Anesthetic level prediction using a QCM based E-nose.
Anesthetic level measurement is a real time process. This paper presents a new method to measure anesthesia level in surgery rooms at hospitals using a QCM based E-Nose. The E-Nose system contains an array of eight different coated QCM sensors. In this work, the best linear reacting sensor is selected from the array and used in the experiments. Then, the sensor response time was observed about 15 min using classic method, which is impractical for on-line anesthetic level detection during a surgery. Later, the sensor transition data is analyzed to reach a decision earlier than the classical method. As a result, it is found out that the slope of transition data gives valuable information to predict the anesthetic level. With this new method, we achieved to find correct anesthetic levels within 100 s.
Saraoğlu
H M
HM
Electrical and Electronics Engineering Dept., Dumlupinar University, Merkez Kampus, Tavsanli Yolu 12 Km., Kütahya 43100, Turkey.
Ozmen
A
A
Ebeoğlu
M A
MA
D000768:Anesthesia, General / Q000295:instrumentation* / Q000379:methods*; D018685:Anesthetics, Inhalation / Q000008:administration & dosage / Q000032:analysis*; D015374:Biosensing Techniques / Q000295:instrumentation* / Q000379:methods; D003460:Crystallization; D004305:Dose-Response Relationship, Drug; D006801:Humans; D008738:Methyl Ethers / Q000008:administration & dosage / Q000032:analysis*; D016571:Neural Networks, Computer; D011791:Quartz / Q000737:chemistry; D000077149:Sevoflurane
D018685:Anesthetics, Inhalation; D008738:Methyl Ethers; D011791:Quartz; D000077149:Sevoflurane