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Journal ArticleDOI

ECG data compression techniques-a unified approach

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TLDR
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. >

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Proceedings ArticleDOI

High diagnostic quality ECG compression and CS signal reconstruction in body sensor networks

TL;DR: This work proposes to fully exploit the wavelet capability to operate at different levels of signal detail at different time scales, and statistically shows that diagnostic quality preservation is possible even at high compression rates.
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Multiwavelet and Biological Signal Processing

TL;DR: The simulation results show that the Cardinal Balanced Multiwavelet (cardbal2) by the means of identity (Id) prefiltering method to be the best effective transformation of ECG signals.
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A New Method for Dictionary Matrix Optimization in ECG Compressed Sensing

TL;DR: A new method for dictionary matrix optimization with the aim of improving the reconstruction quality of ECG signals delivered by a Compressed Sensing algorithm exploits the features common to all the records of the ECG signal of the same patient to obtain an optimized dictionary with reduced size.
Proceedings ArticleDOI

A tutorial review on data compression with detection of fetal heart beat from noisy ECG

TL;DR: Adapt filters for the task of separation of FECG signal from the abdominal ECG signal are implemented and the nature of the signal is understood to reduce the redundancy involved in theECG signal with low noise.
Proceedings ArticleDOI

ECG signal coding using wavelet transform and binary arithmetic coder

TL;DR: A new system for ECG compression using the discrete wavelet transform (DWT) is presented and a new method to code the quantized wavelet coefficients is proposed that exploits both the sparseness and the self-similarity amongst the subbands.
References
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Journal ArticleDOI

A mathematical theory of communication

TL;DR: This final installment of the paper considers the case where the signals or the messages or both are continuously variable, in contrast with the discrete nature assumed until now.
Journal ArticleDOI

A Method for the Construction of Minimum-Redundancy Codes

TL;DR: A minimum-redundancy code is one constructed in such a way that the average number of coding digits per message is minimized.
Journal ArticleDOI

Linear prediction: A tutorial review

TL;DR: This paper gives an exposition of linear prediction in the analysis of discrete signals as a linear combination of its past values and present and past values of a hypothetical input to a system whose output is the given signal.
Journal ArticleDOI

Arithmetic coding for data compression

TL;DR: The state of the art in data compression is arithmetic coding, not the better-known Huffman method, which gives greater compression, is faster for adaptive models, and clearly separates the model from the channel encoding.
Proceedings ArticleDOI

Orthogonal transforms for digital signal processing

TL;DR: The utility and effectiveness of these transforms are evaluated in terms of some standard performance criteria such as computational complexity, variance distribution, mean-square error, correlated rms error, rate distortion, data compression, classification error, and digital hardware realization.
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