Next Article in Journal
The Important Role of Carbohydrates in the Flavor, Function, and Formulation of Oral Nutritional Supplements
Previous Article in Journal
Impact of a Modified Version of Baby-Led Weaning on Infant Food and Nutrient Intakes: The BLISS Randomized Controlled Trial
Open AccessArticle

A Comparative Study on Carbohydrate Estimation: GoCARB vs. Dietitians

Diabetes Technology Research Group, ARTORG Center for Biomedical Engineering Research, University of Bern, Murtenstrasse 50, 3008 Bern, Switzerland
Division of Diabetes, Endocrinology, Metabolism and Clinical Nutrition, Bern University Hospital “Inselspital”, 3010 Bern, Switzerland
Diabetes Centre for Children and Adolescents, Children’s and Youth Hospital “Auf Der Bult”, Janusz-Korczak-Allee 12, 30173 Hannover, Germany
Gewerblich-Industrielle Berufsschule Bern (GIBB), Lorrainestrasse 1, 3000 Bern, Switzerland
Medical University Department, Kantonsspital Aarau, Tellstrasse 25, 5001 Aarau, Switzerland
Faculty of Life Sciences, University of Vienna, Althanstrasse 14, 1090 Vienna, Austria
Food on Record, Freie Strasse 59, 4001 Basel, Switzerland
Author to whom correspondence should be addressed.
Nutrients 2018, 10(6), 741;
Received: 3 May 2018 / Revised: 2 June 2018 / Accepted: 5 June 2018 / Published: 7 June 2018
GoCARB is a computer vision-based smartphone system designed for individuals with Type 1 Diabetes to estimate plated meals’ carbohydrate (CHO) content. We aimed to compare the accuracy of GoCARB in estimating CHO with the estimations of six experienced dietitians. GoCARB was used to estimate the CHO content of 54 Central European plated meals, with each of them containing three different weighed food items. Ground truth was calculated using the USDA food composition database. Dietitians were asked to visually estimate the CHO content based on meal photographs. GoCARB and dietitians achieved comparable accuracies. The mean absolute error of the dietitians was 14.9 (SD 10.12) g of CHO versus 14.8 (SD 9.73) g of CHO for the GoCARB (p = 0.93). No differences were found between the estimations of dietitians and GoCARB, regardless the meal size. The larger the size of the meal, the greater were the estimation errors made by both. Moreover, the higher the CHO content of a food category was, the more challenging its accurate estimation. GoCARB had difficulty in estimating rice, pasta, potatoes, and mashed potatoes, while dietitians had problems with pasta, chips, rice, and polenta. GoCARB may offer diabetic patients the option of an easy, accurate, and almost real-time estimation of the CHO content of plated meals, and thus enhance diabetes self-management. View Full-Text
Keywords: type 1 diabetes; dietitian; visual estimation; carbohydrate counting; computer vision; artificial intelligence; smartphone type 1 diabetes; dietitian; visual estimation; carbohydrate counting; computer vision; artificial intelligence; smartphone
Show Figures

Figure 1

MDPI and ACS Style

Vasiloglou, M.F.; Mougiakakou, S.; Aubry, E.; Bokelmann, A.; Fricker, R.; Gomes, F.; Guntermann, C.; Meyer, A.; Studerus, D.; Stanga, Z. A Comparative Study on Carbohydrate Estimation: GoCARB vs. Dietitians. Nutrients 2018, 10, 741.

Show more citation formats Show less citations formats
Note that from the first issue of 2016, MDPI journals use article numbers instead of page numbers. See further details here.

Article Access Map by Country/Region

Search more from Scilit
Back to TopTop