Using Back-Propagation Neural Network for Automatic Wheezing Detection
Journal
Proceedings - 2015 International Conference on Intelligent Information Hiding and Multimedia Signal Processing, IIH-MSP 2015
Pages
49-52
Date Issued
2016
Author(s)
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.
SDGs
Type
conference paper