IoT Enabled Non-Invasive Detection and Classification of Diabetes using Breath Acetone

Authors : Shahina M, Anusree L

Volume/Issue : Volume 2 - 2017, Issue 12 - December

Google Scholar :

Scribd :

Thomson Reuters ResearcherID :

Diabetes is a metabolic disease that is characterized by high glucose level in the blood. It is a major problem affecting millions of people nowadays. Regular testing and accurate determination of glucose levels is essential for diagnosis and treatment of diabetes. Though the test involving the collection of blood sample from finger pricking may not pose any risk to a healthy adult, but it can be very painful to the diabetic patients. A noninvasive, accurate, easy-to-use and low cost diagnostic tool for diabetes is on high demand. Acetone in the exhaled breath can be estimated for the detection of blood glucose levels. Artificial Neural Network can be used to calculate the glucose levels. It is a non-invasive technique that measure blood glucose levels and the discomfort to the patients can be minimized. Finally, to provide a global connectivity Internet of things can be enabled.


Paper Submission Last Date
31 - May - 2023

Paper Review Notification
In 1-2 Days

Paper Publishing
In 2-3 Days

Video Explanation for Published paper

Never miss an update from Papermashup

Get notified about the latest tutorials and downloads.

Subscribe by Email

Get alerts directly into your inbox after each post and stay updated.

Subscribe by RSS

Add our RSS to your feedreader to get regular updates from us.