Feeling Hungry : Association of Dietary Patterns with Food Choices using Scene Perception
- Studies on nutrition have historically concentrated on food-shortages and over-nutrition. The physiological states of feeling hungry or being satiated and its dynamics in food choices, dietary patterns, and nutritional behavior, have not been the focus of many studies. Currently, visual analytic using easy-to-use tooling offers applicability in a wide-range of disciplines. In this interdisciplinary pilot-study we tested a novel visual analytic software to assess dietary patterns and food choices for greater understanding of nutritional behavior when hungry and when satiated. We developed software toolchain and tested the hypotheses that there is no difference between visual search patterns of dishes 1) when hungry and when satiated and 2) in being vegetarian and non-vegetarian. Results indicate that food choices can be deviant from dietary patterns but correlate slightly with dish-gazing. Further, scene perception probably could vary between being hungry and satiated. Understanding t he complicated relationship between scene perception and nutritional behavioral patterns and scaling up this pilot-study to a full-study using our introduced software approaches is indispensable.
Author: | Shoma Barbara BerkemeyerORCiD, Julius SchöningORCiD |
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Title (English): | Feeling Hungry : Association of Dietary Patterns with Food Choices using Scene Perception |
URN: | urn:nbn:de:bsz:959-opus-49710 |
DOI: | https://doi.org/10.5220/0010146101880195 |
ISBN: | 978-989-758-480-0 |
Parent Title (English): | CHIRA 2020 |
Document Type: | Conference Proceeding |
Language: | English |
Year of Completion: | 2020 |
Release Date: | 2023/06/29 |
Tag: | Dietary Patterns; Food Choices; Gaze Analytics; Multimodal Data Analysis; Nutritional Behavior; Nutritional Patterns; Scene Perception; Visualization |
First Page: | 188 |
Last Page: | 195 |
Note: | 4th International Conference on Computer-Human Interaction Research and Applications (CHIRA), 05.11. - 06.11.2020, Online |
Faculties: | Fakultät AuL |
DDC classes: | 600 Technik, Medizin, angewandte Wissenschaften / 610 Medizin, Gesundheit |
Review Status: | Veröffentlichte Fassung/Verlagsversion |
Licence (German): | Creative Commons - CC BY-NC-ND - Namensnennung - Nicht kommerziell - Keine Bearbeitungen 4.0 International |