K M, Abubeker and Ramasamy, Ramani and Krishnamoorthy, Raja and Gogula, Sreenivasulu and .S, Baskar and Muthu, Sathish and Chellamuthu, Girinivasan and Subramaniam, Kamalraj (2024) Internet of Things enabled open source assisted real-time blood glucose monitoring framework. Scientific Reports, 14. ISSN 2045-2322
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Abstract
Regular monitoring of blood glucose levels is essential for the management of diabetes and the development of appropriate treatment protocols. The conventional blood glucose (BG) testing have an intrusive technique to prick the finger and it can be uncomfortable when it is a regular practice. Intrusive procedures, such as fingerstick testing has negatively influencing patient adherence. Diabetic patients now have an exceptional improvement in their quality of life with the development of cutting-edge sensors and healthcare technologies. intensive care unit (ICU) and pregnant women also have facing challenges including hyperglycemia and hypoglycemia. The worldwide diabetic rate has incited to develop a wearable and accurate non-invasive blood glucose monitoring system. This research developed an Internet of Things (IoT) - enabled wearable blood glucose monitoring (iGM) system to transform diabetes care and enhance the quality of life. The TTGOT-ESP32 IoT platform with a red and near-infrared (R-NIR) spectral range for blood glucose measurement has integrated into this wearable device. The primary objective of this gadget is to provide optimal comfort for the patients while delivering a smooth monitoring experience. The iGM gadget is 98.82 % accuracy when used after 10 hours of fasting and 98.04 % accuracy after 2 hours of breakfast. The primary objective points of the research were continuous monitoring, decreased risk of infection, and improved quality of life. This research contributes to the evolving field of IoT-based healthcare solutions by streaming real-time glucose values on AWS IoT Core to empower individuals with diabetes to manage their conditions effectively. The iGM Framework has a promising future with the potential to transform diabetes management and healthcare delivery.
Item Type: | Article |
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Subjects: | Artificial Intelligence |
Divisions: | Information Technology |
Depositing User: | sathish Muthu |
Date Deposited: | 01 Jul 2024 12:46 |
Last Modified: | 01 Jul 2024 14:50 |
URI: | https://ir.orthopaedicresearchgroup.com/id/eprint/290 |