Wavelet and wavelet packet compression of electrocardiograms
01 May 1997-IEEE Transactions on Biomedical Engineering (IEEE Trans Biomed Eng)-Vol. 44, Iss: 5, pp 394-402
TL;DR: Pilot data from a blind evaluation of compressed ECG's by cardiologists suggest that the clinically useful information present in original ECG signals is preserved by 8:1 compression, and in most cases 16:1 compressed ECGs are clinically useful.
Abstract: Wavelets and wavelet packets have recently emerged as powerful tools for signal compression. Wavelet and wavelet packet-based compression algorithms based on embedded zerotree wavelet (EZW) coding are developed for electrocardiogram (ECG) signals, and eight different wavelets are evaluated for their ability to compress Holter ECG data. Pilot data from a blind evaluation of compressed ECG's by cardiologists suggest that the clinically useful information present in original ECG signals is preserved by 8:1 compression, and in most cases 16:1 compressed ECG's are clinically useful.
Citations
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References
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TL;DR: This work has evaluated all possible reasonably short (less than 36 taps in the synthesis/analysis pair) minimum-order biorthogonal wavelet filter banks and selected the filters best suited to image compression.
Abstract: Choice of filter bank in wavelet compression is a critical issue that affects image quality as well as system design. Although regularity is sometimes used in filter evaluation, its success at predicting compression performance is only partial. A more reliable evaluation can be obtained by considering an L-level synthesis/analysis system as a single-input, single-output, linear shift-variant system with a response that varies according to the input location module (2/sup L/,2/sup L/). By characterizing a filter bank according to its impulse response and step response in addition to regularity, we obtain reliable and relevant (for image coding) filter evaluation metrics. Using this approach, we have evaluated all possible reasonably short (less than 36 taps in the synthesis/analysis pair) minimum-order biorthogonal wavelet filter banks. Of this group of over 4300 candidate filter banks, we have selected and present here the filters best suited to image compression. While some of these filters have been published previously, others are new and have properties that make them attractive in system design. >
679 citations
"Wavelet and wavelet packet compress..." refers methods in this paper
...[23] have proposed an explanation of why some wavelets are good for compression and others are not; however, their method still requires that compression be performed experimentally on a series of impulse functions....
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TL;DR: A preprocessing program developed for real-time monitoring of the electrocardiogram by digital computer has proved useful for rhythm analysis.
Abstract: A preprocessing program developed for real-time monitoring of the electrocardiogram by digital computer has proved useful for rhythm analysis. The program suppresses low amplitude signals, reduces the data rate by a factor of about 10, and codes the result in a form convenient for analysis.
374 citations
"Wavelet and wavelet packet compress..." refers methods in this paper
...Most lossy ECG compression algorithms belong to either of the following categories: direct data compression methods [8], [12], [25], which detect redundancies by direct analysis of actual signal samples; or transform methods [1], [3], [21], which rst transform the signal to some other time{frequency representation better suited for detecting and removing redundancies....
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TL;DR: A new algorithm for ECG signal compression is introduced that can be considered a generalization of the recently published average beat subtraction method, and was found superior at any bit rate.
Abstract: A new algorithm for ECG signal compression is introduced. The compression system is based on the subautoregression (SAR) model, known also as the long-term prediction (LTP) model. The periodicity of the ECG signal is employed in order to further reduce redundancy, thus yielding high compression ratios. The suggested algorithm was evaluated using an in-house database. Very low bit rates on the order of 70 b/s are achieved with a relatively low reconstruction error (percent RMS difference-PRD) of less than 10%. The algorithm was compared, using the same database, with the conventional linear prediction (short-term prediction-STP) method, and was found superior at any bit rate. The suggested algorithm can be considered a generalization of the recently published average beat subtraction method. >
262 citations
"Wavelet and wavelet packet compress..." refers methods in this paper
...Combining wavelet coding with techniques such as average heartbeat subtraction [2] or long-term prediction [4] could result in higher compression ratios and/or better quality reconstruction....
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TL;DR: In this paper, the authors used wavelet transforms to describe and recognize isolated cardiac beats and evaluated their capability of discriminating between normal, premature ventricular contraction, and ischemic beats by means of linear discriminant analysis.
Abstract: The authors' study made use of wavelet transforms to describe and recognize isolated cardiac beats. The choice of the wavelet family as well as the selection of the analyzing function into these families are discussed. The criterion used in the first case was the correct classification rate, and in the second case, the correlation coefficient between the original pattern and the reconstructed one. Two types of description have been considered-the energy-based representation and the extrema distribution estimated at each decomposition level-and their quality has been assessed by using principal component analysis. Their capability of discrimination between normal, premature ventricular contraction, and ischemic beats has been studied by means of linear discriminant analysis. This work leads also, for the problem at hand, to the identification of the most relevant resolution levels. >
232 citations
"Wavelet and wavelet packet compress..." refers methods in this paper
...Recently, wavelets have been applied to several problems in electrocardiology, including data compression [15]–[17], the analysis of ventricular late potentials [18], and the detection of ECG characteristic points [19], [20]....
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01 Jan 1993
TL;DR: In this article, the construction classique des analyses multiresolutions and des bases orthonormees d'ondelettes is adapted to the classique de analyses multiiresolutions.
Abstract: Nous adaptons la construction classique des analyses multiresolutions et des bases orthonormees d'ondelettes au cadre des fonctions definies sur [0,1]. Les proprietes importantes des bases d'ondelettes (regularite, localisation spatiale et oscillations) sont maintenues ainsi que l'existence d'un algorithme rapide (avec un traitement particulier aux extremites de l'intervalle)
206 citations
"Wavelet and wavelet packet compress..." refers background in this paper
...A fourth solution, put forth by Cohen, Daubechies, Jawerth, and Vial [4] and explained in some detail in [5], which avoids the problems mentioned above is to use a special set of basis functions at the edges of a signal and a conventional wavelet basis for the interior of the signal....
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