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.