Hardware, software and sensors for a device platform to measure and predict personal blood glucose levels has been delivered by Toumaz Technology (Abingdon, UK) to complete the first phase of a large-scale European Union (EU) project for diabetes patients.

Toumaz is responsible for the device work package that is part of the EU's DIAdvisor project developing a prediction-based tool using historic and current blood glucose measures to optimise the therapy of Type I and developed Type II diabetes with the goal of minimizing the occurrence of diabetic complications and reducing healthcare costs.

DIAdvisor is being developed by a consortium of 13 companies coordinated by Novo Nordisk (Bagsv rd, Denmark), a leader in diabetes care, that includes the European Division of the International Diabetes Federation.

DIAdvisor received $#128;7.1 million ($9.5 million) under the EU's Framework Seven Program in April, 2008.

The Toumaz device platform integrates a non-intrusive body-worn wireless vital sign sensor from Sensor Technology and Devices (Belfast, UK) and a non invasive glucose sensor from Ondaly (Montpellier, France).

Data collected from the sensors is processed onboard the body-worn device with the Toumaz Sensium chip and transmitted using Toumaz ultra-low power Advanced Mixed Signal (AMx) technology that continuously sends and receives data packets using batteries that can be as small as a slip of paper and not larger than a hearing aid battery.

Cardinal Health (Dublin, Ohio) and Texas Instruments (TI; Dallas) have licensed the Toumaz technology to develop intelligent medical devices.

Data sent from an individual monitor in theDIAdvisor project will be processed with software developed by RomSoft (Iasi, Romania) using models developed at Lunds University (Lund, Sweden) and algorithms developed at Johannes Kepler University (Linz, Austria).

The DIAdvisor device will allow patients to actively and accurately predict short-term blood glucose at any moment automating an analysis of glucose measurements, insulin delivery data and specific patient parameters.

Prediction data will be wirelessly transmitted to a designated healthcare provider which in turn will transmit recommended action and treatment advice for display on a patient's handheld mobile device.