An alternative respiratory sounds classification system utilizing artificial neural networks.

Background: Computerized lung sound analysis involves recording lung sound via an electronic device, followed by computer analysis and classification based on specific signal characteristics as non-linearity and nonstationarity caused by air turbulence. An automatic analysis is necessary to avoid dependence on expert skills.

Methods: This work revolves around exploiting autocorrelation in the feature extraction stage.