A Lung Sound Classification System based on the Rational Dilation Wavelet Transform

Ulukaya S., SERBES G., SEN I., Kahya Y. P.

38th Annual International Conference of the IEEE-Engineering-in-Medicine-and-Biology-Society (EMBC), Florida, United States Of America, 16 - 20 August 2016, pp.3745-3748 identifier identifier identifier

  • Publication Type: Conference Paper / Full Text
  • Doi Number: 10.1109/embc.2016.7591542
  • City: Florida
  • Country: United States Of America
  • Page Numbers: pp.3745-3748
  • Yıldız Technical University Affiliated: Yes


I n this work, a wavelet based classification system that aims to discriminate crackle, normal and wheeze lung sounds is presented. While the previous works related with this problem use constant low Q-factor wavelets, which have limited frequency resolution and can not cope with oscillatory signals, in the proposed system, the Rational Dilation Wavelet Transform, whose Q-factors can be tuned, is employed. Proposed system yields an accuracy of 95 % for crackle, 97 % for wheeze, 93.50 % for normal and 95.17 % for total sound signal types using energy feature subset and proposed approach is superior to conventional low Q-factor wavelet analysis.