Recommendations Related to Wheeze Sound Data Acquisition

Authors

  • F. G. Nabi School of Mechatronic Engineering, Universiti Malaysia Perlis (UniMAP), Kampus Pauh Putra, 02600 Pauh, Perlis. Malaysia.
  • K. Sundaraj Faculty of Electronics and Computer Engineering, Universiti Teknikal Malaysia Melaka (UTeM), Hang Tuah Jaya, 76100 Durian Tunggal, Melaka, Malaysia.
  • C. K. Lam School of Mechatronic Engineering, Universiti Malaysia Perlis (UniMAP), Kampus Pauh Putra, 02600 Pauh, Perlis. Malaysia.
  • R. Palaniappan School of Electronics Engineering (SENSE), VIT University, Vellore. India.
  • J. Hussain Faculty of Electronics and Computer Engineering, Universiti Teknikal Malaysia Melaka (UTeM), Hang Tuah Jaya, 76100 Durian Tunggal, Melaka, Malaysia.

Keywords:

Adventitious Sounds, Electronic Auscultation, Respiratory Sounds, Wheeze Detection, Wheeze Sound,

Abstract

In the field of computerized respiratory sounds, a reliable data set with a sufficient number of subjects is required for the development of wheeze detection algorithm or for further analysis. Validated and accurate data is a critical issue in the field of research. In this study, the protocol related to wheeze sound data acquisition is discussed. Previously, most articles focused on wheeze detection or its parametric analysis, but no consideration was given to data acquisition. Second major purpose of this study is to exhibit particulars of our dataset which was attained for future analysis. We compile a database with a sufficient and reliable number of cases with all essential details, in contrast to commercially available wheeze sound data used for research, freely available online data on websites and data used to train medical students for auscultation.

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Published

2018-05-29

How to Cite

Nabi, F. G., Sundaraj, K., Lam, C. K., Palaniappan, R., & Hussain, J. (2018). Recommendations Related to Wheeze Sound Data Acquisition. Journal of Telecommunication, Electronic and Computer Engineering (JTEC), 10(1-13), 117–120. Retrieved from https://jtec.utem.edu.my/jtec/article/view/4134

Issue

Vol. 10 No. 1-13: Exploring Man-Machines Compliance in Signal Processing and Artificial Intelligence

Section

Articles

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