• DocumentCode
    104771
  • Title

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

  • Author

    Saraoglu, Hamdi Melih ; Selvi, Ali Osman ; Ebeoglu, Mehmet Ali ; Tasaltin, Cihat

  • Author_Institution
    Dept. of Electr. & Electron. Eng., Dumlupinar Univ., Kutahya, Turkey
  • Volume
    13
  • Issue
    11
  • fYear
    2013
  • fDate
    Nov. 2013
  • Firstpage
    4229
  • Lastpage
    4235
  • Abstract
    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.
  • Keywords
    blood; electronic noses; medical disorders; neural nets; organic compounds; pneumodynamics; quartz crystal microbalances; HbA1c levels; QCM sensors; RBFNN; acetone rate; acetone vapor; alveoli; blood cleaning; blood gases; blood glucose; diabetics; electronic nose system; exhaled breath odor; human breath; human expiration; lungs; quartz crystal microbalance sensor; radial basis function neural network; Breath; HbA1c; QCM sensor; concentrator; diabetes; electronic nose; glucose; neural network; radial function;
  • fLanguage
    English
  • Journal_Title
    Sensors Journal, IEEE
  • Publisher
    ieee
  • ISSN
    1530-437X
  • Type

    jour

  • DOI
    10.1109/JSEN.2013.2265233
  • Filename
    6531672