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Novel convolution-based signal processing techniques for an artificial olfactory mucosa

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Gardner, Julian W. and Taylor, J. E. (James E.). (2009) Novel convolution-based signal processing techniques for an artificial olfactory mucosa. IEEE Sensors Journal, Vol.9 (No.8). pp. 929-935. ISSN 1530-437X

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Official URL: http://dx.doi.org/10.1109/JSEN.2009.2024856

Abstract

As our understanding of the human olfactory system has grown, so has our ability to design artificial devices that mimic its functionality, so called electronic noses (e-noses). This has led to the development of a more sophisticated biomimetic system known as an artificial olfactory mucosa (e-mucosa) that comprises a large distributed sensor array and artificial mucous layer. In order to exploit fully this new architecture, new approaches are required to analyzing the rich data sets that it generates. In this paper, we propose a novel convolution based approach to processing signals from the e-mucosa. Computer simulations are performed to investigate the robustness of this approach when subjected to different real-world problems, such as sensor drift and noise. Our results demonstrate a promising ability to classify odors from poor sensor signals.

Item Type:	Journal Article
Subjects:	T Technology > TK Electrical engineering. Electronics Nuclear engineering
Divisions:	Faculty of Science > Engineering
Library of Congress Subject Headings (LCSH):	Signal processing -- Digital techniques, Convolutions (Mathematics), Olfactory mucosa -- Research, Chemical detectors -- Research
Journal or Publication Title:	IEEE Sensors Journal
Publisher:	Institute of Electrical and Electronic Engineers
ISSN:	1530-437X
Date:	30 June 2009
Volume:	Vol.9
Number:	No.8
Number of Pages:	7
Page Range:	pp. 929-935
Identification Number:	10.1109/JSEN.2009.2024856
Status:	Peer Reviewed
Publication Status:	Published
Access rights to Published version:	Restricted or Subscription Access
Funder:	Engineering and Physical Sciences Research Council (EPSRC), University of Warwick
Version or Related Resource:	This item was also presented at the Eighth IASTED International Conference on Biomedical Engineering (BIOMED 2011), Innsbruck, Austria, Feb 16 - 18, 2011.
References:	[1] J. W. Gardner and P. N. Bartlett, Electronic Noses: Principles and Applications. Oxford, U.K.: Oxford Univ. Press, 1999. [2] M. A. Ryan et al., “Monitoring space shuttle air quality using the jet propulsion laboratory electronic nose,” IEEE Sensors J., vol. 4, no. 3, pp. 337–347, Jun. 2004. [3] R. C. Young, W. J. Buttner, B. R. Linnell, and R. Ramesham, “Electronic nose for space program applications,” Sens. Actuators B, vol. 93, pp. 7–16, 2003. [4] M. M. Mozell and M. Jagodowicz, “Chromatographic separation of odorants by the nose: Retention times measured across in vivo olfactory mucosa,” Science, vol. 181, pp. 1247–1249, 1973. [5] P. Vroon, Smell: The Secret Seducer. New York: Strauss and Giroux, 1997, p. 28. [6] S. L. Tan, “Smart Chemical Sensing: Towards a Nose-on-a-Chip,” Ph.D. dissertation, Univ. Warwick, School of Engineering, Coventry, U.K., 2005. [7] R. Gutiérrez-Osuna, “Pattern analysis for machine olfaction:Areview,” IEEE Sensors J., vol. 2, no. 3, pp. 189–201, Jun. 2002. [8] A. Perera, T. Yamanaka, A. Gutiérrez-Gálvez, B. Raman, and R. Gutiérrez-Osuna, “A dimensionality-reduction technique inspired by receptor convergence in the olfactory system,” Sens. Actuators B, vol. 116, pp. 17–22, 2006. [9] M. Bicego, G. Tessari, G. Tecchiolli, and M. Bettinelli, “A comparative analysis of basic pattern recognition techniques for the development of small size electronic nose,” Sens. Actuators B, vol. 85, pp. 137–144, 2002. [10] I. I. Hirschman and D. V. Widdler, The Convolution Transform. Princeton, NJ: Princeton Univ. Press, 1955. [11] S. L. Tan, J. A. Covington, J. W. Gardner, and T. C. Pearce, “Finite element simulation of a biomimetic olfactory microsystem for spatio-temporal signal generation,” AsiaSim 2007 Springer, 2007, pp. 216–226.
URI:	http://wrap.warwick.ac.uk/id/eprint/2255