Discrimination and characterization of breath from smokers and non-smokers via electronic nose and GC/MS analysis

The objective of this study was to prove the general applicability of an electronic nose for analyzing exhaled breath considering the dependency on smoking. At first, odor compounds from spices (n=6) were detected via the electronic nose and further characterized and classified with gas chromatography/ mass spectrometry to demonstrate the principle ability of the electronic nose. Then, the exhaled breath from smokers and non-smokers were analyzed to prove the influence of smoking on breath analyses with the electronic nose. The exhaled breath was sampled from 11 smokers and 11 non-smokers in a special sampling bag with the mounted sensor chip of the electronic nose. Additionally, solid phase micro-extraction (SPME) technique was established for detection of the specific chemical compounds with gas chromatography and mass spectrometry (GC/MS). For analyses of the sensor signals the principle component analysis (PCA) was applied and the groups were differentiated by linear discriminant function analysis. In accordance to the discrimination between the different spices and between smokers and non-smokers the PCA analysis leads to an optimum accuracy of 100%. The results of this study show that an electronic nose has the ability to detect different changes of odor components and provides separation of smoking side effects in smelling different diseases.