On applying continuous wavelet transform in wheeze analysis

Styliani A. Taplidou, Leontios J. Hadjileontiadis, Ilias K. Kitsas, Konstantinos I. Panoulas, Thomas Penzel, Volker Gross, Stavros M. Panas

Research output: Contribution to journalConference articlepeer-review

31 Scopus citations

Abstract

The identification of continuous abnormal lung sounds, like wheezes, in the total breathing cycle is of great importance in the diagnosis of obstructive airways pathologies. To this vein, the current work introduces an efficient method for the detection of wheezes, based on the time-scale representation of breath sound recordings. The employed Continuous Wavelet Transform is proven to be a valuable tool at this direction, when combined with scale-dependent thresholding. Analysis of lung sound recordings from 'wheezing' patients shows promising performance in the detection and extraction of wheezes from the background noise and reveals its potentiality for data-volume reduction in long-term wheezing screening, such as in sleep-laboratories.

Original languageBritish English
Pages (from-to)3832-3835
Number of pages4
JournalAnnual International Conference of the IEEE Engineering in Medicine and Biology - Proceedings
Volume26 V
StatePublished - 2004
EventConference Proceedings - 26th Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBC 2004 - San Francisco, CA, United States
Duration: 1 Sep 20045 Sep 2004

Keywords

  • Breath sounds
  • Continuous wavelet transform
  • Detection/denoising
  • Scalogram
  • Wheezes

Fingerprint

Dive into the research topics of 'On applying continuous wavelet transform in wheeze analysis'. Together they form a unique fingerprint.

Cite this