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Journal ArticleDOI

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
More filters
Proceedings ArticleDOI
25 Nov 2008
TL;DR: A new method for load forecasting based on LS-SVM, PSO and wavelet transform, which has greater generality ability and higher accuracy than other predictors.
Abstract: A new method for load forecasting based on LS-SVM, PSO and wavelet transform is proposed. The wavelet transform is adopted to decompose the historical data, so the approximate part and several detail parts are obtained. The results of wavelet transform are predicted by a separate LS-SVM predictor. PSO is employed to determine these parameters of SVM model. The novel forecast model integrates the advantage of WT, PSO and LS-SVM. Compared with other predictors, this forecast model has greater generality ability and higher accuracy.

6 citations


Cites methods from "Wavelet and wavelet packet compress..."

  • ...Among these methods, wavelet transform has shown promising results in various areas [19][20]....

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Proceedings ArticleDOI
01 Dec 2007
TL;DR: A compression method, based on the choice of a wavelet that matches the electrocardiogram signal to be compressed, is proposed in this paper and compared with the compression using the classical wavelet Db3.
Abstract: A compression method, based on the choice of a wavelet that matches the electrocardiogram signal to be compressed, is proposed in this paper. The coefficients of the scaling filter that minimize the distortion of the compressed signal are used to determine the wavelet. The choice of the scaling filter is done by the parametrization of the scaling coefficients in a way that all the constraints are satisfied for any set of parameters. A genetic algorithm is used to determine the parameters that minimize the distortion of the compressed signal. The performance of the proposed algorithm is analyzed and compared with the compression using the classical wavelet Db3.

6 citations


Cites methods from "Wavelet and wavelet packet compress..."

  • ...Compression techniques using wavelets have efficiently been applied to many different engineering sectors, especially to electrocardiogram (ECG) signals [5]....

    [...]

Proceedings ArticleDOI
13 Oct 1999
TL;DR: A wavelet electrocardiogram (ECG) signal encoder/decoder (codec) based on the set partitioning in hierarchical trees (SPIHT) compression algorithm is proposed and is significantly more efficient in compression and in computation than previously proposed ECG compression schemes.
Abstract: A wavelet electrocardiogram (ECG) signal encoder/decoder (codec) based on the set partitioning in hierarchical trees (SPIHT) compression algorithm is proposed. Experiments on selected records from the MIT-BIH arrhythmia database reveal that the proposed codec is significantly more efficient in compression and in computation than previously proposed ECG compression schemes. The coder also attains exact bit rate control and generates a bit stream progressive in quality or rate.

6 citations

Journal ArticleDOI
18 May 1998
TL;DR: Results obtained with analytical impulses and real impulses digitized in some European high-voltage laboratories show the effectiveness and reliability of the proposed automatic evaluation of the mean curve required by the ANSI/IEEE Std 4-1978.
Abstract: The paper proposes a method, based on the wavelet packet transform, for the automatic evaluation of the mean curve required by the ANSI/IEEE Std 4-1978. After some theoretical remarks on the wavelet packet transform, the fundamental stages of the method are illustrated in detail. Results obtained with analytical impulses and real impulses digitized in some European high-voltage laboratories show the effectiveness and reliability of the method. Suggestions to improve the present standard are also given.

6 citations


Additional excerpts

  • ...Other proposed relations are: Log, Sum, lP, Risk [ 14 ]....

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Journal ArticleDOI
TL;DR: This study proposes an arrhythmia-aware WSN system, and a new DSPbased WSN platform is developed for the high compression performance of physiological data in a ZigBee- based WSN.
Abstract: Telemedicine aided by wireless sensor networks (WSN) has recently become a healthcare trend. Many previous studies have adopted the ZigBee-based WSN to implement a platform and/or a telemedicine system. However, the low data rate and bandwidth have limited the maximum number of nodes in a WSN during continuous and simultaneous transmission. The issue of low data throughput has not been addressed in previous reseazch. In this study, we propose an arrhythmia-aware system, and a new DSPbased WSN platform is developed for the high compression performance of physiological data in a ZigBee-based WSN. Proven by simulations and several real tests, the combination of the proposed platform and the sensor nodes can lead to more bandwidth conservation and extend the WSN scale for the next generation of telemedicine system.

6 citations

References
More filters
Journal ArticleDOI
TL;DR: In this paper, it is shown that the difference of information between the approximation of a signal at the resolutions 2/sup j+1/ and 2 /sup j/ (where j is an integer) can be extracted by decomposing this signal on a wavelet orthonormal basis of L/sup 2/(R/sup n/), the vector space of measurable, square-integrable n-dimensional functions.
Abstract: Multiresolution representations are effective for analyzing the information content of images. The properties of the operator which approximates a signal at a given resolution were studied. It is shown that the difference of information between the approximation of a signal at the resolutions 2/sup j+1/ and 2/sup j/ (where j is an integer) can be extracted by decomposing this signal on a wavelet orthonormal basis of L/sup 2/(R/sup n/), the vector space of measurable, square-integrable n-dimensional functions. In L/sup 2/(R), a wavelet orthonormal basis is a family of functions which is built by dilating and translating a unique function psi (x). This decomposition defines an orthogonal multiresolution representation called a wavelet representation. It is computed with a pyramidal algorithm based on convolutions with quadrature mirror filters. Wavelet representation lies between the spatial and Fourier domains. For images, the wavelet representation differentiates several spatial orientations. The application of this representation to data compression in image coding, texture discrimination and fractal analysis is discussed. >

20,028 citations

Book
01 May 1992
TL;DR: This paper presents a meta-analyses of the wavelet transforms of Coxeter’s inequality and its applications to multiresolutional analysis and orthonormal bases.
Abstract: Introduction Preliminaries and notation The what, why, and how of wavelets The continuous wavelet transform Discrete wavelet transforms: Frames Time-frequency density and orthonormal bases Orthonormal bases of wavelets and multiresolutional analysis Orthonormal bases of compactly supported wavelets More about the regularity of compactly supported wavelets Symmetry for compactly supported wavelet bases Characterization of functional spaces by means of wavelets Generalizations and tricks for orthonormal wavelet bases References Indexes.

16,073 citations

Journal ArticleDOI
TL;DR: In this article, the regularity of compactly supported wavelets and symmetry of wavelet bases are discussed. But the authors focus on the orthonormal bases of wavelets, rather than the continuous wavelet transform.
Abstract: Introduction Preliminaries and notation The what, why, and how of wavelets The continuous wavelet transform Discrete wavelet transforms: Frames Time-frequency density and orthonormal bases Orthonormal bases of wavelets and multiresolutional analysis Orthonormal bases of compactly supported wavelets More about the regularity of compactly supported wavelets Symmetry for compactly supported wavelet bases Characterization of functional spaces by means of wavelets Generalizations and tricks for orthonormal wavelet bases References Indexes.

14,157 citations

Journal ArticleDOI
Ingrid Daubechies1
TL;DR: This work construct orthonormal bases of compactly supported wavelets, with arbitrarily high regularity, by reviewing the concept of multiresolution analysis as well as several algorithms in vision decomposition and reconstruction.
Abstract: We construct orthonormal bases of compactly supported wavelets, with arbitrarily high regularity. The order of regularity increases linearly with the support width. We start by reviewing the concept of multiresolution analysis as well as several algorithms in vision decomposition and reconstruction. The construction then follows from a synthesis of these different approaches.

8,588 citations


"Wavelet and wavelet packet compress..." refers methods in this paper

  • ...In the work described in this paper, was chosen to be Daubechie's W6 wavelet [10], which is illustrated in Figure 1....

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Journal ArticleDOI
TL;DR: The image coding results, calculated from actual file sizes and images reconstructed by the decoding algorithm, are either comparable to or surpass previous results obtained through much more sophisticated and computationally complex methods.
Abstract: Embedded zerotree wavelet (EZW) coding, introduced by Shapiro (see IEEE Trans. Signal Processing, vol.41, no.12, p.3445, 1993), is a very effective and computationally simple technique for image compression. We offer an alternative explanation of the principles of its operation, so that the reasons for its excellent performance can be better understood. These principles are partial ordering by magnitude with a set partitioning sorting algorithm, ordered bit plane transmission, and exploitation of self-similarity across different scales of an image wavelet transform. Moreover, we present a new and different implementation based on set partitioning in hierarchical trees (SPIHT), which provides even better performance than our previously reported extension of EZW that surpassed the performance of the original EZW. The image coding results, calculated from actual file sizes and images reconstructed by the decoding algorithm, are either comparable to or surpass previous results obtained through much more sophisticated and computationally complex methods. In addition, the new coding and decoding procedures are extremely fast, and they can be made even faster, with only small loss in performance, by omitting entropy coding of the bit stream by the arithmetic code.

5,890 citations


Additional excerpts

  • ...algorithm was inspired by that in [28]....

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