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Pulmonary crackle characterization: approaches in the use of discrete wavelet transform regarding border effect, mother-wavelet selection, and subband reduction

机译:肺裂声表征:使用离散小波变换的边界效应,母小波选择和子带缩减的方法

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Introduction Crackles are discontinuous, non-stationary respiratory sounds and can be characterized by their duration and frequency. In the literature, many techniques of filtering, feature extraction, and classification were presented. Although the discrete wavelet transform (DWT) is a well-known tool in this area, issues like signal border extension, mother-wavelet selection, and its subbands were not properly discussed. Methods In this work, 30 different mother-wavelets 8 subbands were assessed, and 9 border extension modes were evaluated. The evaluations were done based on the energy representation of the crackle considering the mother-wavelet and the border extension, allowing a reduction of not representative subbands. Results Tests revealed that the border extension mode considered during the DWT affects crackle characterization, whereas SP1 (Smooth-Padding of order 1) and ASYMW (Antisymmetric-Padding (whole-point)) modes shall not be used. After DWT, only 3 subbands (D3, D4, and D5) were needed to characterize crackles. Finally, from the group of mother-wavelets tested, Daubechies 7 and Symlet 7 were found to be the most adequate for crackle characterization. Discussion DWT can be used to characterize crackles when proper border extension mode, mother-wavelet, and subbands are taken into account.
机译:简介爆裂声是不连续的,非平稳的呼吸声,可以通过持续时间和频率来表征。在文献中,提出了许多过滤,特征提取和分类技术。尽管离散小波变换(DWT)是该领域的知名工具,但诸如信号边界扩展,母小波选择及其子带之类的问题并未得到适当讨论。方法在这项工作中,评估了30个不同的子波8个子带,并评估了9个边界扩展模式。评估是基于裂纹的能量表示进行的,其中考虑了母子波和边界扩展,从而减少了无代表性的子带。结果测试表明,在DWT中考虑的边界扩展模式会影响裂纹的特征,而不应使用SP1(1级平滑填充)和ASYMW(反对称填充(全点))模式。 DWT之后,仅需要3个子带(D3,D4和D5)来表征裂纹。最后,从测试的母小波组中,发现Daubechies 7和Symlet 7最适合裂纹特征。讨论当考虑适当的边界扩展模式,母小波和子带时,DWT可用于表征裂纹。

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