Discrimination analysis of discontinuous breath sounds using higher-order crossings

Research output: Contribution to journalArticlepeer-review

13 Scopus citations


The paper evaluates the performance of an automatic discrimination analysis (DA) method used to discriminate efficiently the types of discontinuous breath sound (DBS), i.e. fine crackles (FCs), coarse crackles (CCs) and squawks (SQs); this may lead to more accurate characterisation of the pulmonary acoustical changes due to the related pathology. Based on higher-order crossings (HOCs), the proposed method, HOC-DA, captured the differences in the oscillatory patterns of FCs, CCs and SQs, which are only exposed when higher (> 1) crossings are employed. Prior to HOC-DA, wavelet-based de-noising of DBSs was employed to eliminate the effects of the vesicular sound (background noise) from their oscillatory pattern. The HOC-DA was applied to 157 discontinuous breath sounds corresponding to 16 cases included in three lung sound databases. Results showed that the HOC-DA efficiently separated FCs from CCs, SQs from CCs (both with an accuracy of 100%), and SQs from FCs (accuracy of 80%), with the optimum order ranging from 9 to 11. When compared with other classification tools, the HOC-DA resulted in high discrimination accuracy without involving high computational complexity. Owing to its simplicity, it could be implemented in a real-time context and be used in clinical medicine as a module of an integrated intelligent patient evaluation system.

Original languageBritish English
Pages (from-to)445-455
Number of pages11
JournalMedical and Biological Engineering and Computing
Issue number4
StatePublished - Jul 2003


  • Discontinuous breath sounds
  • Discrimination analysis
  • Fine/coarse crackles
  • Higher-order crossings
  • Squawks
  • Wavelet-based de-noising


Dive into the research topics of 'Discrimination analysis of discontinuous breath sounds using higher-order crossings'. Together they form a unique fingerprint.

Cite this