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A Survey on different Compression Techniques for ECG Data Reduction

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International Journal of Computer Applications
Foundation of Computer Science (FCS), NY, USA
Year of Publication: 2017
Authors:
Sakshi, Nirvair Neeru
10.5120/ijca2017914834

Sakshi and Nirvair Neeru. A Survey on different Compression Techniques for ECG Data Reduction. International Journal of Computer Applications 170(4):34-39, July 2017. BibTeX

@article{10.5120/ijca2017914834,
	author = {Sakshi and Nirvair Neeru},
	title = {A Survey on different Compression Techniques for ECG Data Reduction},
	journal = {International Journal of Computer Applications},
	issue_date = {July 2017},
	volume = {170},
	number = {4},
	month = {Jul},
	year = {2017},
	issn = {0975-8887},
	pages = {34-39},
	numpages = {6},
	url = {http://www.ijcaonline.org/archives/volume170/number4/28062-2017914834},
	doi = {10.5120/ijca2017914834},
	publisher = {Foundation of Computer Science (FCS), NY, USA},
	address = {New York, USA}
}

Abstract

Electrocardiogram (ECG) is the technique that is used to record the electrical signal of the heart over a time interval by using the electrodes, positioned on a patient's body. The signals collected from the body needs to be processed and compressed before directing to monitoring center. Electrocardiogram (ECG) data compressions minimize the necessities of storage to generate a more proficient tele-cardiology system for the cardiac exploration and diagnosis. This paper focus on the evaluation of several compression schemes for ECG data compression and also provides the comparison of the various ECG compression techniques such as Turning Point, Delta Coding, AZTEC, CORTES, DCT etc. in terms of different performance metrics like Compression Ratio (CR), Percent Mean Square Difference (PRD) and Quality Score (QS).

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Keywords

ECG signal, Compressive Sensing, Time domain techniques, Wavelet based techniques.