Discrimination of Lung Sounds Using a Statistics of Waveform Intervals

In a lung auscultatory sounds diagnosis, the diagnosis result would be affected by the skill of the doctor, that is, the doctor should discriminate a lung sounds by own subjective, since standard diagnosis procedure with objectivity has not been established yet. In many cases of the lung sounds diagnosis, the existence of features, which are called adventitious sounds, are important key. The adventitious sounds is roughly classified into two class; one is called coarse crackles, and the other is called fine crackles. Thus, we construct a computer aided diagnosis (CAD) system for classifying a lung sound into three types, that is, coarse crackle, fine crackle and normal breath sound. We aimed with the waveform time intervals for discrimination. Our CAD system calculates average histograms of intervals for each class, and discriminates a input histogram into these three types by the distance between each average histogram. Keyword: Computer Aided Diagnosis, Respiratory Sounds, Peak interval analysis