Discrimination of volatile organic compounds using a sensor array via a rapid method based on linear discriminant analysis

Abstract

We investigated a discriminant method for volatile organic compounds (VOCs) in exhaled breath under contaminant air as well as purified air conditions using an array of multiple semiconductive gas sensors and the linear discriminant analysis (LDA) space. We analyzed the sensor signals of resistance changes employing our developed discriminant method in the LDA space. In particular, the sensor resistances at intervals at which a resistance change occurred owing to target gas introduction were used as test data. The linear discriminant (LD) scores from the test data in the two-dimensional (2-D) LDA space gradually shifted in the direction of the correct LD scores of the training data. Therefore, the target gases were discriminated using the angle of locus of the test data in the 2-D LDA space. Our results proved the viability of the proposed method to discriminate target gases under contaminant air conditions.