Embedded filter bank-based algorithm for ECG compression
Embedded filter bank-based algorithm for ECG compression
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DOI：
10.1016/j.sigpro.2007.12.006
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发表时间：
2008-06-01
影响因子：
4.4
通讯作者：
Barner, Kenneth E.
中科院分区：
文献类型：
--
作者：
Blanco-Velasco, Manuel;Cruz-Roldan, Fernando;Barner, Kenneth E.
在这项工作中，两个心电图压缩方案提出了使用两种类型的滤波器组分解输入信号：小波包（WP）和近完美重构余弦调制滤波器组。传统的嵌入式零树小波（EZW）算法利用了金字塔小波分解的子带系数之间的层次关系。然而，当与WP一起使用时，它的性能更差，因为层次结构变得更加复杂。为了解决这个问题，我们提出了一种新的技术，认为系数之间没有关系，因此适合用于WP。此外，这种新的近似使得有可能将量化方法应用于M通道最大抽取滤波器组。在这种方式中，所提出的算法提供了两个高效和有效的ECG压缩器，表现出更好的ECG压缩性能比传统的EZW算法。(c)2008 Elsevier B.V.保留所有权利。
In this work, two ECG compression schemes are presented using two types of filter banks to decompose the incoming signal: wavelet packets (WP) and nearly-perfect reconstruction cosine modulated filter banks. The conventional embedded zerotree wavelet (EZW) algorithm takes advantage of the hierarchical relationship among subband coefficients of the pyramidal wavelet decomposition. Nevertheless, it performs worse when used with WP as the hierarchy becomes more complex. In order to address this problem, we propose a new technique that considers no relationship among coefficients, and is therefore suitable for use with WP. Furthermore, this new approximation makes it possible to apply the quantization method to M-channel maximally decimated filter banks. In this fashion, the proposed algorithm provides two efficient and effective ECG compressors that show better ECG compression performance than the conventional EZW algorithm. (c) 2008 Elsevier B.V. All rights reserved.