A wavelet transform-based ECG compression method guaranteeing desired signal quality
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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TL;DR: The hosSQI formula combines two already known SQIs, kurtosis and skewness, exploiting the related properties to improve their performance, and is proposed a promising tool for the real-time assessment of ECG signal quality and physical activity, also during intense exercise.
19 citations
29 Aug 2009
TL;DR: This paper proposes a mobile wireless Electrocardiograph monitoring and recording device based on OMAP processor that takes the advantages of dual-core OMAP processors.
Abstract: Remote medical monitoring system has being developed very fast in recent years. In order to predict complications before patient cause serious harm, we need a wearable, wireless and low power patient device to monitor their electrical charges at real time. In this paper we propose a mobile wireless Electrocardiograph monitoring and recording device based on OMAP processor. This solution takes the advantages of dual-core OMAP processor. Real time tasks such as ECG analysis are assigned to DSP core; other tasks are assigned to ARM core. The ECG monitoring device integrates WiFi to connect with internet, it can exchange data with remote computers. With the help of this Wireless ECG monitoring system doctors can capture the patient's information easily, patients no necessity for staying in hospital.
16 citations
Cites background from "A wavelet transform-based ECG compr..."
...There are many ECG signal compression algorithm shown in [12][13][14]....
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13 Dec 2007
TL;DR: A novel and simple quality controlled ECG compression algorithm is proposed using Wavelet energy based diagnostic distortion (WEDD) measure, which localizes the error between the original and the reconstructed signals in the feature space.
Abstract: A novel and simple quality controlled ECG compression algorithm is proposed using Wavelet energy based diagnostic distortion (WEDD) measure, which localizes the error between the original and the reconstructed signals in the feature space. The compression algorithm is based on Wavelet transform, energy based thresholding and an adaptive quantization scheme. The quality control criterion allows clinically acceptable reconstructions while maintaining high compression ratios. The advantage of the proposed algorithm is that the threshold value and the quantization bits are chosen automatically in few iterations so that the quality of the reconstructed signal is controlled.
15 citations
Cites background from "A wavelet transform-based ECG compr..."
...The WEDD can be written as follows: WEDD = f(Xn, Xn = f(N, EPEi, b) ) // where, Xn = {x[0], x[1], x[2], ....
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...Many low complexity Wavelet/Wavelet packets based ECG compression algorithms are reported [2]- [5], [7], [8]....
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...The PRD measure fails to characterize the local distortion of an ECG signal [2], [9], [10]....
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TL;DR: The simulation result included in this paper shows the clearly increased efficacy and performance in the field of biomedical signal processing.
Abstract: In this paper, a wavelet based methodology is presented for compression of electrocardiogram (ECG) signal. The methodology employs new wavelet filters whose coefficients are derived with beta function and its derivatives. A comparative study of performance of different existing wavelet filters and the Beta wavelet filters 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 Beta wavelet filters give better compression ratio 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.
15 citations
Cites methods from "A wavelet transform-based ECG compr..."
...For this, the following fidelity assessment parameters are considered [8, 38, 39]: • Compression ratio (CR): CR = Length of Original Signal Length of Compressed signal (22)...
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01 Jan 2015
TL;DR: This paper presents a review on state-of-art diagnostic information extraction approaches and their applications in various ECG signal processing schemes such as quality assessment and cardiac disease detection and demonstrates that the proposed MSD measure is effective in quantifying diagnostic information in MECG.
Abstract: Electrocardiogram (ECG) contains the information about the contraction and relaxation of heart chambers. This diagnostic information will change due to various cardiovascular diseases. This information is used by a cardiologist for accurate detection of various life-threatening cardiac disorders. ECG signals are subjected to number of processing, for computer aided detection and localization of cardiovascular diseases. These processing schemes are categorized as filtering, synthesis, compression and transmission. Quantifying diagnostic information from an ECG signal in an efficient way, is always a challenging task in the area of signal processing. This paper presents a review on state-of-art diagnostic information extraction approaches and their applications in various ECG signal processing schemes such as quality assessment and cardiac disease detection. Then, a new diagnostic measure for multilead ECG (MECG) is proposed. The proposed diagnostic measure (MSD) is defined as the difference between multivariate sample entropy values for original and processed MECG signals. The MSD measure is evaluated over MECG compression framework. Experiments are conducted over both normal and pathological MECG from PTB database. The results demonstrate that the proposed MSD measure is effective in quantifying diagnostic information in MECG. The MSD measure is also compare with other measures such as WEDD, PRD and RMSE.
14 citations
Cites background or methods from "A wavelet transform-based ECG compr..."
...The normalized cross-correlation (NCC) measure has been used to evaluate the objective quality of ECG signals [14]....
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...Chen and Itoh proposed an objective diagnostic distortion measure for evaluating the quality of ECG signal [14]....
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References
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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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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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869 citations
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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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