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Journal ArticleDOI

A wavelet transform-based ECG compression method guaranteeing desired signal quality

01 Dec 1998-IEEE Transactions on Biomedical Engineering (IEEE)-Vol. 45, Iss: 12, pp 1414-1419
TL;DR: A new electrocardiogram compression method based on orthonormal wavelet transform and an adaptive quantization strategy, by which a predetermined percent root mean square difference (PRD) can be guaranteed with high compression ratio and low implementation complexity are presented.
Abstract: This paper presents a new electrocardiogram (ECG) compression method based on orthonormal wavelet transform and an adaptive quantization strategy, by which a predetermined percent root mean square difference (PRD) can be guaranteed with high compression ratio and low implementation complexity.
Citations
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Proceedings ArticleDOI
01 Nov 2009
TL;DR: An efficient Electrocardiogram (ECG) signal compression method based on wavelet transform that combines the adapted SPIHT method with VKTP (Vector K-Tree Partitioning) coder to improve the compression ratio while maintaining a good signal quality is presented.
Abstract: In this paper, an efficient Electrocardiogram (ECG) signal compression method based on wavelet transform is presented. The proposed method combines the adapted SPIHT (Set Partitioning In Hierarchical Trees) method with VKTP (Vector K-Tree Partitioning) coder. The SPIHT method is based on the use of wavelet transform which is very well suited to locate the energy of the signal in fewer coefficients. Using the VKTP algorithm, to encode the generated bit stream of SPIHT algorithm, we achieve high compression performances. The tests of this lossy compression/ decompression technique are performed on many ECG records from Arrhythmia Database. The obtained results illustrate the capabilities of the proposed approach to improve the compression ratio while maintaining a good signal quality.

14 citations

Journal ArticleDOI
TL;DR: This paper presents a high performance quality-guaranteed two-dimensional (2D) single-lead ECG compression algorithm using singular value decomposition (SVD) and lossless-ASCII-character-encoding (LLACE)-based techniques.

14 citations

Proceedings ArticleDOI
16 Jul 2008
TL;DR: This work attempts to evaluate the closeness of the objective quality measures with subjective measure and investigation may help to suggest a better quality criterion for optimizing rate-distortion algorithms.
Abstract: Measurement of quality is of fundamental importance to electrocardiogram (ECG) signal processing applications. A number of distortion measures are used for ECG signal quality assessment. A simple and widely used distortion measure is the percentage root mean square difference (PRD). It is an attractive measure due to its simplicity and mathematical convenience. But PRD is not a good measure of the true compression error and results in poor diagnostic relevance. In this paper, we discuss the advantages and drawbacks of the objective distortion measures using different compressed signals. With extensive analysis it is shown that although some distortion measures correlate well with the subjective evaluation for distortions resulting from a given compression method, they may not be reliable for evaluation of some other compression distortions. It is also concluded that a distortion measure should be subjectively meaningful in order to correlate a large or small quantitative distortion measure with bad and good quality. This work attempts to evaluate the closeness of the objective quality measures with subjective measure and investigation may help to suggest a better quality criterion for optimizing rate-distortion algorithms. Experimental results show that wavelet energy based diagnostic distortion (WEDD) measure is significantly better than other measures. This measure is sensitive to ECG feature changes and insensitive to smoothing of low-level background noise.

13 citations


Cites background or methods from "A wavelet transform-based ECG compr..."

  • ...Quality assessment is important in lossy methods since most of the reported methods employed thresholding of samples/coefficients directly or indirectly (via quantization scheme) [2]....

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  • ...It includes diagnostic distortion measures such as weighted PRD [2], weighted diagnostic distortion (WDD) [7], wavelet based weighted PRD (WWPRD) [8] and wavelet energy based diagnostic distortion (WEDD) [9] measure....

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  • ...The effectiveness of the global error measures such as MSE, NMSE, RMSE, NRMSE, PRD, SNR and NCC is analyzed with different sets of experiments [2], [5]....

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  • ...This is because the distortions introduced by the compression methods mainly depend on the type of methodology (amplitude zone time epoch coding (AZTEC), turning point (TP), Fan, prediction, interpolation, Fourier transform (FT), Karhunen-Loeve transform (KLT), Discrete cosine transform (DCT) [1], discrete sinc interpolation (DSI), Wavelet transform (WT) [2] vector quantization (VQ), etc....

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  • ...In general, the percentage rms difference (PRD) is a normalized value which indicates the error between original and reconstructed signals [2]....

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Proceedings ArticleDOI
01 Dec 2013
TL;DR: A ECG compression system is presented based on two-dimensional discrete wavelet transform (2D DWT) and Huffman coding technique and the average compression performance of algorithm is 65% with 0.999 correlation score.
Abstract: In this paper, a ECG compression system is presented based on two-dimensional discrete wavelet transform (2D DWT) and Huffman coding technique. In this method, two different approaches are utilized to construct a 2D array of 1D ECG signal using cut and align (CAB) technique, therefore ECG 2D array is decomposed with 2D DWT which results more number of insignificant coefficients. They are considered as zero amplitude value which accelerate compression rate and Huffman coding maintains the signal quality due to its lossless nature of compression. The average compression performance of algorithm is 65% with 0.999 correlation score.

13 citations


Cites background or methods from "A wavelet transform-based ECG compr..."

  • ...In the past two decades, a substantial progress has been made in the field of data compression [11-24]....

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  • ...Recently transform based compression techniques are has become popular for ECG signals; especially wavelet transform based several techniques [13, 15-24]....

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  • ...They can be categorized into three main types: direct techniques [18], parameter extraction [9-11] and transform and coding based techniques [12-23]....

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Journal ArticleDOI
TL;DR: In this article, an optimised wavelet filter bank based methodology is presented for compression of Electrocardiogram (ECG) signal using simple linear optimisation, the methodology employs new wavelet filtering bank whose coefficients are derived with different window techniques such as Kaiser and Blackman windows, which gives better compression ratio and also yields good fidelity parameters as compared to other wavelet filters.
Abstract: In this paper, an optimised wavelet filter bank based methodology is presented for compression of Electrocardiogram (ECG) signal. The methodology employs new wavelet filter bank whose coefficients are derived with different window techniques such as Kaiser and Blackman windows using simple linear optimisation. A comparative study of performance of different existing wavelet filters and the proposed wavelet filter is made in terms of Compression Ratio (CR), Percent Root mean square Difference (PRD), Mean Square Error (MSE) and Signal-to-Noise Ratio (SNR). When compared, the developed wavelet filter gives better CR and also yields good fidelity parameters as compared to other wavelet filters. The simulation result included in this paper shows the clearly increased efficacy and performance in the field of biomedical signal processing.

11 citations


Cites result from "A wavelet transform-based ECG compr..."

  • ...The simulated results compare with the other algorithms or methods (Chen et al., 2008; Chen and Itoh, 1998) results show the presented results of ECG compression based on Kaiser and Blackman wavelet is better than the others....

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References
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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


"A wavelet transform-based ECG compr..." refers methods in this paper

  • ...Since detailed mathematical aspects of wavelet theory can b found elsewhere [16], here, we shall merely describe the structure of a DOWT-based coding system shown in Fig....

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  • ...The proposed algorithm was implemented on a SparcStation 2 computer, where the wavelet-based filters with 10-taps were designed by Daubechies’s algorithm [16], the layer was set to , the buffer size for segmenting input ECG signals was set to , and the Lempel–Ziv–Welch (LZW) encoder [20] was chosen as the entropy encoder for simplicity....

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Journal ArticleDOI
TL;DR: A new compression algorithm is introduced that is based on principles not found in existing commercial methods in that it dynamically adapts to the redundancy characteristics of the data being compressed, and serves to illustrate system problems inherent in using any compression scheme.
Abstract: Data stored on disks and tapes or transferred over communications links in commercial computer systems generally contains significant redundancy. A mechanism or procedure which recodes the data to lessen the redundancy could possibly double or triple the effective data densitites in stored or communicated data. Moreover, if compression is automatic, it can also aid in the rise of software development costs. A transparent compression mechanism could permit the use of "sloppy" data structures, in that empty space or sparse encoding of data would not greatly expand the use of storage space or transfer time; however , that requires a good compression procedure. Several problems encountered when common compression methods are integrated into computer systems have prevented the widespread use of automatic data compression. For example (1) poor runtime execution speeds interfere in the attainment of very high data rates; (2) most compression techniques are not flexible enough to process different types of redundancy; (3) blocks of compressed data that have unpredictable lengths present storage space management problems. Each compression ' This article was written while Welch was employed at Sperry Research Center; he is now employed with Digital Equipment Corporation. 8 m, 2 /R4/OflAb l strategy poses a different set of these problems and, consequently , the use of each strategy is restricted to applications where its inherent weaknesses present no critical problems. This article introduces a new compression algorithm that is based on principles not found in existing commercial methods. This algorithm avoids many of the problems associated with older methods in that it dynamically adapts to the redundancy characteristics of the data being compressed. An investigation into possible application of this algorithm yields insight into the compressibility of various types of data and serves to illustrate system problems inherent in using any compression scheme. For readers interested in simple but subtle procedures, some details of this algorithm and its implementations are also described. The focus throughout this article will be on transparent compression in which the computer programmer is not aware of the existence of compression except in system performance. This form of compression is "noiseless," the decompressed data is an exact replica of the input data, and the compression apparatus is given no special program information, such as data type or usage statistics. Transparency is perceived to be important because putting an extra burden on the application programmer would cause

2,426 citations


"A wavelet transform-based ECG compr..." refers methods in this paper

  • ...The proposed algorithm was implemented on a SparcStation 2 computer, where the wavelet-based filters with 10-taps were designed by Daubechies’s algorithm [16], the layer was set to , the buffer size for segmenting input ECG signals was set to , and the Lempel‐Ziv‐Welch (LZW) encoder [ 20 ] was chosen as the entropy encoder for simplicity....

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Journal ArticleDOI
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.
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. >

690 citations


"A wavelet transform-based ECG compr..." refers methods in this paper

  • ...In most cases, direct methods are superior to transform methods with respect to system complexity and the error control mechanism, however, transform methods usually achieve higher compression ratios and are insensitive to the noise contained in original ECG signals [1]....

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  • ...In direct methods, the compression is done directly on the ECG samples; examples include the amplitude zone time epoch coding (AZTEC), the turning point (TP), the coordinate reduction time encoding system (CORTES), the scan-along polygonal approximation (SAPA), peak-picking, cycle-to-cycle, and differential pulse code modulation (DPCM) [1]–[4]....

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Journal ArticleDOI
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.

445 citations