Embedded filter bank-based algorithm for ECG compression

Authors:
Manuel Blanco-Velasco;Fernando Cruz-Roldán;Eduardo Moreno-Martínez;Juan-Ignacio Godino-Llorente;Kenneth E. Barner
Affiliations:
Department of Teoría de la Señal y Comunicaciones, Universidad de Alcalá, Campus Universitario, 28871 Alcalá de Henares, Madrid, Spain;Department of Teoría de la Señal y Comunicaciones, Universidad de Alcalá, Campus Universitario, 28871 Alcalá de Henares, Madrid, Spain;Department of Teoría de la Señal y Comunicaciones, Universidad de Alcalá, Campus Universitario, 28871 Alcalá de Henares, Madrid, Spain;Department of Ingeniería de Circuitos y Sistemas, Universidad Politécnica de Madrid, Madrid, Spain;Department of Electrical and Computer Engineering, University of Delaware, Newark, DE 19716, USA
Venue:
Signal Processing
Year:
2008

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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.