Quantitative models for assessment of respiratory diseases

Experienced dynamic demographic growth of many cities, especially in the last three decades, has often resulted in a replacement of areas with vegetation and crops by industrial parks and residential areas, exposing areas to erosion. Mexicali, which is located in an arid region, is experiencing such transformations which are paralleled by a significant increase in respiratory diseases and allergies especially in children. In particular, adverse health effects of PM
₁₀
particles and asthma can be observed. The focus of this paper is to present a method for a quantitative assessment of patient health as it relates to respiratory disorders utilizing lung sounds. In order to accomplish this, applicable traditional techniques within the speech processing domain were utilized to evaluate lung sounds obtained with a digital stethoscope. Traditional methods utilized in the evaluation of asthma involve auscultation and spirometry, but utilization of more sensitive electronic stethoscopes, which are currently available, and application of quantitative signal analysis methods offer opportunities of improved diagnosis. In particular we propose acoustic evaluation methodology based on the Gaussian Mixed Models (GMM) which should assist in broader analysis, identification, and diagnosis of asthma based on the frequency domain analysis of wheezing and crackles.