Electronic Nose System Based on Quartz Crystal Microbalance Sensor for Blood Glucose and HbA1c Levels From Exhaled Breath Odor

It is known that the rate of acetone in human breath changes in diabetics. The organs in the human body produce different gases. During cleaning of the blood, which is transmitted to the lungs and into the blood gases, the breath passes through the alveoli. Human breath acetone concentration is very...

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Bibliographic Details
Published in:IEEE sensors journal 2013-11, Vol.13 (11), p.4229-4235
Main Authors: Saraoglu, Hamdi Melih, Selvi, Ali Osman, Ebeoglu, M. Ali, Tasaltin, Cihat
Format: Article
Language:English
Subjects:
Breath
Breath tests
concentrator
diabetes
electronic nose
Glucose
HbA1c
neural network
Neural networks
QCM sensor
radial function
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Summary:It is known that the rate of acetone in human breath changes in diabetics. The organs in the human body produce different gases. During cleaning of the blood, which is transmitted to the lungs and into the blood gases, the breath passes through the alveoli. Human breath acetone concentration is very low (0.1-10 ppm). This paper aims to determine human blood glucose and HbA1c levels from exhaled breath as a non-invasive method with the help of an electronic nose system based on quartz crystal microbalance (QCM) sensors. The amount of acetone vapor, which is the marker of blood glucose, is 0.1-10 ppm in human expiration. Data of the QCM sensor used in the electronic nose are compared against glucose and HbA1c parameters in blood by using a radial basis function neural network (RBFNN). When breath data are implemented to the RBFNN, the average accuracy rate is 83.03% and 74.76% for HbA1c parameter predictions and glucose parameter predictions, respectively.
ISSN:1530-437X
1558-1748
DOI:10.1109/JSEN.2013.2265233