Determination of glucose and Hba1c values in blood from human breath by using Radial Basis Function Neural Network via electronic nose

Author

Saraoglu, Hamdi Melih ; Selvi, Ali Osman

Author_Institution

Elektrik Elektron. Muhendisligi, Dumlupinar Univ., Kutahya, Turkey

fYear

2014

fDate

16-17 Oct. 2014

Firstpage

1

Lastpage

4

Abstract

In this study, it is aimed to be determined glucose and HbA1c values in blood from the human breath by using electronic nose. It is known that the rate of acetone in human breath changes in diabetes. Electronic nose data is compared against glucose and HbA1c parameters in blood by using Radial Basis Function Neural Network. The minimum error rate is %24,62 for glucose parameter predictions and the minimum error rate is %14,92 for HbA1c parameter predictions. The work has been conducted in the scope of TUBITAK Project, No: 104E053.

Keywords

biomedical measurement; blood; diseases; electronic noses; radial basis function networks; sugar; Hba1c values; acetone; blood; diabetes; electronic nose data; glucose determination; glucose parameter prediction; human breath; radial basis function neural network; Actuators; Biosensors; Blood; Electronic noses; Gas detectors; Sugar; Diabetes; Electronic Nose; Glucose; HbA1c; Neural Network; QCM; Radial Function;

fLanguage

English

Publisher

ieee

Conference_Titel

Biomedical Engineering Meeting (BIYOMUT), 2014 18th National

Conference_Location

Istanbul

Type

conf

DOI

10.1109/BIYOMUT.2014.7026340

Filename

7026340