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Automatic Diagnostic System for Long-Term ECG Data from Holter Monitor

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International Journal of Computer Applications
© 2012 by IJCA Journal
Volume 47 - Number 20
Year of Publication: 2012
Authors:
Ghousia Begum S.
Vipula Singh
10.5120/7303-0502

Ghousia Begum S. and Vipula Singh. Article: Automatic Diagnostic System for Long-Term ECG Data from Holter Monitor. International Journal of Computer Applications 47(20):16-21, June 2012. Full text available. BibTeX

@article{key:article,
	author = {Ghousia Begum S. and Vipula Singh},
	title = {Article: Automatic Diagnostic System for Long-Term ECG Data from Holter Monitor},
	journal = {International Journal of Computer Applications},
	year = {2012},
	volume = {47},
	number = {20},
	pages = {16-21},
	month = {June},
	note = {Full text available}
}

Abstract

An Electrocardiogram (ECG) gives significant information for the cardiologist to detect cardiac diseases. . Automation algorithm is essential to analyse long ECG data. In this paper, we have proposed fully automated, high efficiency, accurate and fast algorithm to detect abnormalities in ECG based on wavelet transform. The algorithm consists of pre-processing, feature extraction and diagnosis. Number of heart beats and Premature Ventricular Contraction (PVC), Premature Atrial Contractions (PACs), Supraventricular tachyarrhythmia and Bradycardia are diagnosed accurately and result matches with doctors opinion. The average sensitivity of algorithm is 99. 70%.

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