Investigation of Human Pathogen Using Electronic Nose for Early Diagnosis

Authors

  • Syahida Amani Zulkifli School of Mechatronic Engineering, Universiti Malaysia Perlis (UniMAP), 02600 Arau, Perlis, Malaysia
  • Che Wan Sharifah Robiah Mohamad School of Mechatronic Engineering, Universiti Malaysia Perlis (UniMAP), 02600 Arau, Perlis, Malaysia
  • Abu Hassan Abdullah School of Mechatronic Engineering, Universiti Malaysia Perlis (UniMAP), 02600 Arau, Perlis, Malaysia

Keywords:

Bacterial infection, Electronic nose, Principal component analysis (PCA), Sensor,

Abstract

Electronic nose (E-nose) known as gas sensor array is a device that analyze the odor measurement give the fast response and less time consuming for clinical diagnosis. Many bacterial pathogens could lead to life threatening infections. Accurate and rapid diagnosis is crucial for the successful management of these infections disease. The conventional method need more time to detect the growth of bacterial. Alternatively, the bacteria are Pseudomonas aeruginosa and Shigella cultured on different media agar can be detected and classifies according to the volatile compound in shorter time using electronic nose (E-nose). Then, the data from electronic nose (E-nose) is processed using statistical method which is principal component analysis (PCA). The study shows the capability of electronic nose (E-nose) for early screening for bacterial infection in human stomach.

References

T. M. A. Sabeel, F. K. CheHarun, S. E. Eluwa, and S. M. A. Sabeel, “Detection of volatile compounds in urine using an electronic nose instrument,” in 2013 International Conference On Computing, Electrical And Electronic Engineering (ICCEEE), 2013.

N. M. Zetola, C. Modongo, K. Mathlagela, E. Sepako, O. Matsiri, T. Tamuhla, B. Mbongwe, E. Martinelli, G. Sirugo, R. Paolesse, and C. Di Natale, “Identification of a large pool of microorganisms with an array of porphyrin based gas sensors,” Sensors (Switzerland), vol. 16, no. 4, pp. 1–14, 2016.

J. Heo and S. Z. Hua, “An overview of recent strategies in pathogen sensing,” Sensors (Switzerland), vol. 9, no. 6, pp. 4483–4502, 2009.

A. A. Abdullah, N. Yusuf, A. Zakaria, M. I. Omar, A. Y. Shakaff, A. H. Adom, L. M. Kamarudin, Y. E. Juan, A. Othman, and M. S. Yassin, “Bacteria Classification Using Electronic Nose for Diabetic Wound Monitoring,” Appl. Mech. Mater., vol. 339, no. July, pp. 167–172, 2013.

E. Tait, J. D. Perry, S. P. Stanforth, and J. R. Dean, “Identification of Volatile Organic Compounds Produced by Bacteria Using HS-SPME-GC – MS,” pp. 363–373, 2014.

“Bacterial Gastroenteritis Medication,” pp. 2–5, 2017.

N. Yusuf, M. I. Omar, A. Zakaria, A. I. Jeffree, R. Thriumani, A. A. Abdullah, A. Y. M. Shakaff, M. J. Masnan, E. J. Yeap, A. Othman, and M. S. Yasin, “Evaluation of E-nose technology for detection of the causative bacteria in different culture media on diabetic foot infection,” IECBES 2014, Conf. Proc. - 2014 IEEE Conf. Biomed. Eng. Sci. “Miri, Where Eng. Med. Biol. Humanit. Meet,” no. July, pp. 67–70, 2015.

A. Dan Wilson, “Advanced methods for teaching electronic-nose technologies to diagnosticians and clinical laboratory technicians,” Procedia -Social Behav. Sci., vol. 46, pp. 4544–4554, 2012.

L. Zhang, F. Tian, and G. Pei, “A novel sensor selection using pattern recognition in electronic nose,” Measurement, vol. 54, pp. 31–39, 2014.

W. B. Hugo, “A brief history of heat, chemical and radiation preservation and disinfection,” Int. Biodeterior. Biodegrad., vol. 36, no. 3–4, pp. 197–217, 1995.

V. O. Ifeanyi, S. C. Nwosu, J. O. Okafor, C. P. Onnegbu, and N. E., “Comparative studies on five culture media for bacterial isolation,” African J. Microbiol. Res., vol. 8, no. 36, pp. 3330–3334, 2014.

R. Arulanantham, S. Pathmanathan, N. Ravimannan, and K. Niranjan, “Alternative culture media for bacterial growth using different formulation of protein sources,” J. Nat. Prod. Plant Resour, vol. 2, no. 6, pp. 697–700, 2012.

J. Gutiérrez and M. C. Horrillo, “Talanta Advances in artificial olfaction : Sensors and applications,” vol. 124, pp. 95–105, 2014.

M. B. Banerjee and T. Nandy, “Multivariate Preprocessing Techniques Towards Optimising Response of Fused Sensor from Electronic Nose and Electronic Tongue,” pp. 949–954, 2016.

M. J. Masnan, A. Zakaria, A. Y. M. Shakaff, N. I. Mahat, H. Hamid, N. Subari, and J. M. Saleh, “Principal Component Analysis – A Realization of Classification Success in Multi Sensor Data Fusion,” Principal Component Analysis Application., pp. 1–25, 2012.

Downloads

Published

2017-09-15

How to Cite

Zulkifli, S. A., Mohamad, C. W. S. R., & Abdullah, A. H. (2017). Investigation of Human Pathogen Using Electronic Nose for Early Diagnosis. Journal of Telecommunication, Electronic and Computer Engineering (JTEC), 9(2-12), 95–98. Retrieved from https://jtec.utem.edu.my/jtec/article/view/2776