Development of a Mobile Application Platform for Self-Management of Obesity Using Artificial Intelligence Techniques
Obesity is a major global health challenge and a risk factor for the leading causes of death, including heart disease, stroke, diabetes, and several types of cancer. Attempts to manage and regulate obesity have led to the implementation of various dietary regulatory initiatives to provide informatio...
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| Format: | Article |
| Language: | English |
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Wiley
2021-01-01
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| Series: | International Journal of Telemedicine and Applications |
| Online Access: | http://dx.doi.org/10.1155/2021/6624057 |
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| author | Sylvester M. Sefa-Yeboah Kwabena Osei Annor Valencia J. Koomson Firibu K. Saalia Matilda Steiner-Asiedu Godfrey A. Mills |
| author_facet | Sylvester M. Sefa-Yeboah Kwabena Osei Annor Valencia J. Koomson Firibu K. Saalia Matilda Steiner-Asiedu Godfrey A. Mills |
| author_sort | Sylvester M. Sefa-Yeboah |
| collection | DOAJ |
| description | Obesity is a major global health challenge and a risk factor for the leading causes of death, including heart disease, stroke, diabetes, and several types of cancer. Attempts to manage and regulate obesity have led to the implementation of various dietary regulatory initiatives to provide information on the calorie contents of meals. Although knowledge of the calorie content is useful for meal planning, it is not sufficient as other factors, including health status (diabetes, hypertension, etc.) and level of physical activity, are essential in the decision process for obesity management. In this work, we present an artificial intelligence- (AI-) based application that is driven by a genetic algorithm (GA) as a potential tool for tracking a user’s energy balance and predicting possible calorie intake required to meet daily calorie needs for obesity management. The algorithm takes the users’ input information on desired foods which are selected from a database and extracted records of users on cholesterol level, diabetes status, and level of physical activity, to predict possible meals required to meet the users need. The micro- and macronutrients of food content are used for the computation and prediction of the potential foods required to meet the daily calorie needs. The functionality and performance of the model were tested using a sample of 30 volunteers from the University of Ghana. Results revealed that the model was able to predict both glycemic and non-glycemic foods based on the condition of the user as well as the macro- and micronutrients requirements. Moreover, the system is able to adequately track the progress of the user’s weight loss over time, daily nutritional needs, daily calorie intake, and predictions of meals that must be taken to avoid compromising their health. The proposed system can serve as a useful resource for individuals, dieticians, and other health management personnel for managing obesity, patients, and for training students in fields of dietetics and consumer science. |
| format | Article |
| id | doaj-art-56285e072fef4e82a5483d3626c83e4b |
| institution | Kabale University |
| issn | 1687-6415 1687-6423 |
| language | English |
| publishDate | 2021-01-01 |
| publisher | Wiley |
| record_format | Article |
| series | International Journal of Telemedicine and Applications |
| spelling | doaj-art-56285e072fef4e82a5483d3626c83e4b2025-02-03T01:25:12ZengWileyInternational Journal of Telemedicine and Applications1687-64151687-64232021-01-01202110.1155/2021/66240576624057Development of a Mobile Application Platform for Self-Management of Obesity Using Artificial Intelligence TechniquesSylvester M. Sefa-Yeboah0Kwabena Osei Annor1Valencia J. Koomson2Firibu K. Saalia3Matilda Steiner-Asiedu4Godfrey A. Mills5Department of Computer Engineering, University of Ghana, P.O. Box LG, 77 Legon, GhanaDepartment of Computer Engineering, University of Ghana, P.O. Box LG, 77 Legon, GhanaDepartment of Electrical and Computer Engineering, Tufts University, Medford, MA 02155, USADepartment of Nutrition and Food Science, University of Ghana, P.O. Box LG134, Legon, GhanaDepartment of Nutrition and Food Science, University of Ghana, P.O. Box LG134, Legon, GhanaDepartment of Computer Engineering, University of Ghana, P.O. Box LG, 77 Legon, GhanaObesity is a major global health challenge and a risk factor for the leading causes of death, including heart disease, stroke, diabetes, and several types of cancer. Attempts to manage and regulate obesity have led to the implementation of various dietary regulatory initiatives to provide information on the calorie contents of meals. Although knowledge of the calorie content is useful for meal planning, it is not sufficient as other factors, including health status (diabetes, hypertension, etc.) and level of physical activity, are essential in the decision process for obesity management. In this work, we present an artificial intelligence- (AI-) based application that is driven by a genetic algorithm (GA) as a potential tool for tracking a user’s energy balance and predicting possible calorie intake required to meet daily calorie needs for obesity management. The algorithm takes the users’ input information on desired foods which are selected from a database and extracted records of users on cholesterol level, diabetes status, and level of physical activity, to predict possible meals required to meet the users need. The micro- and macronutrients of food content are used for the computation and prediction of the potential foods required to meet the daily calorie needs. The functionality and performance of the model were tested using a sample of 30 volunteers from the University of Ghana. Results revealed that the model was able to predict both glycemic and non-glycemic foods based on the condition of the user as well as the macro- and micronutrients requirements. Moreover, the system is able to adequately track the progress of the user’s weight loss over time, daily nutritional needs, daily calorie intake, and predictions of meals that must be taken to avoid compromising their health. The proposed system can serve as a useful resource for individuals, dieticians, and other health management personnel for managing obesity, patients, and for training students in fields of dietetics and consumer science.http://dx.doi.org/10.1155/2021/6624057 |
| spellingShingle | Sylvester M. Sefa-Yeboah Kwabena Osei Annor Valencia J. Koomson Firibu K. Saalia Matilda Steiner-Asiedu Godfrey A. Mills Development of a Mobile Application Platform for Self-Management of Obesity Using Artificial Intelligence Techniques International Journal of Telemedicine and Applications |
| title | Development of a Mobile Application Platform for Self-Management of Obesity Using Artificial Intelligence Techniques |
| title_full | Development of a Mobile Application Platform for Self-Management of Obesity Using Artificial Intelligence Techniques |
| title_fullStr | Development of a Mobile Application Platform for Self-Management of Obesity Using Artificial Intelligence Techniques |
| title_full_unstemmed | Development of a Mobile Application Platform for Self-Management of Obesity Using Artificial Intelligence Techniques |
| title_short | Development of a Mobile Application Platform for Self-Management of Obesity Using Artificial Intelligence Techniques |
| title_sort | development of a mobile application platform for self management of obesity using artificial intelligence techniques |
| url | http://dx.doi.org/10.1155/2021/6624057 |
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