Digital Signal Processing and Display of Lung Sounds

Abstract

Presented here is an examination of the issues surrounding the analysis of lung sounds and their display. The project is aimed at providing a visual representation of the information that a physician gleans from auscultation of the lungs. Such a tool would be of benefit to those who are hearing impaired and also in teaching auscultation. A second goal is to provide a tool that will allow the examination and quantification of lung sounds thus permitting linkage between the acoustic events and their physical causes. The project is divided into two tasks. The first is the isolation of the wheezes and crackles; the second is their display. The isolation problem is difficult due to the variance in the frequency characteristics of the sounds; wheezes may appear anywhere in a two thousand hertz band and crackles also display a varying spectrum. The difficulty in separation is further compounded by the spectral overlap of the two. These problems preclude any 'simple' filter solution. In order to separate the sounds, filtering methods based on exploiting the statistical differences namely the stationarity of the wheeze and non-stationarity of the crackle are utilized. Of the several methods attempted, the most promising was the Adaptive Line Enhancement process when driven by the Least Mean Squares adaptive algorithm. An important criteria for being able to display the sounds was to access their temporal information. Accomplishing this with the standard short time Fourier transform precludes adequate resolution to identify the frequency characteristics of crackles. Display of the crackle information was facilitated by the use of high resolution time-frequency methods based on Cohen's Class of time-frequency representations. These methods are able to simultaneously provide high time and frequency resolution. A method for automatic adjustment of the parameters involved in the process was developed in order to yield the best display possible.