin Action Model

Nocturnal hypoglycemia is a common and potentially very dangerous condition facing persons with insulin-treated diabetes. To reduce the risk of going low while sleeping, many patient wilfully elevate their glucose level before bedtime, thereby also eroding the conditions for a sound glucose control for the next day. Recent advances in sensor technology allow for real time frequent monitoring of the glucose level, and the road map towards an artificial pancreas involves combining an insulin pump with such sensors. The first steps towards a more autonomous insulin pump have been taken by allowing the pump to suspend the insulin supply when a hypoglycemic episode is imminent. This feature relies on algorithms for predicting the nocturnal event. In this paper, we present a novel model for this purpose. In comparison to previous methods, a better trade-off between sensitivity and false alarm rate was achieved, as well as improved warning time.