Audio-visual Recognition of Auscultatory Breathing Sounds using Fourier and Wavelet Analyses

Authors

  • Fumio Nogata Emeritus professor, Gifu University, Japan
  • Yasunai Yokota
  • Yoko Kawamura
  • Hiroyuki Morita
  • Yoshiyuki Uno

Keywords:

Breath Sound, Visualization, Image Analysis, FFt and Wavelet

Abstract

The era of computer management of clinical data demands the establishment of new techniques to analyze auscultatory sounds that can be better understood by both physicians and patients. This paper describes visual-based recognition techniques of breath sounds using two spectrograms created using short term FFT and wavelet analyses. Changes of frequency, intensity, and tone with time of breath sounds (21 samples) were shown using spectrograms of two kinds. Consequently, abnormal breath sounds were simply detected by differences of those patterns at first sight. They assist the recognition of the associated condition of disease. We expect to become a diagnostic support system in the near future.

 

 

Author Biography

Fumio Nogata, Emeritus professor, Gifu University, Japan

Department of Information Science,

Faculty of Engineering

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Published

2015-10-30

How to Cite

Nogata, F., Yokota, Y., Kawamura, Y., Morita, H., & Uno, Y. (2015). Audio-visual Recognition of Auscultatory Breathing Sounds using Fourier and Wavelet Analyses. Asian Journal of Computer and Information Systems, 3(4). Retrieved from https://www.ajouronline.com/index.php/AJCIS/article/view/2925