Lung Consolidation Detection through Analysis of Vocal Resonance Signals

Consolidation of the lung is a common pathology which is sometimes life threatening. One of the primary causes is the infection of lung tissue (pneumonia). Vocal resonance and vocal fremitus are part of the routine clinical examination of the respiratory system by physicians, which although time consuming, helps in the diagnosis of consolidation of the lung. In this paper, we suggest a possible automatic lung consolidation detection system that can be used by health workers with basic training. Analysis is performed on the vocal resonance sound signals recorded using an electronic stethoscope from the chest walls of normal subjects and patients. We show that for the detection system, use of signal loudness, which is generally considered by physicians, would be infeasible and propose that signal power spectral density computed using our system be considered. Certain frequency regions in the power spectral density (periodogram) are proved to be significant indicators of lung consolidation using t-tests. These findings are then applied to design the detection system using Gaussian naive Bayes classifiers.