Search results for "Electronic nose"
showing 3 items of 33 documents
Odorant-binding protein-based optoelectronic tongue and nose for sensing volatile organic compounds
2019
International audience; We developed an array of odorant-binding protein mutants with various binding properties. The same design is suitable for the detection and identification of volatile organic compounds (VOCs) both in the liquid phase and in the gas phase by surface plasmon resonance imaging. The obtained optoelectronic tongue is highly selective at low concentrations of VOCs with a low detection limit, but a narrow linear range. In comparison, the optoelectronic nose gives a much higher signal to noise ratio, but the discrimination of VOCs from different chemical classes requires kinetic data to get rid of non-specific signals. This work shows that these optoelectronic tongue and nos…
Use of electronic nose to determine defect percentage in oils. Comparison with sensory panel results
2010
Abstract An electronic nose based on an array of 6 metal oxide semiconductor sensors was used, jointly with linear discriminant analysis (LDA) and artificial neural network (ANN) method, to classify oils containing the five typical virgin olive oil (VOO) sensory defects (fusty, mouldy, muddy, rancid and winey). For this purpose, these defects, available as single standards of the International Olive Council, were added to refined sunflower oil. According to the LDA models and the ANN method, the defected samples were correctly classified. On the other hand, the electronic nose data was used to predict the defect percentage added to sunflower oil using multiple linear regression models. All …
Modular Point-of-Care Breath Analyzer and Shape Taxonomy-Based Machine Learning for Gastric Cancer Detection
2022
Background: Gastric cancer is one of the deadliest malignant diseases, and the non-invasive screening and diagnostics options for it are limited. In this article, we present a multi-modular device for breath analysis coupled with a machine learning approach for the detection of cancer-specific breath from the shapes of sensor response curves (taxonomies of clusters). Methods: We analyzed the breaths of 54 gastric cancer patients and 85 control group participants. The analysis was carried out using a breath analyzer with gold nanoparticle and metal oxide sensors. The response of the sensors was analyzed on the basis of the curve shapes and other features commonly used for comparison. These f…