Comments on "An efficient coding algorithm for the compression of ECG signals using the wavelet transform"

Abstract

The author proposed an effective wavelet-based ECG compression algorithm (Rajoub, 2002). The reported extraordinary performance motivated us to explore the findings and to use it in our research activity. During the implementation of the proposed algorithm several important points regarding accuracy, methodology, and coding were found to be improperly substantiated. This paper discusses these findings and provides specific subjective and objective measures that could improve the interpretation of compression results in these research-type problems.

Compressing electrocardiogram signals using parameterized wavelets

“…• Preprocessing of the ECG signal in order to attain a resulting signal with a zero mean, since in ECG signal the important part is not the signal level but the time variation of the ECG waveform [3].…”

“…The goal of the experiments is to compare the compression method proposed in this paper with the method proposed by Rajoub in [19] with the modifications suggested by [3]. The ECG signals to the Arrythmia database of the "Research Resource for Complex Physiologic Signals" [11].…”

“…• Transform methods, which first transform the signal to another time-frequency representation better suited for detecting and removing redundancies [3], [4], [5], [9], [14], [17], [18] and [19].…”

ECG Compression using the Three-Level Quantization and Wavelet Transform

“…This implies that many of the transform coefficients will have little energy and may be discarded. A variety of encoding methods, for instance vector quantization and linear prediction, are used directly to the wavelet coefficients [6][7][8][9].…”

Wavelet-Threshold based ECG Compression with Smooth Retrieved Quality for Telecardiology

“…Best reconstruction results are obtained with VQ on scales with long duration and low dynamic range, and scalar quantization on scales of short duration and high dynamic range. Threshold-based algorithms: Recently many attractive threshold based compression methods have been presented in the literature [11]- [14]. we have found that in these threshold based compression method two important problems are not addressed.…”