Detection of sevoflurane anesthetic levels using QCM-SSC sensor array and artifical neural network

DETECTION OF SEVOFLURANE ANESTHETIC LEVELS USING QCM-SSCSENSOR ARRAY AND ARTIFICAL NEURAL NETWORKBurçak EDINElectric-Electronic Engineering, M.S.Thesis, 2007Thesis Supervisor: Asist. Prof. Hamdi Melih SARAOGLUABSTRACTIn this thesis, we have examined for the response of the e-nose implemented with sensorarray of Quatrz Chrystal Microbalance (QCM). During the study, the QCM based e-nose wasused to collect sensor data, and an Artificial Neural Network (ANN) was trained with this data.After that, the trained ANN is tasted with random data. As a result, acceptable values have beenobtained.The work has been conducted in the scopes of TUBITAK Project, No: 104E053:?Diagnosing System Design for Medical Applications Using by QCM-SSC Gas Sensor Array?and Scientific Search Project of Dumlupınar University, No: 2004-6: ?Real Time Detection ofthe Anesthetic Gases by Using PC(PIC) & QCM Sensor Array?Key Words: E-nose, Level (density) of the anesthesia, QCM sensor, Sevoflurane