ArticleSensors (Basel, Switzerland)2025
Quantification of Volatile Compounds in Mixtures Using a Single Thermally Modulated MOS Gas Sensor with PCA-ANN Data Processing.
Article in Sensors (Basel, Switzerland), 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.
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Who cites it
2 citing papers in PubMed.
- Multi-Scale Temporal-Dependency Learning for Single-Sensor Gas Classification.Sensors (Basel, Switzerland) · 2026Article
- Rapid Electrochemical Profiling of Fecal Short-Chain Fatty Acids Using Esterification/Dissociation Fingerprints and Artificial Neural Networks.Biosensors · 2026Article
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Authors and funding
1 author.
Funding
Abstract
Recent research efforts have focused on improving the performance of metal-oxide semiconductor (MOS) gas sensors through their thermal modulation using integrated heaters. This approach allows us to enhance the selectivity of measurements; however, the main challenge with this amelioration lies in interpreting the sensor response, which takes the form of complex patterns that require the application of advanced signal processing techniques. This study introduces a methodology for the quantitative determination of volatile compounds (ethanol and methanol at various concentrations ranging from 31 to 2000 ppm for each of these compounds) in mixtures using a single thermally modulated MOS gas sensor. The recorded responses of the detector were interpreted by combining two signal processing techniques: principal component analysis (PCA) for feature extraction, and artificial neural networks (ANNs) for predicting the levels of the tested volatile components. The proposed methodology demonstrated satisfactory performance achieving R
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