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In this paper, a wavelet packet-based method is used for detection of abnormal respiratory sounds. The sound signal is divided into segments, and a feature vector for classification is formed using the results of the search for the best wavelet packet decomposition. The segments are classified as...
Wheezes are abnormal sounds which are known to be relevant to Chronic Obstructive Pulmonary Diseases (COPD). The analysis of such signals is especially useful in patient monitoring or pharmacology. Respiratory sounds are dependent on the flow and the volume. Furthermore, they can be the result of...
A new automatic wheeze detection method which is based on image processing techniques applied to the sonagram was developed here. In the calculation of the sonagram, autoregressive and FFT spectrum estimation methods were compared. The method was validated in four wheezing asthmatic patients by a...