Stance4Health Nutritional APP: A Path to Personalized Smart Nutrition
Access to good nutritional health is one of the principal objectives of current society. Several e-services offer dietary advice. However, multifactorial and more individualized nutritional recommendations should be developed to recommend healthy menus according to the specific user’s needs. In this...
| Main Authors: | , , , , , , |
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| Format: | Article |
| Language: | English |
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MDPI AG
2023-01-01
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| Series: | Nutrients |
| Subjects: | |
| Online Access: | https://www.mdpi.com/2072-6643/15/2/276 |
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| author | Daniel Hinojosa-Nogueira Bartolomé Ortiz-Viso Beatriz Navajas-Porras Sergio Pérez-Burillo Verónica González-Vigil Silvia Pastoriza de la Cueva José Ángel Rufián-Henares |
| author_facet | Daniel Hinojosa-Nogueira Bartolomé Ortiz-Viso Beatriz Navajas-Porras Sergio Pérez-Burillo Verónica González-Vigil Silvia Pastoriza de la Cueva José Ángel Rufián-Henares |
| author_sort | Daniel Hinojosa-Nogueira |
| collection | DOAJ |
| description | Access to good nutritional health is one of the principal objectives of current society. Several e-services offer dietary advice. However, multifactorial and more individualized nutritional recommendations should be developed to recommend healthy menus according to the specific user’s needs. In this article, we present and validate a personalized nutrition system based on an application (APP) for smart devices with the capacity to offer an adaptable menu to the user. The APP was developed following a structured recommendation generation scheme, where the characteristics of the menus of 20 users were evaluated. Specific menus were generated for each user based on their preferences and nutritional requirements. These menus were evaluated by comparing their nutritional content versus the nutrient composition retrieved from dietary records. The generated menus showed great similarity to those obtained from the user dietary records. Furthermore, the generated menus showed less variability in micronutrient amounts and higher concentrations than the menus from the user records. The macronutrient deviations were also corrected in the generated menus, offering a better adaptation to the users. The presented system is a good tool for the generation of menus that are adapted to the user characteristics and a starting point to nutritional interventions. |
| first_indexed | 2024-03-09T11:32:48Z |
| format | Article |
| id | doaj.art-a06a41c6316e47c4971fe503a9330812 |
| institution | Directory Open Access Journal |
| issn | 2072-6643 |
| language | English |
| last_indexed | 2024-03-09T11:32:48Z |
| publishDate | 2023-01-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Nutrients |
| spelling | doaj.art-a06a41c6316e47c4971fe503a93308122023-11-30T23:49:20ZengMDPI AGNutrients2072-66432023-01-0115227610.3390/nu15020276Stance4Health Nutritional APP: A Path to Personalized Smart NutritionDaniel Hinojosa-Nogueira0Bartolomé Ortiz-Viso1Beatriz Navajas-Porras2Sergio Pérez-Burillo3Verónica González-Vigil4Silvia Pastoriza de la Cueva5José Ángel Rufián-Henares6Centro de Investigación Biomédica, Departamento de Nutrición y Bromatología, Instituto de Nutrición y Tecnología de los Alimentos, Universidad de Granada, 18071 Granada, SpainDepartamento de Ciencias de la Computación e Inteligencia Artificial, Universidad de Granada, 18071 Granada, SpainCentro de Investigación Biomédica, Departamento de Nutrición y Bromatología, Instituto de Nutrición y Tecnología de los Alimentos, Universidad de Granada, 18071 Granada, SpainCentro de Investigación Biomédica, Departamento de Nutrición y Bromatología, Instituto de Nutrición y Tecnología de los Alimentos, Universidad de Granada, 18071 Granada, SpainGestión de Salud y Nutrición S.L., 33003 Oviedo, SpainCentro de Investigación Biomédica, Departamento de Nutrición y Bromatología, Instituto de Nutrición y Tecnología de los Alimentos, Universidad de Granada, 18071 Granada, SpainCentro de Investigación Biomédica, Departamento de Nutrición y Bromatología, Instituto de Nutrición y Tecnología de los Alimentos, Universidad de Granada, 18071 Granada, SpainAccess to good nutritional health is one of the principal objectives of current society. Several e-services offer dietary advice. However, multifactorial and more individualized nutritional recommendations should be developed to recommend healthy menus according to the specific user’s needs. In this article, we present and validate a personalized nutrition system based on an application (APP) for smart devices with the capacity to offer an adaptable menu to the user. The APP was developed following a structured recommendation generation scheme, where the characteristics of the menus of 20 users were evaluated. Specific menus were generated for each user based on their preferences and nutritional requirements. These menus were evaluated by comparing their nutritional content versus the nutrient composition retrieved from dietary records. The generated menus showed great similarity to those obtained from the user dietary records. Furthermore, the generated menus showed less variability in micronutrient amounts and higher concentrations than the menus from the user records. The macronutrient deviations were also corrected in the generated menus, offering a better adaptation to the users. The presented system is a good tool for the generation of menus that are adapted to the user characteristics and a starting point to nutritional interventions.https://www.mdpi.com/2072-6643/15/2/276computational nutritionmeal plan generatornutritional appnutritional interventionsmartphone applicationdiet app |
| spellingShingle | Daniel Hinojosa-Nogueira Bartolomé Ortiz-Viso Beatriz Navajas-Porras Sergio Pérez-Burillo Verónica González-Vigil Silvia Pastoriza de la Cueva José Ángel Rufián-Henares Stance4Health Nutritional APP: A Path to Personalized Smart Nutrition Nutrients computational nutrition meal plan generator nutritional app nutritional intervention smartphone application diet app |
| title | Stance4Health Nutritional APP: A Path to Personalized Smart Nutrition |
| title_full | Stance4Health Nutritional APP: A Path to Personalized Smart Nutrition |
| title_fullStr | Stance4Health Nutritional APP: A Path to Personalized Smart Nutrition |
| title_full_unstemmed | Stance4Health Nutritional APP: A Path to Personalized Smart Nutrition |
| title_short | Stance4Health Nutritional APP: A Path to Personalized Smart Nutrition |
| title_sort | stance4health nutritional app a path to personalized smart nutrition |
| topic | computational nutrition meal plan generator nutritional app nutritional intervention smartphone application diet app |
| url | https://www.mdpi.com/2072-6643/15/2/276 |
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