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.
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TL;DR: Experimental results show that the design method guarantees a high compression performance SQ scheme with statistically linear distortion, which can be independent of training data and can facilitate rapid error control.
Abstract: While wavelet-based electrocardiogram (ECG) data compression using scalar quantisation (SQ) yields excellent compression performance, a wavelet’s SQ scheme, however, must select a set of multilevel quantisers for each quantisation process. As a result of the properties of multiple-to-one mapping, however, this scheme is not conducive for reconstruction error control. In order to address this problem, this paper presents a single-variable control SQ scheme able to guarantee the reconstruction quality of wavelet-based ECG data compression. Based on the reversible round-off non-recursive discrete periodised wavelet transform (RRO-NRDPWT), the SQ scheme is derived with a three-stage design process that first uses genetic algorithm (GA) for high compression ratio (CR), followed by a quadratic curve fitting for linear distortion control, and the third uses a fuzzy decision-making for minimising data dependency effect and selecting the optimal SQ. The two databases, Physikalisch-Technische Bundesanstalt ...
4 citations
Cites methods from "A wavelet transform-based ECG compr..."
...With uniform quantisation, a closed-loop error control process was proposed for the quantisation scale determination using specified distortion as a termination condition (Chen & Itoh, 1998)....
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18 Jun 2015
TL;DR: Dual tree discrete wavelet decomposition based ECG signal compression is exploited using zero run-length coding techniques, with main advancement, its sensitivity of generating sparse data set that helps to enhance compression performance of system.
Abstract: An Electrocardiogram (ECG) signal compression becomes more area of interest due to increases demand of tel-e-healthcare system. In this manuscript, dual tree discrete wavelet decomposition (DT-DWT) based ECG signal compression is exploited using zero run-length coding techniques. The main advancement of proposed technique, its sensitivity of generating sparse data set that helps to enhance compression performance of system. Performance of method evaluated through compression ratio and percentage root-mean square difference and quality evaluated using the cross correlation between the original and reconstructed MIT-BIH records. As discuses in results, proposed method is good as compare to earlier developed techniques in term of compression.
4 citations
Cites background or methods from "A wavelet transform-based ECG compr..."
...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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...This can be categorized into three main sections as follows: direct techniques [1-8], parameter extraction [9-11] and transform and coding based techniques [12-23]....
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TL;DR: A wireless e-healthcare system that couples a UMTS 3G wireless network with a wireless local area network using UMTS-WLAN technology so patients can be almost anywhere and still receive real-time medical service.
Abstract: Wireless communication in e-healthcare environments is a new and promising area, but there is no efficient wireless telemedicine system that can be used in a wide area network. This paper presents a wireless e-healthcare system that couples a UMTS 3G wireless network with a wireless local area network using UMTS-WLAN technology. The medical instruments collect the patient's medical data and send them to the medical centre through a UMTS-WLAN access point or through a WLAN-enabled UMTS user equipment point (i.e., UMTS cellular terminal). Patients can be almost anywhere and still receive real-time medical service. The simulation studies using OPNET show the performance of our wireless e-healthcare system.
4 citations
TL;DR: The results show that nonlinear transform (ENOCA) gives better performance at high PRD where as at low PRD, DCT performs better.
Abstract: This paper presents and analyzes nonlinear transform-based method electrocardiogram (ECG) compression. The procedure used is similar to that used in linear transform-based method. The ECG signal is first transformed using (i) linear transform: discrete cosine transforms (DCT), Laplacian pyramid (LP), wavelet transform (WT) and it is transformed using (ii) nonlinear transform: essentially nonoscillatory cell average (ENOCA). The transformed coefficients (TC) are thresholded using the bisection algorithm in order to match the predefined user-specified percentage root mean square difference (PRD) within the tolerance. Then, the binary lookup table is made to store the position map for zero and nonzero coefficients (NZCs). The NZCs are quantized by Max–Lloyd quantizer followed by arithmetic coding. Lookup table is encoded by Huffman coding. The results are presented on different ECG signals of varying characteristics. The results show that nonlinear transform (ENOCA) gives better performance at high PRD where as at low PRD, DCT performs better.
4 citations
17 Mar 2009
TL;DR: An adaptive thresholding, based on the required signal-to-noise-ratio (SNR) and the concept of energy packing efficiency, is used to classify the wavelet coefficients into significant and insignificant ones using an efficient coding algorithm.
Abstract: This paper proposes a new wavelet-based ECG compression technique. An adaptive thresholding, based on the required signal-to-noise-ratio (SNR) and the concept of energy packing efficiency, is used to classify the wavelet coefficients into significant and insignificant ones. Both coefficients are encoded using an efficient coding algorithm. The proposed technique is tested using several records taken from the MIT-BIH Arrhythmia database. The results show that high compression ratios with SNR's better than 18dB can be achieved.
4 citations
Cites methods from "A wavelet transform-based ECG compr..."
...The correlation coefficient as defined in [ 9 ] is given as:...
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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