Wheeze type classification using non-dyadic wavelet transform based optimal energy ratio technique


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

COMPUTERS IN BIOLOGY AND MEDICINE, vol.104, pp.175-182, 2019 (SCI-Expanded) identifier identifier identifier

  • Publication Type: Article / Article
  • Volume: 104
  • Publication Date: 2019
  • Doi Number: 10.1016/j.compbiomed.2018.11.004
  • Journal Name: COMPUTERS IN BIOLOGY AND MEDICINE
  • Journal Indexes: Science Citation Index Expanded (SCI-EXPANDED), Scopus
  • Page Numbers: pp.175-182
  • Keywords: Respiratory sounds, Pulmonary sounds, Discrimination, Wheezing, Monophonic, Polyphonic, LUNG SOUND ANALYSIS, RESPIRATORY SOUNDS
  • Yıldız Technical University Affiliated: Yes

Abstract

Background and objective: Wheezes in pulmonary sounds are anomalies which are often associated with obstructive type of lung diseases. The previous works on wheeze-type classification focused mainly on using fixed time-frequency/scale resolution based on Fourier and wavelet transforms. The main contribution of the proposed method, in which the time-scale resolution can be tuned according to the signal of interest, is to discriminate monophonic and polyphonic wheezes with higher accuracy than previously suggested time and time-frequency/scale based methods.