Computer Vision-Based Carbohydrate Estimation for Type 1 Diabetic Patients Using Smartphones

Anthimopoulos, Marios; Dehais, Joachim Blaise; Shevchik, Sergey; Botwey, Ransford Henry; Duke, David; Diem, Peter; Mougiakakou, Stavroula (2015). Computer Vision-Based Carbohydrate Estimation for Type 1 Diabetic Patients Using Smartphones. Journal of diabetes science and technology, 9(3), pp. 507-515. Diabetes Technology Society 10.1177/1932296815580159

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Background: Individuals with type 1 diabetes (T1D) have to count the carbohydrates (CHOs) of their meal to estimate the prandial insulin dose needed to compensate for the meal’s effect on blood glucose levels. CHO counting is very challenging but also crucial, since an error of 20 grams can substantially impair postprandial control. Method: The GoCARB system is a smartphone application designed to support T1D patients with CHO counting of nonpacked foods. In a typical scenario, the user places a reference card next to the dish and acquires 2 images with his/her smartphone. From these images, the plate is detected and the different food items on the plate are automatically segmented and recognized, while their 3D shape is reconstructed. Finally, the food volumes are calculated and the CHO content is estimated by combining the previous results and using the USDA nutritional database. Results: To evaluate the proposed system, a set of 24 multi-food dishes was used. For each dish, 3 pairs of images were taken and for each pair, the system was applied 4 times. The mean absolute percentage error in CHO estimation was 10 ± 12%, which led to a mean absolute error of 6 ± 8 CHO grams for normal-sized dishes. Conclusion: The laboratory experiments demonstrated the feasibility of the GoCARB prototype system since the error was below the initial goal of 20 grams. However, further improvements and evaluation are needed prior launching a system able to meet the inter- and intracultural eating habits.

Item Type:

Journal Article (Original Article)

Division/Institute:

10 Strategic Research Centers > ARTORG Center for Biomedical Engineering Research
04 Faculty of Medicine > Department of Intensive Care, Emergency Medicine and Anaesthesiology (DINA) > University Emergency Center
10 Strategic Research Centers > ARTORG Center for Biomedical Engineering Research > ARTORG Center - Diabetes Technology
04 Faculty of Medicine > Department of Gynaecology, Paediatrics and Endocrinology (DFKE) > Clinic of Endocrinology, Diabetology and Clinical Nutrition

Graduate School:

Graduate School for Cellular and Biomedical Sciences (GCB)

UniBE Contributor:

Anthimopoulos, Marios; Dehais, Joachim Blaise; Shevchik, Sergey; Botwey, Ransford Henry; Diem, Peter and Mougiakakou, Stavroula

Subjects:

500 Science > 570 Life sciences; biology
600 Technology > 610 Medicine & health

ISSN:

1932-2968

Publisher:

Diabetes Technology Society

Language:

English

Submitter:

Stavroula Mougiakakou

Date Deposited:

19 May 2015 13:44

Last Modified:

09 May 2016 14:46

Publisher DOI:

10.1177/1932296815580159

PubMed ID:

25883163

URI:

https://boris.unibe.ch/id/eprint/68155

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