Data compression techniques for electrocardiograms

Shridhar, M.; Mohankrishnan, N.

doi:10.1109/ceej.1984.6590967

Cited by 6 publications

(1 citation statement)

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“…Many data compression techniques for ECG data have been presented in literature [5], [6], [7]. Roughly, they can be classified into two categories: (i).…”

Section: Previous Approachesmentioning

confidence: 99%

A predictive adaptive approach to generic ECG data compression

Brito

Henriques

Gil

et al.

IEEE International Workshop on Intelligent Signal Processing, 2005.

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In the modern hospital, the efficient storage of electronically recorded biomedical signals as well as its transmission over communication networks is becoming more and more important. Although digital storage media is currently almost inexpensive and computational power has exponentially increased in last years, effective electrocardiogram (ECG) compression techniques are still very attractive. In fact, several millions of electrocardiograms are recorded annually and the transfer of electrocardiogram records over communication networks for remote analysis is now done more than ever. Besides the increased storage capacity for archival purposes, ECG compression allows real-time transmission over communication networks, economic off-line transmission to remote interpretation sites and enables efficient ECG rhythm analysis algorithms. In this paper, an adaptive approach to ECG compression is proposed, which provides comparable results with various types of ECG signal, namely normal sinus rhythm, ventricular tachycardia and ventricular fibrillation. Most proposals in the literature approach the problem of ECG compression without considering the possibility of such pathologies and, consequently, their performance deteriorate in cases where such signals are present. Experimental results of the proposed algorithm are promising, although compression ratios are still not yet as good as they can get.

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“…Many data compression techniques for ECG data have been presented in literature [5], [6], [7]. Roughly, they can be classified into two categories: (i).…”

Section: Previous Approachesmentioning

confidence: 99%

A predictive adaptive approach to generic ECG data compression

Brito

Henriques

Gil

et al.

IEEE International Workshop on Intelligent Signal Processing, 2005.

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Using off-the-shelf lossy compression for wireless home sleep staging

Lan

Chang

Kuo

et al. 2015

Journal of Neuroscience Methods

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ECG data compression techniques-a unified approach

Jalaleddine

Hutchens

Strattan

et al. 1990

IEEE Trans. Biomed. Eng.

611

224

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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.

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Data compression techniques for electrocardiograms

Cited by 6 publications

References 0 publications

A predictive adaptive approach to generic ECG data compression

A predictive adaptive approach to generic ECG data compression

Using off-the-shelf lossy compression for wireless home sleep staging

ECG data compression techniques-a unified approach

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