Respiratory sound analysis in healthy and pathological subjects: A wavelet approach

In this paper we describe the application of a wavelet analysis-based method, to characterize the frequency power distribution of the unsteady respiratory sound signals in order to better discriminate the healthy state of a given subject. To evaluate the methodology, both normal tracheal sounds as well as adventitious respiratory sounds were investigated. In particular, our analysis shows the possibility to extract useful statistical information on the energy content and its mean frequency distribution giving us a quantitative characteristic hallmark of the respiratory pattern. The presence of sound anomalies can be pointed out through some specific patterns of the wavelet mean power spectra and thus the localization of the related quartiles which can be used as simple and efficient diagnostic indices. In this study the method has been applied in healthy subjects and patients with different respiratory diseases. Results show that different power spectra patterns characterize health from disease. Some preliminary results indicate also that pathological patterns can change as result of therapeutical interventions like mechanical ventilation.