Parallel software architecture for the next generation of glucose monitoring

Diabetes is a widespread disease. Elevated blood glucose levels continuously damage multiple organs in the long-term. In the short-term, hypo- and hyperglycemic shocks are acute risks. Diabetes patients monitor their glucose level using continuous glucose monitoring systems. Based on their measured glucose level, the patient take insulin to lower their blood glucose level. With the advances in mobile computing, an increasing number of diabetes patients engage in self-built systems. They read their glucose levels from glucose-monitoring systems and calculate their insulin dosage based on the measured levels. The self-built nature of such a system raises a number of medical and software engineering concerns. Therefore, we propose a software architecture for the next generation of glucose monitoring. The proposed architecture builds on the principles of the high-level architecture. We decompose the entire glucose monitoring system to basic elements, which are either real or simulated. This opens the proposed architecture to software engineering, simulation, and fault-tolerance research. As a proof of concept, we present an illustrative configuration of the implemented software architecture that predicts future blood glucose levels 15 minutes in advance for type-1 diabetes patients. All relative errors are in the A+B zones of Clarke and Parkes error grids, with almost 95% of errors in the safest A-zones of both grids.