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Volume & Issue no: Volume 4, Issue 1, January - February 2015

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Title:
12 Lead ECG Data Compression Using Principal Component Analysis
Author Name:
RITURAJ JAIN
Abstract:
Abstract It is required that signals like temperature, arterial pressure or electrocardiogram (ECG) waveforms etc. generated by medical checkup and diagnosis must be supervised constantly. The electrocardiography is one of the basic investigative methods in cardiology through which all necessary information about electrical activity of the heart can be collect. Recorded ECG signal which are in huge in size not only used for diagnosis purpose but it is to be stored for future reference. So compression of huge amount of ECG signal data is required to keep these records for observing a patient. This paper presents 12 Lead ECG signal data compression using Principal Component Analysis. The methods are applied to ECG database file 105 of the MIT-BIH Arrhythmia Data base. The results are efficient for data compression of ECG signals which are analyzed on the basis of compression ratio (CR). Key Words:- Compression, Compression Ratio (CR), ECG Signal, Percentage Root Mean Square Error (PRD), Principal Component Analysis.
Cite this article:
RITURAJ JAIN , " 12 Lead ECG Data Compression Using Principal Component Analysis" , International Journal of Emerging Trends & Technology in Computer Science (IJETTCS) , Volume 4, Issue 1, January - February 2015 , pp. 034-039 , ISSN 2278-6856.
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International Journal of Emerging Trends & Technology in Computer Science (IJETTCS)
ISSN 2278-6856
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