Krishnakumar, S. and Umashankar, G. and Lumen, Christy V. and Vikas, Vikas and Hemalatha, R.J. (2022) Management of Diabetes Mellitus (DM) for Children and Adults Based on Internet of Things (IoT): Healthcare Transformation. In: The Internet of Medical Things (IoMT). Wiley, pp. 207-223. ISBN 9781119769200
Full text not available from this repository. (Request a copy)Abstract
Diabetes mellitus (DM) is a metabolic disorder described by hyperglycemia, because of imperfections in secretion or potential activity of insulin. Diabetes disorders are more common to all groups of people due to various factors. The concept of the study is to design and develop an assistant system for DM for children and adults using the Internet of Things (IoT). The prototype device contains microcontrollers to update the real parameters of the patients to the IoT cloud database. The sensors utilized here are the MAX30100 to gauge the SPO2 and the non‐invasive glucose sensor used to quantify the blood glucose level and the temperature sensor used to gauge the constant temperature of the patients. The chatbot will transmit data to interact about the patient's health conditions. An advanced assistive device to help manage diabetes in children and adults to regulate in their daily lives for better treatment. The main target of this project is to prevent children from harmful conditions of diabetes with help of technical things like robotic assistant and emergency alarm. The present study used to monitor blood glucose level, body temperature, pulse rate, and SPO2 effectively. The data recorded by the device is directly sent to the doctors through the internet. The doctors can monitor the patient from medical centres continuously. Based on the patient's health parameters and blood glucose level, doctors can suggest the prescription to the nurses or caretakers for the patient through the IoT.
Item Type: | Book Section |
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Subjects: | Biomedical Engineering > Biomedical Engineering Design |
Divisions: | Biomedical Engineering |
Depositing User: | Mr IR Admin |
Date Deposited: | 07 Oct 2024 11:19 |
Last Modified: | 07 Oct 2024 11:19 |
URI: | https://ir.vistas.ac.in/id/eprint/9364 |