A Comparative Study on Carbohydrate Estimation: GoCARB vs. Dietitians
by
Maria F. Vasiloglou 1, Stavroula Mougiakakou 1,2,*, Emilie Aubry 2
, Anika Bokelmann 3, Rita Fricker 4, Filomena Gomes 5, Cathrin Guntermann 3, Alexa Meyer 6, Diana Studerus 7 and Zeno Stanga 2
Maria F. Vasiloglou 1, Stavroula Mougiakakou 1,2,*, Emilie Aubry 2, Anika Bokelmann 3, Rita Fricker 4, Filomena Gomes 5, Cathrin Guntermann 3, Alexa Meyer 6, Diana Studerus 7 and Zeno Stanga 2
1
Diabetes Technology Research Group, ARTORG Center for Biomedical Engineering Research, University of Bern, Murtenstrasse 50, 3008 Bern, Switzerland
2
Division of Diabetes, Endocrinology, Metabolism and Clinical Nutrition, Bern University Hospital “Inselspital”, 3010 Bern, Switzerland
3
Diabetes Centre for Children and Adolescents, Children’s and Youth Hospital “Auf Der Bult”, Janusz-Korczak-Allee 12, 30173 Hannover, Germany
4
Gewerblich-Industrielle Berufsschule Bern (GIBB), Lorrainestrasse 1, 3000 Bern, Switzerland
5
Medical University Department, Kantonsspital Aarau, Tellstrasse 25, 5001 Aarau, Switzerland
6
Faculty of Life Sciences, University of Vienna, Althanstrasse 14, 1090 Vienna, Austria
7
Food on Record, Freie Strasse 59, 4001 Basel, Switzerland
*
Author to whom correspondence should be addressed.
Nutrients 2018, 10(6), 741; https://doi.org/10.3390/nu10060741
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
▼
Show Figures
Figure 1
This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited
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
Note that from the first issue of 2016, MDPI journals use article numbers instead of page numbers. See further details here.
