Abstract
In this paper, a classification method for respiratory sounds (RSs) in patients with asthma and in healthy subjects is presented. Wavelet transform is applied to a window containing 256 samples. Elements of the feature vectors are obtained from the wavelet coefficients. The best feature elements are selected by using dynamic programming. Grow and Learn (GAL) neural network is used for the classification. It is observed that RSs of patients (with asthma) and healthy subjects are successfully classified by the GAL network.
Original language | English |
---|---|
Pages (from-to) | 697-699 |
Number of pages | 3 |
Journal | Annual Reports of the Research Reactor Institute, Kyoto University |
Volume | 1 |
Publication status | Published - 2001 |
Event | 23rd Annual International Conference of the IEEE Engineering in Medicine and Biology Society - Istanbul, Turkey Duration: 25 Oct 2001 → 28 Oct 2001 |
Keywords
- Artificial neural network
- Classification of biomedical signals
- Respiratory sounds