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Systems and WBANs for Controlling Obesity
According to World Health Organization (WHO) estimations, one out of five adults worldwide will be obese by 2025. Worldwide obesity has doubled since 1980. In fact, more than 1.9 billion adults (39%) of 18 years and older were overweight and over 600 million (13%) of these were obese in 2014. 42 mil...
Autores principales: | , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Hindawi
2018
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5823412/ https://www.ncbi.nlm.nih.gov/pubmed/29599941 http://dx.doi.org/10.1155/2018/1564748 |
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author | Mohammed, Maali Said Sendra, Sandra Lloret, Jaime Bosch, Ignacio |
author_facet | Mohammed, Maali Said Sendra, Sandra Lloret, Jaime Bosch, Ignacio |
author_sort | Mohammed, Maali Said |
collection | PubMed |
description | According to World Health Organization (WHO) estimations, one out of five adults worldwide will be obese by 2025. Worldwide obesity has doubled since 1980. In fact, more than 1.9 billion adults (39%) of 18 years and older were overweight and over 600 million (13%) of these were obese in 2014. 42 million children under the age of five were overweight or obese in 2014. Obesity is a top public health problem due to its associated morbidity and mortality. This paper reviews the main techniques to measure the level of obesity and body fat percentage, and explains the complications that can carry to the individual's quality of life, longevity and the significant cost of healthcare systems. Researchers and developers are adapting the existing technology, as intelligent phones or some wearable gadgets to be used for controlling obesity. They include the promoting of healthy eating culture and adopting the physical activity lifestyle. The paper also shows a comprehensive study of the most used mobile applications and Wireless Body Area Networks focused on controlling the obesity and overweight. Finally, this paper proposes an intelligent architecture that takes into account both, physiological and cognitive aspects to reduce the degree of obesity and overweight. |
format | Online Article Text |
id | pubmed-5823412 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2018 |
publisher | Hindawi |
record_format | MEDLINE/PubMed |
spelling | pubmed-58234122018-03-29 Systems and WBANs for Controlling Obesity Mohammed, Maali Said Sendra, Sandra Lloret, Jaime Bosch, Ignacio J Healthc Eng Review Article According to World Health Organization (WHO) estimations, one out of five adults worldwide will be obese by 2025. Worldwide obesity has doubled since 1980. In fact, more than 1.9 billion adults (39%) of 18 years and older were overweight and over 600 million (13%) of these were obese in 2014. 42 million children under the age of five were overweight or obese in 2014. Obesity is a top public health problem due to its associated morbidity and mortality. This paper reviews the main techniques to measure the level of obesity and body fat percentage, and explains the complications that can carry to the individual's quality of life, longevity and the significant cost of healthcare systems. Researchers and developers are adapting the existing technology, as intelligent phones or some wearable gadgets to be used for controlling obesity. They include the promoting of healthy eating culture and adopting the physical activity lifestyle. The paper also shows a comprehensive study of the most used mobile applications and Wireless Body Area Networks focused on controlling the obesity and overweight. Finally, this paper proposes an intelligent architecture that takes into account both, physiological and cognitive aspects to reduce the degree of obesity and overweight. Hindawi 2018-02-01 /pmc/articles/PMC5823412/ /pubmed/29599941 http://dx.doi.org/10.1155/2018/1564748 Text en Copyright © 2018 Maali Said Mohammed et al. http://creativecommons.org/licenses/by/4.0/ 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. |
spellingShingle | Review Article Mohammed, Maali Said Sendra, Sandra Lloret, Jaime Bosch, Ignacio Systems and WBANs for Controlling Obesity |
title | Systems and WBANs for Controlling Obesity |
title_full | Systems and WBANs for Controlling Obesity |
title_fullStr | Systems and WBANs for Controlling Obesity |
title_full_unstemmed | Systems and WBANs for Controlling Obesity |
title_short | Systems and WBANs for Controlling Obesity |
title_sort | systems and wbans for controlling obesity |
topic | Review Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5823412/ https://www.ncbi.nlm.nih.gov/pubmed/29599941 http://dx.doi.org/10.1155/2018/1564748 |
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