Development of a smart environment for diabetes data analysis and new knowledge mining

Diabetes care requires the control of an extensive set of clinical and non-clinical variables which affect the metabolism of glucose in order to prevent acute complications (i.e. hypoglycemic episodes) and to reduce the risk of long-term ones. In this study, we present a clinical information system which records medical (clinical and laboratory) parameters related to Type 1 and 2 diabetes and, mainly, takes a significant step forward towards the collection of lifestyle data. In addition, the intuitive representation and the intelligent analysis of all these multiparameter data enable the clinician to interpret the status of each patient and support him indirectly in the development of an effective individualized treatment plan.