{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,10,30]],"date-time":"2025-10-30T07:15:05Z","timestamp":1761808505084,"version":"build-2065373602"},"reference-count":49,"publisher":"MDPI AG","issue":"7","license":[{"start":{"date-parts":[[2022,3,29]],"date-time":"2022-03-29T00:00:00Z","timestamp":1648512000000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/summer-heart-0930.chufeiyun1688.workers.dev:443\/https\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"DOI":"10.13039\/501100014193","name":"Polytechnic Institute of Viseu","doi-asserted-by":"publisher","award":["PROJ\/IPV\/IDI\/002"],"award-info":[{"award-number":["PROJ\/IPV\/IDI\/002"]}],"id":[{"id":"10.13039\/501100014193","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Sensors"],"abstract":"<jats:p>Precision nutrition is a popular eHealth topic among several groups, such as athletes, people with dementia, rare diseases, diabetes, and overweight. Its implementation demands tight nutrition control, starting with nutritionists who build up food plans for specific groups or individuals. Each person then follows the food plan by preparing meals and logging all food and water intake. However, the discipline demanded to follow food plans and log food intake results in high dropout rates. This article presents the concepts, requirements, and architecture of a solution that assists the nutritionist in building up and revising food plans and the user following them. It does so by minimizing human\u2013computer interaction by integrating the nutritionist and user systems and introducing off-the-shelf IoT devices in the system, such as temperature sensors, smartwatches, smartphones, and smart bottles. An interaction time analysis using the keystroke-level model provides a baseline for comparison in future work addressing both the use of machine learning and IoT devices to reduce the interaction effort of users.<\/jats:p>","DOI":"10.3390\/s22072617","type":"journal-article","created":{"date-parts":[[2022,3,29]],"date-time":"2022-03-29T21:45:51Z","timestamp":1648590351000},"page":"2617","update-policy":"https:\/\/summer-heart-0930.chufeiyun1688.workers.dev:443\/https\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":12,"title":["Multi-Device Nutrition Control"],"prefix":"10.3390","volume":"22","author":[{"ORCID":"https:\/\/summer-heart-0930.chufeiyun1688.workers.dev:443\/https\/orcid.org\/0000-0002-2754-5401","authenticated-orcid":false,"given":"Carlos A. S.","family":"Cunha","sequence":"first","affiliation":[{"name":"CISeD\u2014Research Centre in Digital Services, Polytechnic Institute of Viseu, 3504-510 Viseu, Portugal"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/summer-heart-0930.chufeiyun1688.workers.dev:443\/https\/orcid.org\/0000-0002-6819-0985","authenticated-orcid":false,"given":"Rui P.","family":"Duarte","sequence":"additional","affiliation":[{"name":"CISeD\u2014Research Centre in Digital Services, Polytechnic Institute of Viseu, 3504-510 Viseu, Portugal"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"1968","published-online":{"date-parts":[[2022,3,29]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","first-page":"1958","DOI":"10.1016\/S0140-6736(19)30041-8","article-title":"Health effects of dietary risks in 195 countries, 1990\u20132017: A systematic analysis for the Global Burden of Disease Study 2017","volume":"393","author":"Afshin","year":"2019","journal-title":"Lancet"},{"key":"ref_2","doi-asserted-by":"crossref","unstructured":"Wohlers, E.M., Sirard, J.R., Barden, C.M., and Moon, J.K. 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