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IoT Based Expert System for Diabetes Diagnosis and Insulin Dosage Calculation
High blood glucose levels are the defining characteristic of diabetes. Uncontrolled blood glucose levels in diabetic patients might result in mortality. As a result, there is a dire need to control blood glucose levels by constantly monitoring them and delivering the appropriate amount of insulin. H...
Autores principales: | , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
MDPI
2022
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9819254/ https://www.ncbi.nlm.nih.gov/pubmed/36611472 http://dx.doi.org/10.3390/healthcare11010012 |
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author | Valsalan, Prajoona Hasan, Najam Ul Farooq, Umer Zghaibeh, Manaf Baig, Imran |
author_facet | Valsalan, Prajoona Hasan, Najam Ul Farooq, Umer Zghaibeh, Manaf Baig, Imran |
author_sort | Valsalan, Prajoona |
collection | PubMed |
description | High blood glucose levels are the defining characteristic of diabetes. Uncontrolled blood glucose levels in diabetic patients might result in mortality. As a result, there is a dire need to control blood glucose levels by constantly monitoring them and delivering the appropriate amount of insulin. However, insulin consumption is affected by several variables, including age, calorific intake, and body weight. The patient must see the doctor on a regular basis in order to determine the appropriate dose. Nonetheless, hospital facilities are finding it increasingly difficult to treat patients as the number of patients rises; thus, the healthcare industry is searching for an efficient method that can alleviate their burden by assisting patients with chronic conditions through remote patient care. In this work, we have developed an expert system to provide remote treatment for diabetic patients. Our expert system consists of two distinct components: one for the patient and one for the hospital. The sole requirement for the patient will be a wearable device that captures and transmits all relevant data to the cloud. On the hospital side, there should be a system in place to process that data in the cloud. The system employs a fuzzy system to handle data in two stages. A fuzzy system is initially employed to identify whether or not a patient is diabetic. In the second stage, a fuzzy system is utilized to determine the insulin dosage for a diabetic patient. Using sensors and the ESP8266 platform, we have developed a prototype of patient-side hardware. The MATLAB fuzzy toolbox is used for the processing part, which includes fuzzy systems, and the results of the MATLAB analysis are presented in the form of simulation results to demonstrate the accuracy of the proposed system in terms of determining insulin dosage. The results of the simulation using the fuzzy toolbox for the insulin dose of the diabetic patient are significantly close to the amount of dosage prescribed by the endocrinologist. |
format | Online Article Text |
id | pubmed-9819254 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2022 |
publisher | MDPI |
record_format | MEDLINE/PubMed |
spelling | pubmed-98192542023-01-07 IoT Based Expert System for Diabetes Diagnosis and Insulin Dosage Calculation Valsalan, Prajoona Hasan, Najam Ul Farooq, Umer Zghaibeh, Manaf Baig, Imran Healthcare (Basel) Article High blood glucose levels are the defining characteristic of diabetes. Uncontrolled blood glucose levels in diabetic patients might result in mortality. As a result, there is a dire need to control blood glucose levels by constantly monitoring them and delivering the appropriate amount of insulin. However, insulin consumption is affected by several variables, including age, calorific intake, and body weight. The patient must see the doctor on a regular basis in order to determine the appropriate dose. Nonetheless, hospital facilities are finding it increasingly difficult to treat patients as the number of patients rises; thus, the healthcare industry is searching for an efficient method that can alleviate their burden by assisting patients with chronic conditions through remote patient care. In this work, we have developed an expert system to provide remote treatment for diabetic patients. Our expert system consists of two distinct components: one for the patient and one for the hospital. The sole requirement for the patient will be a wearable device that captures and transmits all relevant data to the cloud. On the hospital side, there should be a system in place to process that data in the cloud. The system employs a fuzzy system to handle data in two stages. A fuzzy system is initially employed to identify whether or not a patient is diabetic. In the second stage, a fuzzy system is utilized to determine the insulin dosage for a diabetic patient. Using sensors and the ESP8266 platform, we have developed a prototype of patient-side hardware. The MATLAB fuzzy toolbox is used for the processing part, which includes fuzzy systems, and the results of the MATLAB analysis are presented in the form of simulation results to demonstrate the accuracy of the proposed system in terms of determining insulin dosage. The results of the simulation using the fuzzy toolbox for the insulin dose of the diabetic patient are significantly close to the amount of dosage prescribed by the endocrinologist. MDPI 2022-12-21 /pmc/articles/PMC9819254/ /pubmed/36611472 http://dx.doi.org/10.3390/healthcare11010012 Text en © 2022 by the authors. https://creativecommons.org/licenses/by/4.0/Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/). |
spellingShingle | Article Valsalan, Prajoona Hasan, Najam Ul Farooq, Umer Zghaibeh, Manaf Baig, Imran IoT Based Expert System for Diabetes Diagnosis and Insulin Dosage Calculation |
title | IoT Based Expert System for Diabetes Diagnosis and Insulin Dosage Calculation |
title_full | IoT Based Expert System for Diabetes Diagnosis and Insulin Dosage Calculation |
title_fullStr | IoT Based Expert System for Diabetes Diagnosis and Insulin Dosage Calculation |
title_full_unstemmed | IoT Based Expert System for Diabetes Diagnosis and Insulin Dosage Calculation |
title_short | IoT Based Expert System for Diabetes Diagnosis and Insulin Dosage Calculation |
title_sort | iot based expert system for diabetes diagnosis and insulin dosage calculation |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9819254/ https://www.ncbi.nlm.nih.gov/pubmed/36611472 http://dx.doi.org/10.3390/healthcare11010012 |
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