Classification of Respiratory Sounds by Using an Artificial Neural Network
نویسندگان
چکیده
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. Keywords-Respiratory Sounds, Classification of Biomedical Signals, Artificial Neural Network.
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عنوان ژورنال:
- IJPRAI
دوره 17 شماره
صفحات -
تاریخ انتشار 2003