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A Survey on different Compression Techniques for ECG Data Reduction

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

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

	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 = {},
	doi = {10.5120/ijca2017914834},
	publisher = {Foundation of Computer Science (FCS), NY, USA},
	address = {New York, USA}


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