| Autor: |
Papathanail I; ARTORG Center for Biomedical Engineering Research, University of Bern, 3008 Bern, Switzerland., Abdur Rahman L; ARTORG Center for Biomedical Engineering Research, University of Bern, 3008 Bern, Switzerland., Brigato L; ARTORG Center for Biomedical Engineering Research, University of Bern, 3008 Bern, Switzerland., Bez NS; School of Health Professions, Bern University of Applied Sciences, 3008 Bern, Switzerland., Vasiloglou MF; ARTORG Center for Biomedical Engineering Research, University of Bern, 3008 Bern, Switzerland., van der Horst K; School of Health Professions, Bern University of Applied Sciences, 3008 Bern, Switzerland., Mougiakakou S; ARTORG Center for Biomedical Engineering Research, University of Bern, 3008 Bern, Switzerland. |
| Abstrakt: |
A healthy diet can help to prevent or manage many important conditions and diseases, particularly obesity, malnutrition, and diabetes. Recent advancements in artificial intelligence and smartphone technologies have enabled applications to conduct automatic nutritional assessment from meal images, providing a convenient, efficient, and accurate method for continuous diet evaluation. We now extend the goFOOD TM automatic system to perform food segmentation, recognition, volume, as well as calorie and macro-nutrient estimation from single images that are captured by a smartphone. In order to assess our system's performance, we conducted a feasibility study with 50 participants from Switzerland. We recorded their meals for one day and then dietitians carried out a 24 h recall. We retrospectively analysed the collected images to assess the nutritional content of the meals. By comparing our results with the dietitians' estimations, we demonstrated that the newly introduced system has comparable energy and macronutrient estimation performance with the previous method; however, it only requires a single image instead of two. The system can be applied in a real-life scenarios, and it can be easily used to assess dietary intake. This system could help individuals gain a better understanding of their dietary consumption. Additionally, it could serve as a valuable resource for dietitians, and could contribute to nutritional research. |
