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http://dx.doi.org/10.6109/jkiice.2016.20.2.437

Premature Contraction Arrhythmia Classification through ECG Pattern Analysis and Template Threshold  

Cho, Ik-sung (Department of Information and Communication Engineering, Kyungwoon University)
Cho, Young-Chang (Department of Information and Communication Engineering, Kyungwoon University)
Kwon, Hyeog-soong (Department of IT Engineering, Pusan National University)
Publication Information
Journal of the Korea Institute of Information and Communication Engineering / v.20, no.2, 2016 , pp. 437-444 More about this Journal
Abstract
Most methods for detecting arrhythmia require pp interval, diversity of P wave morphology, but it is difficult to detect the p wave signal because of various noise types. Therefore it is necessary to use noise-free R wave. In this paper, we propose algorithm for premature contraction arrhythmia classification through ECG pattern analysis and template threshold. For this purpose, we detected R wave through the preprocessing method using morphological filter, subtractive operation method. Also, we developed algorithm to classify premature contraction wave pattern using weighted average, premature ventricular contraction(PVC) and atrial premature contraction(APC) through template threshold for R wave amplitude. The performance of R wave detection, PVC classification is evaluated by using 6 record of MIT-BIH arrhythmia database that included over 30 PVC and APC. The achieved scores indicate the average of 99.77% in R wave detection and the rate of 94.91%, 95.76% in PVC and APC classification.
Keywords
ECG pattern; template threshold; RR interval; R wave amplitude; PVC; APC;
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