Automatic wheezing recognition in recorded lung sounds

This paper describes the investigation of techniques for lung sounds analysis using the spectrogram image processing of respiratory cycles as a parameter source for automatic wheezing recognition and visual user feedback. The spectrogram is generated from lung sound recorded in a wave file. The spectrogram image is passed through a bidimensional convolution filter and a limiter in order to increase the contrast and isolate the highest components. The spectral average from the treated spectrogram is computed and stored as an array. The array´s tops are located and used as inputs to a multi-layer perceptron artificial neural network. The presented results shows that this technique achieves 83,93% match in the wheezing detection for isolated respiratory cycle and 96,43% match for detection in sounds from the same person. Also, the system returns the original recorded sound and the post-processed spectrogram image for the user to take his own conclusions.