Literature DB >> 2186997

ECG data compression techniques--a unified approach.

S M Jalaleddine1, C G Hutchens, R D Strattan, W A Coberly.   

Abstract

A broad spectrum of techniques for electrocardiogram (ECG) data compression have been proposed during the last three decades. Such techniques have been vital in reducing the digital ECG data volume for storage and transmission. These techniques are essential to a wide variety of applications ranging from diagnostic to ambulatory ECG's. Due to the diverse procedures that have been employed, comparison of ECG compression methods is a major problem. Present evaluation methods preclude any direct comparison among existing ECG compression techniques. The main purpose of this paper is to address this issue and to establish a unified view of ECG compression techniques. 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 and entropy coding, AZTEC, Turning-point, CORTES, Fan and SAPA algorithms, peak-picking, and cycle-to-cycle compression methods. The transformation methods briefly presented, include: Fourier, Walsh, and K-L transforms. The theoretical basis behind the direct ECG data compression schemes are presented and classified into three categories: tolerance-comparison compression, differential pulse code modulation (DPCM), and entropy coding methods. The paper concludes with the presentation of a framework for evaluation and comparison of ECG compression schemes.

Mesh:

Year:  1990        PMID: 2186997     DOI: 10.1109/10.52340

Source DB:  PubMed          Journal:  IEEE Trans Biomed Eng        ISSN: 0018-9294            Impact factor:   4.538


  24 in total

1.  Adaptive vector quantisation for electrocardiogram signal compression using overlapped and linearly shifted codevectors.

Authors:  S G Miaou; J H Larn
Journal:  Med Biol Eng Comput       Date:  2000-09       Impact factor: 2.602

2.  Lossless compression of otoneurological eye movement signals.

Authors:  Timo Tossavainen; Martti Juhola
Journal:  J Clin Monit Comput       Date:  2002-12       Impact factor: 2.502

3.  Exploiting multi-lead electrocardiogram correlations using robust third-order tensor decomposition.

Authors:  Sibasankar Padhy; Samarendra Dandapat
Journal:  Healthc Technol Lett       Date:  2015-09-01

4.  Optimal wavelets for biomedical signal compression.

Authors:  Mogens Nielsen; Ernest Nlandu Kamavuako; Michael Midtgaard Andersen; Marie-Françoise Lucas; Dario Farina
Journal:  Med Biol Eng Comput       Date:  2006-06-13       Impact factor: 2.602

5.  Parametric modelling of ECG signal.

Authors:  S Mukhopadhyay; P Sircar
Journal:  Med Biol Eng Comput       Date:  1996-03       Impact factor: 2.602

6.  Optimisation algorithms for ECG data compression.

Authors:  D Haugland; J G Heber; J H Husøy
Journal:  Med Biol Eng Comput       Date:  1997-07       Impact factor: 2.602

7.  Development of a portable multipurpose recorder using a 24-hour ambulatory recorder: application to polysomnography.

Authors:  M Horikawa; H Harada
Journal:  Med Biol Eng Comput       Date:  1997-11       Impact factor: 2.602

8.  Wireless electrocardiogram transmission in ISM band: an approach towards telecardiology.

Authors:  R Gupta; M Mitra
Journal:  J Med Syst       Date:  2014-08-02       Impact factor: 4.460

9.  Quality Aware Compression of Electrocardiogram Using Principal Component Analysis.

Authors:  Rajarshi Gupta
Journal:  J Med Syst       Date:  2016-03-09       Impact factor: 4.460

10.  Wavelet-based Encoding Scheme for Controlling Size of Compressed ECG Segments in Telecardiology Systems.

Authors:  Asiya M Al-Busaidi; Lazhar Khriji; Farid Touati; Mohd Fadlee Rasid; Adel Ben Mnaouer
Journal:  J Med Syst       Date:  2017-09-12       Impact factor: 4.460

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