Using Back-Propagation Neural Network for Automatic Wheezing Detection

Abstract

This study describes the design of a fast and high performance wheeze recognition system. The proposed wheezing detection algorithm is based on order truncate average (OTA) and back-propagation neural network (BPNN). Some features are then extracted from the processed spectra to train a BPNN. Eventually, the new testing samples go through the trained BPNN to recognize whether they are wheezing sounds. Experimental results show a high sensitivity of 0.946 and a specificity of 1.0 in qualitative analysis of wheeze recognition.