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Bacteria classification using electronic nose for diabetic wound monitoring

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Main Authors: Azian Azamimi, Abdullah, Nurlisa, Yusuf @ Idris, Ammar, Zakaria, Dr., Mohammad Iqbal, Omar@Ye Htut, Assoc. Prof. Dr., Ali Yeon, Md Shakaff, Prof. Dr., Abd Hamid, Adom, Prof. Dr., Latifah Munirah, Kamarudin, Dr., Yeap, Ewe Juan, Dr., Amizah, Othman, Dr., Mohd Sadek, Yasin
Other Authors: azamimi@unimap.edu.my
Format: Article
Language:English
Published: Trans Tech Publications 2014
Subjects:
Bacteria infection
Diabetic foot
Electronic nose
Linear discriminant analysis (LDA)
Principle component analysis (PCA)
Online Access:http://dspace.unimap.edu.my:80/dspace/handle/123456789/32392
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spelling my.unimap-323922014-03-06T07:29:08Z Bacteria classification using electronic nose for diabetic wound monitoring Azian Azamimi, Abdullah Nurlisa, Yusuf @ Idris Ammar, Zakaria, Dr. Mohammad Iqbal, Omar@Ye Htut, Assoc. Prof. Dr. Ali Yeon, Md Shakaff, Prof. Dr. Abd Hamid, Adom, Prof. Dr. Latifah Munirah, Kamarudin, Dr. Yeap, Ewe Juan, Dr. Amizah, Othman, Dr. Mohd Sadek, Yasin azamimi@unimap.edu.my ammarzakaria@unimap.edu.my iqbalomar@unimap.edu.my aliyeon@unimap.edu.my abdhamid@unimap.edu.my Bacteria infection Diabetic foot Electronic nose Linear discriminant analysis (LDA) Principle component analysis (PCA) Link to publisher's homepage at http://www.ttp.net/ Array based gas sensor technology namely Electronic Nose (E-nose) now offers the potential of a rapid and robust analytical approach to odor measurement for medical use. Wounds become infected when a microorganism which is bacteria from the environment or patient's body enters the open wound and multiply. The conventional method consumes more time to detect the bacteria growth. However, by using this E-Nose, the bacteria can be detected and classified according to their volatile organic compound (VOC) in shorter time. Readings were taken from headspace of samples by manually introducing the portable e-nose system into a special container that containing a volume of bacteria in suspension. The data will be processed by using statistical analysis which is Principle Component Analysis (PCA) and Linear Discriminant Analysis (LDA) methods. The most common bacteria in diabetic foot are Staphylococcus aureus, Escherchia coli, Pseudomonas aeruginosa, and many more. 2014-03-06T07:29:08Z 2014-03-06T07:29:08Z 2013 Article Applied Mechanics and Materials, vol. 339, 2013, pages 167-172 978-303785737-3 1660-9336 http://www.scientific.net/AMM.339.167 http://dspace.unimap.edu.my:80/dspace/handle/123456789/32392 en Trans Tech Publications
institution Universiti Malaysia Perlis
building UniMAP Library
collection Institutional Repository
continent Asia
country Malaysia
content_provider Universiti Malaysia Perlis
content_source UniMAP Library Digital Repository
url_provider http://dspace.unimap.edu.my/
language English
topic Bacteria infection
Diabetic foot
Electronic nose
Linear discriminant analysis (LDA)
Principle component analysis (PCA)
spellingShingle Bacteria infection
Diabetic foot
Electronic nose
Linear discriminant analysis (LDA)
Principle component analysis (PCA)
Azian Azamimi, Abdullah
Nurlisa, Yusuf @ Idris
Ammar, Zakaria, Dr.
Mohammad Iqbal, Omar@Ye Htut, Assoc. Prof. Dr.
Ali Yeon, Md Shakaff, Prof. Dr.
Abd Hamid, Adom, Prof. Dr.
Latifah Munirah, Kamarudin, Dr.
Yeap, Ewe Juan, Dr.
Amizah, Othman, Dr.
Mohd Sadek, Yasin
Bacteria classification using electronic nose for diabetic wound monitoring
description Link to publisher's homepage at http://www.ttp.net/
author2 azamimi@unimap.edu.my
author_facet azamimi@unimap.edu.my
Azian Azamimi, Abdullah
Nurlisa, Yusuf @ Idris
Ammar, Zakaria, Dr.
Mohammad Iqbal, Omar@Ye Htut, Assoc. Prof. Dr.
Ali Yeon, Md Shakaff, Prof. Dr.
Abd Hamid, Adom, Prof. Dr.
Latifah Munirah, Kamarudin, Dr.
Yeap, Ewe Juan, Dr.
Amizah, Othman, Dr.
Mohd Sadek, Yasin
format Article
author Azian Azamimi, Abdullah
Nurlisa, Yusuf @ Idris
Ammar, Zakaria, Dr.
Mohammad Iqbal, Omar@Ye Htut, Assoc. Prof. Dr.
Ali Yeon, Md Shakaff, Prof. Dr.
Abd Hamid, Adom, Prof. Dr.
Latifah Munirah, Kamarudin, Dr.
Yeap, Ewe Juan, Dr.
Amizah, Othman, Dr.
Mohd Sadek, Yasin
author_sort Azian Azamimi, Abdullah
title Bacteria classification using electronic nose for diabetic wound monitoring
title_short Bacteria classification using electronic nose for diabetic wound monitoring
title_full Bacteria classification using electronic nose for diabetic wound monitoring
title_fullStr Bacteria classification using electronic nose for diabetic wound monitoring
title_full_unstemmed Bacteria classification using electronic nose for diabetic wound monitoring
title_sort bacteria classification using electronic nose for diabetic wound monitoring
publisher Trans Tech Publications
publishDate 2014
url http://dspace.unimap.edu.my:80/dspace/handle/123456789/32392
_version_ 1643796881940152320
score 13.18916

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