Determination of glucose and Hba1c values in blood from human breath by using Radial Basis Function Neural Network via electronic nose ̄nsan nefesinden kandaki glikoz ve HbA1c deʇerlerinin elektronik burun yardi{dotless}mi{dotless}yla radyal fonksiyon tabanli{dotless} yapay sinir aʇi{dotless} kullani{dotless}larak belirlenmesi

Saraoʇlu H. M., SELVİ A. O.

2014 18th National Biomedical Engineering Meeting, BIYOMUT 2014, İstanbul, Türkiye, 16 - 17 Ekim 2014 identifier

  • Yayın Türü: Bildiri / Tam Metin Bildiri
  • Doi Numarası: 10.1109/biyomut.2014.7026340
  • Basıldığı Şehir: İstanbul
  • Basıldığı Ülke: Türkiye
  • Anahtar Kelimeler: Diabetes, Electronic Nose, Glucose, HbA1c, Neural Network, QCM, Radial Function
  • Bilecik Şeyh Edebali Üniversitesi Adresli: Hayır

Özet

© 2014 IEEE.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.