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Sunderland Repository records the research produced by the University of Sunderland including practice-based research and theses.

IoT based expert system for diabetes diagnosis and insulin dosage calculation

Valsalan, Prajoona, Hasan, Najam Ul, Farooq, Umer, Zghaibeh, Manaf and Baig, Imran (2022) IoT based expert system for diabetes diagnosis and insulin dosage calculation. Healthcare, 11 (1). pp. 1-12. ISSN 2227-9032

Item Type: 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.

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Uncontrolled Keywords: IoT; fuzzy system; diabetes diagnosis and treatment; remote health
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Depositing User: Umer Farooq


Item ID: 17490
Identification Number:
ISSN: 2227-9032
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Catalogue record

Date Deposited: 28 Mar 2024 13:37
Last Modified: 28 Mar 2024 13:45


Author: Prajoona Valsalan
Author: Najam Ul Hasan
Author: Umer Farooq
Author: Manaf Zghaibeh
Author: Imran Baig

University Divisions

Faculty of Technology


Engineering > Electrical Engineering

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