Please use this identifier to cite or link to this item: http://repository.iiitd.edu.in/xmlui/handle/123456789/1442
Title: Continuous glucose monitoring
Authors: Sahu, Sahil
Jalote, Pankaj (Advisor)
Sethi, Tavpritesh (Advisor)
Keywords: PPG
GSR
diabetes
blood glucose
signal processing
machine learning
Issue Date: 29-Nov-2023
Publisher: IIIT-Delhi
Abstract: Diabetes is a chronic illness that affects millions of people worldwide and requires regular monitoring of a patient’s blood glucose level. Currently, blood glucose is monitored by a minimally invasive process where a small droplet of blood is extracted and passed to a glucometer—however, this process is uncomfortable for the patient. In this project, a noninvasive technique is investigated for the quantitative estimation of glucose levels in the blood based on Photoplethysmography (PPG) signal, Galvanic Skin Response, and other biosignals.
URI: http://repository.iiitd.edu.in/xmlui/handle/123456789/1442
Appears in Collections:Year-2023

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