A Hybrid E-nose System based on Metal Oxide Semiconductor Gas Sensors and Compact Colorimetric Sensors
2021
Commercial metal-oxide semiconductor (MOS) gas sensors have been widely used by recent studies as detection units of electronic noses (e-nose) in various applications including disease diagnosis. However, the enoses employing the MOS sensors can only discriminate a limited number of odor groups due to their poor selectivity. Preliminary studies have shown that the selectivity of the MOS sensors can be enhanced by jointly integrating with other sensory units such as QCM or potentiometric sensors, which, however, involves complex interface circuitry and measurement procedures. In contrast, this paper presents a hybrid electronic nose that combines olfactory information from an MOS sensor array together with a compact paperbased colorimetric sensor array which is simpler and easier to utilize. The proposed system employs total 8 MOS sensors, and the compact paper-based colorimetric sensors are fabricated with indicator dyes such as phenol red, methyl red, and methylene blue. Color profiles of the paper-based sensors are captured using a USB-microscope and the alterations of the dyes during the gas exposure are monitored. The improvement of the system performance in classifying six volatile organic compounds (VOC) are investigated by comparing the classification results of the system with and without the colorimetric sensors. The measurement data from both sensor arrays are mapped to the feature space using principal component analysis (PCA) for pattern extraction. It was confirmed that pattern separation among the target VOCs could be improved based on data fusion of these two sensor arrays. This hybrid e-nose system may be useful for improvement of VOC classification performance.
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