  People with diabetes have to manage their blood glucose level to keep it
within an appropriate range. Predicting whether future glucose values will be
outside the healthy threshold is of vital importance in order to take
corrective actions to avoid potential health damage. In this paper we describe
our research with the aim of predicting the future behavior of blood glucose
levels, so that hypoglycemic events may be anticipated. The approach of this
work is the application of transformation functions on glucose time series, and
their use in convolutional neural networks. We have tested our proposed method
using real data from 4 different diabetes patients with promising results.
