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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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Citations
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Journal ArticleDOI

A novel algorithm for wavelet based ECG signal coding

TL;DR: A novel algorithm for wavelet based ECG signal coding is proposed that outperforms than other coders such as Djohn, EZW, SPIHT, etc., exits in the literature in terms of simplicity and coding efficiency.
Journal ArticleDOI

An improved closed form design method for the cosine modulated filter banks using windowing technique

TL;DR: An improved closed form method for designing cosine modulated filter banks with prescribed stopband attenuation and channel overlap based on optimum passband frequency is presented, which is calculated using empirical formulas instead of using time consuming single or multivariable optimization.
Journal ArticleDOI

Computationally efficient sub-band coding of ECG signals.

TL;DR: It is concluded that the present scheme, suitable for real time implementation on a PC, can provide compression ratios between 5 and 15 without loss of clinical information.
Journal ArticleDOI

DWT Based Detection of R-peaks and Data Compression of ECG Signals

TL;DR: An algorithm based on discrete wavelet transforms (DWT) for detection of R-peaks, computation ofR-R interval and data compression of ECG signals is presented and is robust to noise.
Journal ArticleDOI

ECG Signal Compression using Optimum Wavelet Filter Bank Based on Kaiser Window

TL;DR: An optimized wavelet filter bank based methodology is presented for compression of electrocardiogram (ECG) signal, which employs a modified thresholding, which improves the compression of signal as compared to earlier existing thresholding technique.
References
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Proceedings ArticleDOI

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