Respiratory Wheeze Sound Analysis Using Digital Signal Processing Techniques

Auscultation and interpretation of lung sounds by a stethoscope had been an essential method of diagnosing pulmonary diseases. However this method has always been unreliable due to poor audibility, inter-observer variations (between different physicians). Thus computerized analysis of lung sounds for diagnosis of pulmonary diseases is seen as a convenient method. In the present paper different lung sounds have been analyzed for wheeze detection and classification to Monophonic or Polyphonic using MATLAB (Matrix Laboratory software). The presented algorithm integrates and analyses the set of parameters based on ATS (American Thoracic Society) definition of wheeze and the previous researches. It is very robust, computationally simple and yielded overall sensitivity of 90% for wheeze episode detection and accuracy of 91%. The algorithm differentiates between monophonic wheezes and polyphonic wheezes with sensitivity of 91% and accuracy of 70%. In case of other lung sounds the proposed algorithm excluded normal sounds from being identified as a wheeze with the specificity of 90%.