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•

Wavelet threshold based TDL and TDR algorithms for real-time ECG signal compression

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M.S. Manikandan¹, Samarendra Dandapat¹•Institutions (1)

Indian Institute of Technology Guwahati¹

01 Jan 2008-Biomedical Signal Processing and Control

TL;DR: Experimental results show that the TDR algorithm achieves the required compression data rate to meet the demands of wire/wireless link while the TDL algorithm does not, and demonstrates that the proposed TDR algorithms is suitable for real-time applications.

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57 citations

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

...2-D Compression algorithms Cut and align beats (CAB) approach (CAB+DCT) [59] Truncated singular value decomposition (TSVD) [60] JPEG2000 coding [61] CAB and modified SPIHT [62] JPEG2000:ECG signals with irregular periods [63] Table 2 Performance measures: compression efficiency and distortion...
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...D Compression algorithms Cut and align beats (CAB) approach (CAB+DCT) [59] Truncated singular value decomposition (TSVD) [60] JPEG2000 coding [61] CAB and modified SPIHT [62] JPEG2000:ECG signals with irregular periods [63] Table 2 Performance measures: compression efficiency and distortion Compression ratio (CR) [51]: CR ¼ amount of original data; bits amount of compressed data; bits ¼ Lbo Lbc , where Lbo and Lbc are the number of bits in the original and compressed data, respectively....
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...Compression algorithms under this category result in good compression performance at the cost of increased computational complexity and memory space requirements [15,20,45,60]....
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Journal Article•DOI•

ECG Data Encryption Then Compression Using Singular Value Decomposition

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Ting Yu Liu¹, Kuan Jen Lin¹, Hsi Chun Wu¹•Institutions (1)

Fu Jen Catholic University¹

01 May 2018-IEEE Journal of Biomedical and Health Informatics

TL;DR: Experimental results prove the first ETC approach for processing ECG data using the singular value decomposition technique to be an effective technique for assuring data security as well as compression performance forECG data.

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Abstract: Electrocardiogram (ECG) monitoring systems are widely used in healthcare. ECG data must be compressed for transmission and storage. Furthermore, there is a need to be able to directly process biomedical signals in encrypted domains to ensure the protection of patients’ privacy. Existing encryption-then-compression (ETC) approaches for multimedia using the state-of-the-art encryption techniques inevitably sacrifice the compression efficiency or signal quality. This paper presents the first ETC approach for processing ECG data. The proposed approach not only can protect data privacy but also provide the same quality of the reconstructed signals without sacrificing the compression efficiency relative to unencrypted compressions. Specifically, the singular value decomposition technique is used to compress the data such that the proposed system can provide quality-control compressed data, even though the data has been encrypted. Experimental results prove the proposed system to be an effective technique for assuring data security as well as compression performance for ECG data.

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52 citations

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

...We should point out that the PRD results reported in [18] should be for PRDN....
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...Both the periodic length and periodic pattern may vary to a certain degree [18]....
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...All of the segmented ECG cycles are normalized to the same periodic length n by using the transformation in [18]....
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...The commonly used transform methods include the Fourier transform [13], Karhunen-Loeve transform (KLT) [14], 2D discrete cosine transform (DCT) [15], Walsh transform [16], the wavelet transform [17], and singular value decomposition (SVD) [18]–[20]....
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Journal Article•DOI•

Hybrid method based on singular value decomposition and embedded zero tree wavelet technique for ECG signal compression

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Ranjeet Kumar¹, Anil Kumar¹, Girish Kumar Singh²•Institutions (2)

Indian Institute of Information Technology, Design and Manufacturing, Jabalpur¹, Indian Institute of Technology Roorkee²

01 Jun 2016-Computer Methods and Programs in Biomedicine

TL;DR: The proposed algorithm is efficient and flexible with different types of ECG signal for compression, and controls quality of reconstruction, and can play a big role to save the memory space of health data centres as well as save the bandwidth in telemedicine based healthcare systems.

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51 citations

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

...2-D array of ECG data is decomposed with SVD into three triplets [26]:...
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...Previous SVD based technique [26] was limited with lower compression rate...
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...Similarly, singular value decomposition (SVD) based techniques have been presented, based on beat correlation properties of the ECG signal to enhance compression performance of the algorithm [26]....
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...It describes the basic information of quasi-periodic signal, which can be represented using linear combination of singular triplets [26]....
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...In the field of ECG signal compression, several techniques have been reported in literature [2,7–9,26,31–35], and have claimed their efficiency in terms of higher compression performance as compared to the existing methods....
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Journal Article•DOI•

An ECG signal compression technique using ASCII character encoding

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Sourav Mukhopadhyay¹, S. Mitra¹, Madhuchhanda Mitra¹•Institutions (1)

University of Calcutta¹

01 Jul 2012-Measurement

TL;DR: The data reconstruction algorithm has been developed using the reversed logic and it is seen that data is reconstructed preserving the significant ECG signal morphology.

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49 citations

Journal Article•DOI•

A Novel Blaschke Unwinding Adaptive-Fourier-Decomposition-Based Signal Compression Algorithm With Application on ECG Signals

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Chunyu Tan¹, Liming Zhang¹, Hau-Tieng Wu²•Institutions (2)

University of Macau¹, Duke University²

01 Mar 2019-IEEE Journal of Biomedical and Health Informatics

TL;DR: A novel signal compression algorithm based on the Blaschke unwinding adaptive Fourier decomposition, which utilizes the Nevanlinna factorization and the maximal selection principle in each decomposition step, and achieves a faster convergence rate with higher fidelity.

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Abstract: This paper presents a novel signal compression algorithm based on the Blaschke unwinding adaptive Fourier decomposition (AFD). The Blaschke unwinding AFD is a newly developed signal decomposition theory. It utilizes the Nevanlinna factorization and the maximal selection principle in each decomposition step, and achieves a faster convergence rate with higher fidelity. The proposed compression algorithm is applied to the electrocardiogram signal. To assess the performance of the proposed compression algorithm, in addition to the generic assessment criteria, we consider the less discussed criteria related to the clinical needs—for the heart rate variability analysis purpose, how accurate the R-peak information is preserved is evaluated. The experiments are conducted on the MIT-BIH arrhythmia benchmark database. The results show that the proposed algorithm performs better than other state-of-the-art approaches. Meanwhile, it also well preserves the R-peak information.

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48 citations

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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