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dc.contributor.authorNurlisa, Yusuf
dc.contributor.authorMuhammad Iqbal, Omar
dc.contributor.authorAmmar, Zakaria
dc.contributor.authorAzian Azamimi, Abdullah
dc.contributor.authorLatifah Munirah, Kamarudin
dc.contributor.authorAli Yeon, Md Shakaff, Prof. Dr.
dc.contributor.authorMaz Jamilah, Masnan
dc.contributor.authorNurhamidah, Zakaria
dc.contributor.authorYeap, Ewe Juan, Dr
dc.contributor.authorAbu Talib, Othman, Dr.
dc.contributor.authorMohd Sadek, Yasin
dc.date.accessioned2014-06-14T04:13:41Z
dc.date.available2014-06-14T04:13:41Z
dc.date.issued2013
dc.identifier.citationp. 114-118en_US
dc.identifier.urihttp://dspace.unimap.edu.my:80/dspace/handle/123456789/35490
dc.identifier.urihttp://ieeexplore.ieee.org/xpl/login.jsp?tp=&arnumber=6728791
dc.descriptionProceeding of The Conference on Wireless Sensor (ICWISE 2013) at Kuching Sarawak, Malaysia on 2 December 2013 through 4 December 2013. Link to publisher's homepage at http://ezproxy.unimap.edu.my:2080/Xplore/dynhome.jspen_US
dc.description.abstractFoot infections may lead to serious complications if failed to detect at an early stage; especially for diabetic patients. It is necessary to develop an easy and reliable method to identify and classify the causative bacteria from the wound to assist health care practitioners. Therefore, this study proposed an alternative to the conventional technique by using an electronic nose with 32 matrices of non-specific conducting polymer sensors known as Cyranose320. A novel odour detection method is developed and targeted for microbial bacteria causing infection on diabetic foot using direct injection of static headspace. The bacteria are obtained from the clinical specimens by swabbing technique and isolated in a blood agar medium to verify the performance of the bacterial specialized medium. Various classification algorithm techniques proved that each bacteria produce certain characteristic of odour and can be used as a surrogate bio-marker. Thus, preliminary results from this study show that the electronic nose is able to identify and classify the presence of causative bacteria with high success rate of over 90% in diabetic foot infection.en_US
dc.language.isoenen_US
dc.publisherIEEE Computer Societyen_US
dc.relation.ispartofseriesProceedings of the Conference on Wireless Sensor (ICWISE 2013);
dc.subjectCyranose320en_US
dc.subjectDiabetic foot infectionen_US
dc.subjectElectronic noseen_US
dc.subjectPattern recognitionen_US
dc.titleDiagnosis of bacteria for diabetic foot infection using electronic nose technologyen_US
dc.typeWorking Paperen_US
dc.identifier.url10.1109/ICWISE.2013.6728791
dc.contributor.urlazamimi@unimap.edu.myen_US
dc.contributor.urlammarzakaria@unimap.edu.myen_US


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