Title :
Automatic wheezing recognition in recorded lung sounds
Author :
Riella, R.J. ; Nohama, P. ; Borges, R.F. ; Stelle, A.L.
Author_Institution :
Centro Fed. de Educacao, Tecnologica do Parana, Curitiba, Brazil
Abstract :
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.
Keywords :
bioacoustics; biomedical measurement; lung; medical image processing; medical signal detection; multilayer perceptrons; patient diagnosis; automatic wheezing recognition; bidimensional convolution filter; lung sounds analysis; multilayer perceptron artificial neural network; postprocessed spectrogram image; recorded lung sounds; respiratory cycles; spectrogram image processing; visual user feedback; wheezing detection; Adaptive filters; Artificial neural networks; Diseases; Finite impulse response filter; Image processing; Image recognition; Lungs; Pathology; Spectrogram; Visualization;
Conference_Titel :
Engineering in Medicine and Biology Society, 2003. Proceedings of the 25th Annual International Conference of the IEEE
Print_ISBN :
0-7803-7789-3
DOI :
10.1109/IEMBS.2003.1280432