J. Gutiérrez

Differentiation of red wines using an electronic nose based on surface acoustic wave devices

An electronic nose, utilizing the principle of surface acoustic waves (SAW), was used to differentiate among different wines of the same variety of grapes which come from the same cellar. The electronic nose is based on eight surface acoustic wave sensors, one is a reference sensor and the others are coated by different polymers by spray coating technique. Data analysis was performed by two pattern recognition methods; principal component analysis (PCA) and probabilistic neuronal network (PNN). The results showed that electronic nose was able to identify the tested wines.

Analysis of grape variety and denomination of origin of several wines with an artificial nose

In this work we present the analysis and classification of different wines depending simultaneously on their denomination of origin and grape variety. We explain the array sensor system and the volatile compounds extraction method used to build the electronic nose. We also review the wine samples and their characteristics. Then with Principal Component Analysis (PCA) we inspect the data and a Probabilistic Neural Network (PNN) successfully classify the samples according to their denomination of origin and grape variety.

Detection of stress through sweat analysis with an electronic nose

Cortisol and adrenaline are two hormones associated with stress. Therefore, their detection is important for applications in medicine and security. We propose to detect the presence of these chemical compounds in the bodys sweat by electronic noses with resistive sensors as a non-invasive method. Low concentrations of cortisol (5 ¿M ¿ 50 ¿M) and adrenaline (0.3 mM ¿ 5.5 mM) have been measured. Furthermore, our electronic nose have been able to distinguish between sweat from physical stress and quiet situation by two pattern recognition techniques as principal component analysis (PCA) and probabilistic neuronal network (PNN), being the prediction rate of the network 85%.