Detection of seasonal allergic rhinitis from exhaled breath VOCs using an electronic nose based on an array of chemical sensors

In this study, we investigate for the first time the ability of an electronic nose (E-nose) based on an array of chemical sensors to discriminate between breath Volatile Organic Compounds (VOCs) that characterize patients with Seasonal Allergic Rhinitis (SAR) and healthy states. To reach this aim, multivariate analysis including Principal Component Analysis (PCA), Hierarchical Cluster Analysis (HCA) and Support Vector Machines (SVMs) were applied for database as an alternative tools for the resolution of complex classification situations. The preliminary results reveal that VOC-patterns of exhaled breath were accurately discriminated patients with SAR from healthy controls. These findings indicate that the E-nose may succeed as a non-invasive diagnostic tool, low cost and rapid technique for breath analysis.