Paper Info
Title
Embedded filter bank-based algorithm for ECG compression
Abstract
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.
Year
DOI
Venue
2008
10.1016/j.sigpro.2007.12.006
Signal Processing
Keywords
Field
DocType
channel bank filter,pyramidal wavelet decomposition,flltering theory,wavelet packets wp,filter bank,proposed algorithm,modulated filter bank,wavelet packet,fllter bank.,ecg compression performance,effective ecg compressor,channel bank fllter,ecg compression,ecg compression scheme,bank-based algorithm,electrocardiogram ecg,conventional embedded zerotree wavelet,embedded zerotree wavelet,conventional ezw algorithm,filtering theory
Signal processing,Compression (physics),Wavelet decomposition,Trigonometric functions,Filter bank,Algorithm,Quantization (signal processing),Wavelet packet decomposition,Mathematics,Wavelet
Journal
Volume
Issue
ISSN
88
6
Signal Processing
Citations 
PageRank 
References 
16
0.97
10
Authors
5
Name
Order
Citations
PageRank
Manuel Blanco-Velasco131430.57
Fernando Cruz-Roldán211119.33
Eduardo Moreno-Martínez3171.68
Juan I. Godino-Llorente417712.38
Kenneth E. Barner581270.19