LDA-based vapor recognition using image-formed array sensor response for portable electronic nose

Yoonseok Yang; S. Choi; G. Jeong

doi:10.1007/978-3-642-03882-2_466

LDA-based vapor recognition using image-formed array sensor response for portable electronic nose

Yoonseok Yang^*
, S. Choi
, G. Jeong

^*Corresponding author for this work

Healthcare Information

Seoul National University
Kookmin University

Research output: Contribution to conference › Conference paper › peer-review

5 Scopus citations

Abstract

The efficient formulation of measured data in artificial olfactory system is very important for simplicity, robustness and implementation of the algorithm especially in portable system which has limited resources. In this study, we applied the linear discriminant analysis (LDA) to E-nose measurements formulated in 2 dimensional matrices. The 160 measurements for 8 different vapors using 6 channel sensor array were identified with the accuracy of 98.75%. LDA is one of the most efficient computer vision algorithms to recognize image objects. It maintained the significant features for vapor classification during dimension reduction. This can simplify further processing like storage or transmission. Therefore, the proposed method will help the realization of the ubiquitous or embedded olfactory sensing system.

Original language	English
Title of host publication	World Congress on Medical Physics and Biomedical Engineering
Subtitle of host publication	Image Processing, Biosignal Processing, Modelling and Simulation, Biomechanics
Publisher	Springer Verlag
Pages	1756-1759
Number of pages	4
Edition	4
ISBN (Print)	9783642038815
DOIs	https://doi.org/10.1007/978-3-642-03882-2_466
State	Published - 2009
Event	World Congress on Medical Physics and Biomedical Engineering: Image Processing, Biosignal Processing, Modelling and Simulation, Biomechanics - Munich, Germany Duration: 2009.09.7 → 2009.09.12

Publication series

Name	IFMBE Proceedings
Number	4
Volume	25
ISSN (Print)	1680-0737

Conference

Conference	World Congress on Medical Physics and Biomedical Engineering: Image Processing, Biosignal Processing, Modelling and Simulation, Biomechanics
Country/Territory	Germany
City	Munich
Period	09.09.7 → 09.09.12

UN SDGs

This output contributes to the following UN Sustainable Development Goals (SDGs)

SDG 3 Good Health and Well-being

Keywords

Electrical brain stimulation
Neural stimulation
Rehabilitation
Stroke recovery
ZigBee

Quacquarelli Symonds(QS) Subject Topics

Engineering - Chemical
Biological Sciences

Access to Document

10.1007/978-3-642-03882-2_466

Cite this

Yang, Y., Choi, S., & Jeong, G. (2009). LDA-based vapor recognition using image-formed array sensor response for portable electronic nose. In World Congress on Medical Physics and Biomedical Engineering: Image Processing, Biosignal Processing, Modelling and Simulation, Biomechanics (4 ed., pp. 1756-1759). (IFMBE Proceedings; Vol. 25, No. 4). Springer Verlag. https://doi.org/10.1007/978-3-642-03882-2_466

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title = "LDA-based vapor recognition using image-formed array sensor response for portable electronic nose",

abstract = "The efficient formulation of measured data in artificial olfactory system is very important for simplicity, robustness and implementation of the algorithm especially in portable system which has limited resources. In this study, we applied the linear discriminant analysis (LDA) to E-nose measurements formulated in 2 dimensional matrices. The 160 measurements for 8 different vapors using 6 channel sensor array were identified with the accuracy of 98.75\%. LDA is one of the most efficient computer vision algorithms to recognize image objects. It maintained the significant features for vapor classification during dimension reduction. This can simplify further processing like storage or transmission. Therefore, the proposed method will help the realization of the ubiquitous or embedded olfactory sensing system.",

keywords = "Electrical brain stimulation, Neural stimulation, Rehabilitation, Stroke recovery, ZigBee",

author = "Yoonseok Yang and S. Choi and G. Jeong",

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series = "IFMBE Proceedings",

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edition = "4",

note = "World Congress on Medical Physics and Biomedical Engineering: Image Processing, Biosignal Processing, Modelling and Simulation, Biomechanics ; Conference date: 07-09-2009 Through 12-09-2009",

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Yang, Y, Choi, S & Jeong, G 2009, LDA-based vapor recognition using image-formed array sensor response for portable electronic nose. in World Congress on Medical Physics and Biomedical Engineering: Image Processing, Biosignal Processing, Modelling and Simulation, Biomechanics. 4 edn, IFMBE Proceedings, no. 4, vol. 25, Springer Verlag, pp. 1756-1759, World Congress on Medical Physics and Biomedical Engineering: Image Processing, Biosignal Processing, Modelling and Simulation, Biomechanics, Munich, Germany, 09.09.7. https://doi.org/10.1007/978-3-642-03882-2_466

LDA-based vapor recognition using image-formed array sensor response for portable electronic nose. / Yang, Yoonseok; Choi, S.; Jeong, G.
World Congress on Medical Physics and Biomedical Engineering: Image Processing, Biosignal Processing, Modelling and Simulation, Biomechanics. 4. ed. Springer Verlag, 2009. p. 1756-1759 (IFMBE Proceedings; Vol. 25, No. 4).

Research output: Contribution to conference › Conference paper › peer-review

TY - GEN

T1 - LDA-based vapor recognition using image-formed array sensor response for portable electronic nose

AU - Yang, Yoonseok

AU - Choi, S.

AU - Jeong, G.

PY - 2009

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N2 - The efficient formulation of measured data in artificial olfactory system is very important for simplicity, robustness and implementation of the algorithm especially in portable system which has limited resources. In this study, we applied the linear discriminant analysis (LDA) to E-nose measurements formulated in 2 dimensional matrices. The 160 measurements for 8 different vapors using 6 channel sensor array were identified with the accuracy of 98.75%. LDA is one of the most efficient computer vision algorithms to recognize image objects. It maintained the significant features for vapor classification during dimension reduction. This can simplify further processing like storage or transmission. Therefore, the proposed method will help the realization of the ubiquitous or embedded olfactory sensing system.

AB - The efficient formulation of measured data in artificial olfactory system is very important for simplicity, robustness and implementation of the algorithm especially in portable system which has limited resources. In this study, we applied the linear discriminant analysis (LDA) to E-nose measurements formulated in 2 dimensional matrices. The 160 measurements for 8 different vapors using 6 channel sensor array were identified with the accuracy of 98.75%. LDA is one of the most efficient computer vision algorithms to recognize image objects. It maintained the significant features for vapor classification during dimension reduction. This can simplify further processing like storage or transmission. Therefore, the proposed method will help the realization of the ubiquitous or embedded olfactory sensing system.

KW - Electrical brain stimulation

KW - Neural stimulation

KW - Rehabilitation

KW - Stroke recovery

KW - ZigBee

UR - https://www.scopus.com/pages/publications/77950137703

U2 - 10.1007/978-3-642-03882-2_466

DO - 10.1007/978-3-642-03882-2_466

M3 - Conference paper

AN - SCOPUS:77950137703

SN - 9783642038815

T3 - IFMBE Proceedings

SP - 1756

EP - 1759

BT - World Congress on Medical Physics and Biomedical Engineering

PB - Springer Verlag

T2 - World Congress on Medical Physics and Biomedical Engineering: Image Processing, Biosignal Processing, Modelling and Simulation, Biomechanics

Y2 - 7 September 2009 through 12 September 2009

ER -

Yang Y, Choi S, Jeong G. LDA-based vapor recognition using image-formed array sensor response for portable electronic nose. In World Congress on Medical Physics and Biomedical Engineering: Image Processing, Biosignal Processing, Modelling and Simulation, Biomechanics. 4 ed. Springer Verlag. 2009. p. 1756-1759. (IFMBE Proceedings; 4). doi: 10.1007/978-3-642-03882-2_466

LDA-based vapor recognition using image-formed array sensor response for portable electronic nose

Abstract

Publication series

Conference

UN SDGs

Keywords

Quacquarelli Symonds(QS) Subject Topics

Access to Document

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