Detection of COPD’s auscultative symptoms using higher order statistics in the analysis of respiratory sounds

Abstract

In this paper we present the method for determination of the specific auscultatory diagnostic signs in patients with chronic obstructive pulmonary disease (COPD), which is based upon the utilization of the polyspectral analysis and the calculation of higher order statistics. The main stages of the method are the calculation and construction of the bicoherence function of the lung sound signal in order to find its maximal value. The visual and numerical estimations of the obtained maximum allow us to conclude the presence or absence in this lung’s audio signal of the artifact, which indicates the pathology. For more accurate results one needs to determine asymmetry coefficient and to perform the estimation of bifrequency corresponding to the maximal value of the bicoherence coefficient. The calculation of skewness and kurtosis coefficients of cross-correlation functions of lung sound signals, which were recorded simultaneously in four channels, allows us to reduce the sensitivity of the method to noise components. Therefore, by analyzing all proposed calculated characteristics and parameters one can conclude the presence or absence of the pathology in this audio signal.