Recognition of multiple food, exercise and nutrition labels in glucoguide: phase IIa

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Diabetes is a chronic disease with many complications including heart attack, stroke, amputations and blindness. Self-management of blood glucose and improving lifestyle are very important to prevent complications, but it is a very difficult task. Mobile apps for diabetes tracking are increasingly available, but they can still be difficult to use - especially entering diet and exercise along with blood sugar and figuring out how to change diet and exercise to properly manage blood sugar. Therefore, we have been researching and developing GlucoGuide - an app that data-mines inputted diet and exercise data to give individual feedback and recommendations to help manage and reverse diabetes. This Phase IIa research and development project is a continuation of our Phase I I2I project (July 2014-July 2015) on GlucoGuide with promising results. Due to our achievements, we have secured early stage Angel Investment to our technologies, and the investor has put aside $70,000 specially to match this grant proposal. Continuing on our Phase I research and development, we will develop further analytic algorithms (including deep learning) to recognize food, multiple food combination, food nutrition label, barcode scanning and exercise equipment using the smartphone's camera. With simply taking a picture of meals, nutrition labels, and exercise equipment, users will be able to receive targeted recommendations to help manage their blood glucose better. This proposed research will significantly improve the usability of GlucoGuide, allowing for commercialization. The GlucoGuide Apps and system will benefit patients with pre-diabetes and diabetes, and overall, help to reduce the burden and cost on the healthcare systems in Canada and wrold.