ECG data compression using truncated singular value decomposition

doi:10.1109/4233.966104

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ECG data compression using truncated singular value decomposition

Journal Article•DOI•

ECG data compression using truncated singular value decomposition

Jyh-Jong Wei¹, Chuang-Jan Chang, Nai-Kuan Chou, Gwo-Jen Jan•Institutions (1)

National Taiwan University¹

01 Dec 2001-Vol. 5, Iss: 4, pp 290-299

TL;DR: The results showed that truncated SVD method can provide an efficient coding with high-compression ratios and demonstrated the method as an effective technique for ECG data storage or signals transmission.

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Abstract: The method of truncated singular value decomposition (SVD) is proposed for electrocardiogram (ECG) data compression. The signal decomposition capability of SVD is exploited to extract the significant feature components of the ECG by decomposing the ECG into a set of basic patterns with associated scaling factors. The signal information is mostly concentrated within a certain number of singular values with related singular vectors due to the strong interbeat correlation among ECG cycles. Therefore, only the relevant parts of the singular triplets need to be retained as the compressed data for retrieving the original signals. The insignificant overhead can be truncated to eliminate the redundancy of ECG data compression. The Massachusetts Institute of Technology-Beth Israel Hospital arrhythmia database was applied to evaluate the compression performance and recoverability in the retrieved ECG signals. The approximate achievement was presented with an average data rate of 143.2 b/s with a relatively low reconstructed error. These results showed that the truncated SVD method can provide efficient coding with high-compression ratios. The computational efficiency of the SVD method in comparing with other techniques demonstrated the method as an effective technique for ECG data storage or signals transmission.

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Journal Article•DOI•

Data Compression in Smart Distribution Systems via Singular Value Decomposition

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Julio Cesar Stacchini de Souza¹, Tatiana M. L. Assis², Bikash C. Pal³•Institutions (3)

Federal Fluminense University¹, Federal University of Rio de Janeiro², Imperial College London³

01 Jan 2017-IEEE Transactions on Smart Grid

TL;DR: The proposed methodology for lossy data compression in smart distribution systems using the singular value decomposition technique is capable of significantly reducing the volume of data to be transmitted through the communications network and accurately reconstructing the original data.

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Abstract: Electrical distribution systems have been experiencing many changes in recent times. Advances in metering system infrastructure and the deployment of a large number of smart meters in the grid will produce a big volume of data that will be required for many different applications. Despite the significant investments taking place in the communications infrastructure, this remains a bottleneck for the implementation of some applications. This paper presents a methodology for lossy data compression in smart distribution systems using the singular value decomposition technique. The proposed method is capable of significantly reducing the volume of data to be transmitted through the communications network and accurately reconstructing the original data. These features are illustrated by results from tests carried out using real data collected from metering devices at many different substations.

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140 citations

Journal Article•DOI•

Compression of electrocardiogram signals using JPEG2000

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Ali Bilgin¹, Michael W. Marcellin¹, Maria I. Altbach•Institutions (1)

University of Arizona¹

01 Nov 2003-IEEE Transactions on Consumer Electronics

TL;DR: The goal of this paper is to demonstrate how the JPEG2000 codec can be used to compress electrocardiogram (ECG) data, and to demonstrate the ECG application as an example that can be extended to other signals that exist within the consumer electronics realm.

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Abstract: JPEG2000 is the latest international standard for compression of still images. Although the JPEG2000 codec is designed to compress images, we illustrate that it can also be used to compress other signals. As an example, we illustrate how the JPEG2000 codec can be used to compress electrocardiogram (ECG) data. Experiments using the MIT-BIH arrhythmia database illustrate that the proposed approach outperforms many existing ECG compression schemes. The proposed scheme allows the use of existing hardware and software JPEG2000 codecs for ECG compression, and can be especially useful in eliminating the need for specialized hardware development. The desirable characteristics of the JPEG2000 codec, such as precise rate control and progressive quality, are retained in the presented scheme. The goal of this paper is to demonstrate the ECG application as an example. This example can be extended to other signals that exist within the consumer electronics realm.

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138 citations

Cites background or methods from "ECG data compression using truncate..."

...These portable ECG devices record and store the data for subsequent interpretation by a doctor....
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...We used the MIT-BIH arrhythmia database to evaluate the performance of the proposed scheme....
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Journal Article•DOI•

An effective and efficient compression algorithm for ECG signals with irregular periods

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Hsiao-Hsuan Chou¹, Ying-Jui Chen¹, Yu-Chien Shiau², Te-Son Kuo¹•Institutions (2)

National Taiwan University¹, Memorial Hospital of South Bend²

05 Jun 2006-IEEE Transactions on Biomedical Engineering

TL;DR: An effective and efficient preprocessing algorithm for two-dimensional electrocardiogram (ECG) compression to better compress irregular ECG signals by exploiting their inter- and intra-beat correlations and is shown to outperform some existing arts in the literature.

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Abstract: This paper presents an effective and efficient preprocessing algorithm for two-dimensional (2-D) electrocardiogram (ECG) compression to better compress irregular ECG signals by exploiting their inter-and intra-beat correlations. To better reveal the correlation structure, we first convert the ECG signal into a proper 2-D representation, or image. This involves a few steps including QRS detection and alignment, period sorting, and length equalization. The resulting 2-D ECG representation is then ready to be compressed by an appropriate image compression algorithm. We choose the state-of-the-art JPEG2000 for its high efficiency and flexibility. In this way, the proposed algorithm is shown to outperform some existing arts in the literature by simultaneously achieving high compression ratio (CR), low percent root mean squared difference (PRD), low maximum error (MaxErr), and low standard derivation of errors (StdErr). In particular, because the proposed period sorting method rearranges the detected heartbeats into a smoother image that is easier to compress, this algorithm is insensitive to irregular ECG periods. Thus either the irregular ECG signals or the QRS false-detection cases can be better compressed. This is a significant improvement over existing 2-D ECG compression methods. Moreover, this algorithm is not tied exclusively to JPEG2000. It can also be combined with other 2-D preprocessing methods or appropriate codecs to enhance the compression performance in irregular ECG cases.

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110 citations

Cites background or methods from "ECG data compression using truncate..."

...Comparing to the literature, we see that existing 2-D ECG compression methods [1], [4] show good results for normal ECG signals but not for irregular ones....
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...It is clear that the proposed Approach 1 perform better than [1], [4], [15], [16], especially in irregular ECG record 119....
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...By Period Normalization: For effective length equalization, Wei [4] proposed the period normalization method that scales the periods to form a 2-...
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...Although period normalization cannot retain the ECG losslessly and it cannot handle ECG with extremely irregular periods very well, its global performance indicator PRD is better than Approach 1 and other works [1], [4], [15], [16] in most cases....
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...Wei [4] used “period normalization and truncated SVD algorithm” to compress 2-D ECG arrays....
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Journal Article•DOI•

Wavelet-based electrocardiogram signal compression methods and their performances: A prospective review

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M. Sabarimalai Manikandan¹, Samarendra Dandapat²•Institutions (2)

Indian Institute of Technology Bhubaneswar¹, Indian Institute of Technology Guwahati²

01 Nov 2014-Biomedical Signal Processing and Control

TL;DR: A prospective review of wavelet-based ECG compression methods and their performances based upon findings obtained from various experiments conducted using both clean and noisy ECG signals is presented.

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110 citations

Cites background or methods from "ECG data compression using truncate..."

...Furthermore, the aliasing effect may ccur due to improper designs of interpolation filter and downampling factors [157]....
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...In many 2-D compression methods, the effect of smoothing of background noise is shown [157,159]....
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...D DCT [156], truncated singular value decomposition (TSVD) [157], JPEG2000 [158], CAB and modified SPIHT [159] and JPEG2000 coding for ECG with irregular periods [160] exploit both sample-to-sample and beat-to-beat correlation....
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...Wei [157] Yes Yes No Yes No Frame SVD Uniform quantization...
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...In literature, 2-D ECG compression methods such as CAB+2-D DCT [154], 2-D wavelet packet transform (WPT) [155], 2-D DCT [156], truncated singular value decomposition (TSVD) [157], JPEG2000 [158], CAB and modified SPIHT [159] and JPEG2000 coding for ECG with irregular periods [160] exploit both sample-to-sample and beat-to-beat correlation....
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Journal Article•DOI•

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Xuezhi Zhao¹, Bangyan Ye¹•Institutions (1)

South China University of Technology¹

01 May 2009-Mechanical Systems and Signal Processing

TL;DR: In this article, a signal can be decomposed into the linear sum of a series of component signals by Hankel matrix-based SVD, and essentially what the component signals reflect are projections of original signal on the orthonormal bases of m-dimensional and n-dimensional vector spaces.

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103 citations

Cites methods from "ECG data compression using truncate..."

...Most references on the signal processing of SVD always place their emphasis on practicality and SVD is only used as a tool to solve certain specific signal processing problem, such as feature extraction [3–6], data compression [7], noise reduction [8–11], speech coding [12] and so on, while the study on the essence of signal decomposition of SVD is very few, in this paper this essence has been ascertained, and on this basis the similarity mechanism of signal processing between SVD and wavelet transform is explained from the angle of basis of vector space....
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References

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Book•

Matrix computations

[...]

Gene H. Golub

01 Jan 1983

34,729 citations

"ECG data compression using truncate..." refers background in this paper

...Therefore, the SVD of the matrix can be performed as [20], where are the left and right singular vectors, respectively....
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Journal Article•DOI•

ECG data compression techniques-a unified approach

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S.M.S. Jalaleddine¹, C.G. Hutchens¹, R.D. Strattan², W. A. Coberly²•Institutions (2)

Oklahoma State University–Stillwater¹, University of Tulsa²

01 Apr 1990-IEEE Transactions on Biomedical Engineering

TL;DR: The theoretical bases behind the direct ECG data compression schemes are presented and classified into three categories: tolerance-comparison compression, DPCM, and entropy coding methods and a framework for evaluation and comparison of ECG compression schemes is presented.

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Abstract: Electrocardiogram (ECG) compression techniques are compared, and a unified view of these techniques is established. ECG data compression schemes are presented in two major groups: direct data compression and transformation methods. The direct data compression techniques are ECG differential pulse code modulation (DPCM) and entropy coding, AZTEC, Turning-point, CORTES, Fan and SAPA algorithms, peak-picking, and cycle-to-cycle compression methods. The transformation methods include Fourier, Walsh, and Karhunen-Loeve transforms. The theoretical bases behind the direct ECG data compression schemes are presented and classified into three categories: tolerance-comparison compression, DPCM, and entropy coding methods. A framework for evaluation and comparison of ECG compression schemes is presented. >

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690 citations

"ECG data compression using truncate..." refers methods in this paper

...The compression techniques for an ECG have been extensively discussed [ 1 ] and can be classified into the following three major categories....
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Journal Article•DOI•

Wavelet compression of ECG signals by the set partitioning in hierarchical trees algorithm

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Zhitao Lu¹, Dong Youn Kim², William A. Pearlman¹•Institutions (2)

Rensselaer Polytechnic Institute¹, Yonsei University²

01 Jul 2000-IEEE Transactions on Biomedical Engineering

TL;DR: A wavelet electrocardiogram (ECG) data 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.

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Abstract: A wavelet electrocardiogram (ECG) data codec based on the set partitioning in hierarchical trees (SPIHT) compression algorithm is proposed in this paper. The SPIHT algorithm (A. Said and W.A. Pearlman, IEEE Trans. Ccts. Syst. II, vol. 6, p. 243-50, 1996) has achieved notable success in still image coding. The authors modified the algorithm for the one-dimensional case and applied it to compression of ECG data. Experiments on selected records from the MIT-BIH arrhythmia database revealed 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.

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521 citations

Journal Article•DOI•

Wavelet and wavelet packet compression of electrocardiograms

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M.L. Hilton¹•Institutions (1)

University of South Carolina¹

01 May 1997-IEEE Transactions on Biomedical Engineering

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.

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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.

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445 citations

"ECG data compression using truncate..." refers methods in this paper

...[23]) provides a better performance than previous wavelet-based methods (Hilton [22] and Djohan et al....
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Journal Article•DOI•

AZTEC, a Preprocessing Program for Real-Time ECG Rhythm Analysis

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Jerome R. Cox¹, Floyd M. Nolle¹, H. A. Fozzard², G. C. Oliver¹•Institutions (2)

Washington University in St. Louis¹, University of Chicago²

01 Apr 1968-IEEE Transactions on Biomedical Engineering

TL;DR: A preprocessing program developed for real-time monitoring of the electrocardiogram by digital computer has proved useful for rhythm analysis.

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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.

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374 citations