Hydra: A hybrid diagnosis and monitoring architecture for diabetes

We present Hydra: a multi-agent hybrid diagnosis and monitoring architecture that is aimed at helping diabetic patients manage their illness. It makes use of model-based diagnosis techniques, where the model can be developed by two different approaches combined in a novel way. In the first approach, we build the model based on the medical guidelines provided for diabetes. A computational logic agent monitors the patient and provides feedback based on the model whenever the current observations regarding the patient are sufficient to draw a conclusion. In the second approach, we assume a function for the model, and learn its parameters through data. The model is consistently updated via incoming observations about the patients, and allows prediction of possible future values. We describe the components of such an architecture, and how it can integrated into the existing COMMODITY12 personal health system. We implement a prototype of Hydra, and present its workings on a case study on hypoglycemia monitoring. We report our prediction results for this scenario.