The platform for the target implementation is a handheld device like a PDA or a mobile phone which the patient can carry anywhere during the day.
The flow through the BG (blood glucose) predictor system can be divided into three steps:
Inputs from vital sign sensors and blood glucose measurements are acquired from the patients;
A prediction engine consisting of a mixed model, combined with a predictive control algorithm, predicts the future blood glucose development;
A decision support module interprets the predicted BG curve
into the future. This allows patients to step in and take action before the peaks actually occur, and in this way avoiding the devastating effects that blood glucose extreme levels can cause to the body on the long run.
The decision management module is crucial to the requirements of this project, as most patients, even if they had a prediction for the BG levels for the next two hours, they most likely would not know what to do with it.
The project researchers have been careful to set very high safety criteria when it comes to the prediction rules and the advisory component. In the preliminary clinical trials, the predictive power of the system was shown to be useful up to two hours ahead. Its recommendations perfectly matched those of real doctors 88 % of the time and out of almost 1500 recommendations during testing it never provided any harmful advice.
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