Rapid Identification Method of Aerobic Bacteria in Diabetic Foot Ulcers Using Electronic Nose

被引：12

作者：

Abdullah, Azian Azamimi ^{[1
]}

Jing, Tan Woei ^{[1
]}

Sie, Chua Ai ^{[1
]}

Yusuf, Nurlisa ^{[1
]}

Zakaria, Ammar ^{[1
]}

Omar, Mohammad Iqbal ^{[1
]}

Shakaff, Ali Yeon Md ^{[1
]}

Adom, Abdul Hamid ^{[1
]}

Kamarudin, Latifah Munirah ^{[1
]}

Juan, Yeap Ewe ^{[2
]}

Othman, Annizah ^{[2
]}

Yassin, Mohd Sadek ^{[2
]}

机构：

[1] Univ Malaysia Perlis, Ctr Excellent Adv Sensor Technol CEASTech, Jejawi 02600, Perlis, Malaysia

[2] HTF Jalan Kolam, Kangar 01000, Perlis, Malaysia

来源：

ADVANCED SCIENCE LETTERS | 2014年 / 20卷 / 01期

关键词：

Diabetic Foot Ulcer; Electronic Nose; Bacteria Infection; Principle Component Analysis; Linear Discriminant Analysis; Feed Forward Back Propagation; Self Organizing Map; Artificial Neural Network;

D O I：

10.1166/asl.2014.5306

中图分类号：

O [数理科学和化学]; P [天文学、地球科学]; Q [生物科学]; N [自然科学总论];

学科分类号：

07 ; 0710 ; 09 ;

摘要：

Diabetic foot ulcer (DFU) is an infection, ulcer or destruction of deep tissue associated with neurological abnormalities, musculoskeletal deformities and various degrees of peripheral vascular disease of lower limb. In this study, an electronic nose is proposed to recognize types of bacteria in the diabetic foot ulcer on patients with the aid of data analysis using PCA (Principal Component Analysis) and LDA (Linear Discriminant Analysis) as the first step for feature extraction. Bacteria classification is also enhanced by pattern analysis using FFBP (Feed Forward Back Propagation) and SOM (Self Organizing Map) of ANN (Artificial Neural Network). Experimental results show that the use of electronic nose in identifying bacteria on diabetic foot ulcers works effectively as the high accuracy obtained for the bacteria classification.

引用

页码：37 / 41

页数：5

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