Simultaneous 12-lead QRS detection by K-means clustering algorithm

An electrocardiogram (ECG) is a recording of the electrical activity of the heart. Analysis of ECG data can give important information about the health and condition of the heart and can help physicians to diagnose cardiac arrhythmias, acute myocardial infarctions, conduction abnormalities, and many...

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Bibliographic Details
Published in:International Conference on Recent Advances and Innovations in Engineering (ICRAIE-2014) pp. 1 - 4
Main Authors: Nagal, Devendra, Sharma, Swati
Format: Conference Proceeding
Language:English
Published: IEEE 01.05.2014
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Summary:An electrocardiogram (ECG) is a recording of the electrical activity of the heart. Analysis of ECG data can give important information about the health and condition of the heart and can help physicians to diagnose cardiac arrhythmias, acute myocardial infarctions, conduction abnormalities, and many other heart diseases. ECGs can also be used to determine heart rate by calculating the time between successive QRS complexes. This paper presents an application of K-means algorithm applied on 25 subjects of CSE data set-3 for the detection of QRS complexes in the simultaneously recorded 12 lead ECG. The detection rate of 99.89% is achieved.
DOI:10.1109/ICRAIE.2014.6909244