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• El Barbri, N
• Duran, C
• Brezmes, J
• Cañellas, N
• Ramírez, JLuis
• Bouchikhi, B
• Llobet, E
• [+] on Google Scholar
• El Barbri, N
• Duran, C
• Brezmes, J
• Cañellas, N
• Ramírez, JLuis
• Bouchikhi, B
• Llobet, E
• [+] on PubMed
• El Barbri, N
• Duran, C
• Brezmes, J
• Cañellas, N
• Ramírez, JLuis
• Bouchikhi, B
• Llobet, E

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Sensors 2008, 8(11), 7369-7379; doi:10.3390/s8117369

Article

Selectivity Enhancement in Multisensor Systems Using Flow Modulation Techniques

Noureddine El Barbri¹ , Cristhian Duran^2,3 , Jesús Brezmes³ , Nicolau Cañellas³ , José Luis Ramírez³ , Benachir Bouchikhi¹  and Eduard Llobet^3,*

¹ Sensor Electronic & Instrumentation Group, Faculty of Sciences, Physics Department, Moulay Ismaïl University, Meekness, Morocco ² Department of Electronic Engineering, University of Pamplona, Pamplona, Colombia ³ MINOS, Department of Electronic Engineering, University Rovira i Virgili, Tarragona, Spain

* Author to whom correspondence should be addressed.

Received: 22 May 2008; in revised form: 11 November 2008 / Accepted: 11 November 2008 / Published: 19 November 2008

(This article belongs to the Section Chemical Sensors)

Download PDF Full-Text [121 KB, uploaded 19 November 2008 10:23 CET]

Abstract: In this paper, the use of a new technique to obtain transient sensor information is introduced and its usefulness to improve the selectivity of metal oxide gas sensors is discussed. The method is based on modulating the flow of the carrier gas that brings the species to be measured into the sensor chamber. In such a way, the analytes’ concentration at the surface of the sensors is altered. As a result, reproducible patterns in the sensor response develop, which carry important information for helping the sensor system, not only to discriminate among the volatiles considered but also to semi-quantify them. This has been proved by extracting features from sensor dynamics using the discrete wavelet transform (DWT) and by building and validating support vector machine (SVM) classification models. The good results obtained (100% correct identification among 5 volatile compounds and nearly a 89% correct simultaneous identification and quantification of these volatiles), which clearly outperform those obtained when the steady-state response is used, prove the concept behind flow modulation.

Keywords: Metal oxide gas sensor; flow modulation; support vector machine; wavelet transform

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