Integración de sensores de teléfonos en servicios de sensores OGC

Presentación de gvSIG Mobile Sensor, que integra la tecnología SOS (Sensor Observation Service) en los dispositivos móviles a partir de una nueva extensión de gvSIG Mobile. Esta funcionalidad almacena las peticiones SOS en plantillas, representado a los distintos sensores registrados. Las plantillas sirven para transformar los datos obtenidos por el sensor en un instante dado, en peticiones de inserción de observación válidas para el servicio SOS-T

Prediction of postprandial blood glucose under intra-patient variability and uncertainty and its use in the design of insulin dosing strategies for type 1 diabetic patients

In this thesis I propose a novel method to estimate the dose and injection-to-meal time for low-risk intensive insulin therapy. This dosage-aid system uses an optimization algorithm to determine the insulin dose and injection-to-meal time that minimizes the risk of postprandial hyper- and hypoglycaemia in type 1 diabetic patients. To this end, the algorithm applies a methodology that quantifies the risk of experiencing different grades of hypo- or hyperglycaemia in the postprandial state induced by insulin therapy according to an individual patient’s parameters. This methodology is based on modal interval analysis (MIA). Applying MIA, the postprandial glucose level is predicted with consideration of intra-patient variability and other sources of uncertainty. A worst-case approach is then used to calculate the risk index. In this way, a safer prediction of possible hyper- and hypoglycaemic episodes induced by the insulin therapy tested can be calculated in terms of these uncertainties.