HYBRID SENSOR BASED E-NOSE FOR LUNG CANCER DIAGNOSIS

Volatile Organic Compounds in human breath can be indicator of certain diseases. In this work an Electronic Nose system was developed in order to analyze human breath about diagnose whether people with lung cancer or not. In this Electronic Nose system, 8 Metal Oxide Semiconductor gas sensors and 14 Quartz Crystal Microbalance sensors were used. All sensors used in this system are sensitive to Volatile Organic Compounds related with lung cancer. Data obtained by using this system were first preprocessed. Then features were extracted from data for increase success of classification. In order to remove unnecessary features, Principal Component Analysis was used. Last, extracted features were classified with k-Nearest Neighbours and Support Vector Machines methods.