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Non-Contact Measurement of Blood Glucose based on Artificial Neural Network

by Bagas Satya Dian Nugraha, Faghanie Sugarizka
journal cover thumbnail

International Journal of Computer Applications
Foundation of Computer Science (FCS), NY, USA
Volume 76 - Number 13
Year of Publication: 2013
Authors: Bagas Satya Dian Nugraha, Faghanie Sugarizka
10.5120/13309-0848

Bagas Satya Dian Nugraha, Faghanie Sugarizka . Non-Contact Measurement of Blood Glucose based on Artificial Neural Network. International Journal of Computer Applications. 76, 13 ( August 2013), 33-36. DOI=10.5120/13309-0848

@article{ 10.5120/13309-0848,
author = { Bagas Satya Dian Nugraha, Faghanie Sugarizka },
title = { Non-Contact Measurement of Blood Glucose based on Artificial Neural Network },
journal = { International Journal of Computer Applications },
issue_date = { August 2013 },
volume = { 76 },
number = { 13 },
month = { August },
year = { 2013 },
issn = { 0975-8887 },
pages = { 33-36 },
numpages = {9},
url = { https://ijcaonline.org/archives/volume76/number13/13309-0848/ },
doi = { 10.5120/13309-0848 },
publisher = {Foundation of Computer Science (FCS), NY, USA},
address = {New York, USA}
}
%0 Journal Article
%1 2024-02-06T21:45:49.388689+05:30
%A Bagas Satya Dian Nugraha
%A Faghanie Sugarizka
%T Non-Contact Measurement of Blood Glucose based on Artificial Neural Network
%J International Journal of Computer Applications
%@ 0975-8887
%V 76
%N 13
%P 33-36
%D 2013
%I Foundation of Computer Science (FCS), NY, USA
Abstract

Diabetes mellitus is a disease caused by metabolic disorder that result a lack of insulin in human body. Deficiency of the insulin hormone causes abnormal blood sugar level fluctuation. These conditions should be treated appropriately to prevent the occurrence acute metabolic disorder and chronic complication, so an appropriate treatment can be done by medical personal. This paper develops a non-contact device to measure blood sugar level based on Artificial Neural Network (ANN). ANN in this device convert temperature difference between tragus and antihelix to an index of blood glucose. Tragus and antihelix are the name of two sections of human ear. Using infra red sensor that called thermopile, temperature of these section is measure. So there is no contact between human body and the device. Weight and bias of ANN determine by Back Propagation trained using data from conventional measurement. Experiment result using Matlab Simulink and Peripheral Component Interconnect (PCI) interfacing showed that the device can measured blood glucose and can be used for measurement easier, faster and less intimidating as occurs in conventional measurements.

References
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  4. Ganesan, N. Application of Neural Networks in Diagnosing Cancer Disease Using Demographic Data (PDF). International Journal of Computer Applications. Retrieved 2013-7-15.
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Index Terms

Computer Science
Information Sciences

Keywords

blood glucose level non-contact measurement tragus and antihelix artificial neural network

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