Universitât Bern

Debiotech S.a.

Roche Diabetes Care, Inc.

University of Bern

Stavroula Mougiakakou

Laurent-Dominique Piveteau

Stephan Proennecke

Qingnan Sun

Marko Jankovic

João Budzinski

Abhishek S Soni

Alan Greenburg

Peter Diem

Marios Anthimpoulos

Joachim Dehais

Eleni Daskalaki

Sergey Shevchick

An aspect of the invention provides a method and a product for determining a modification of the therapy management by using a processor unit which retrieves few data related to the blood glucose measurement performed over a predetermined time period; retrieve the medication delivery parameter executed by the delivery device over said predetermined time period; retrieve from the memory data associated to the CIR of the patient; and determine a modification to the therapy based on at least a part of the retrieved data.

System and method for improving the drug therapy management

The optimal insulin to be delivered by an insulin infusion pump is determined by using a reinforcement learning algorithm aiming to the personalized glucose regulation. The algorithm optimizes the daily basal insulin rate and insulin: carbohydrate ratio for each patient, on the basis of his/her measured glucose profile. The proposed algorithm is able to learn in real-time patient-specific characteristics captured in the daily glucose profile and provide individualized insulin treatment. An automatic and personalized tuning method contributes in the optimisation of the algorithm's performance.

Estimation of insulin based on reinforcement learning

There is disclosed a system for estimating the volume of food on a plate, for example meal, with a mobile device. The system uses a camera and a light pattern projector. Images of the food with and without a projected light pattern on it enable to compute the tridimensional shape and volume, while image segmentation and recognition steps estimate one or more food types in said images. By applying accessible knowledge databases, the carbs content is estimated and the associated insulin bolus doses are provided. Developments comprise coding of the light pattern, different light sources and associated wavelengths, motion compensations, additional optics, estimation of fat content and associated multi-wave boluses. The invention can be implemented in a glucometer or in an insulin pump controller provided with a test strip port or with a mobile phone.

Estimation of food volume and carbs

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Bern, Switzerland

Stavroula Mougiakakou