Title :
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
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;
Conference_Titel :
Biomedical Engineering Meeting (BIYOMUT), 2014 18th National
Conference_Location :
Istanbul
DOI :
10.1109/BIYOMUT.2014.7026340
