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Detection of QRS Feature Based on Phase Transition Tracking for Premature Ventricular Contraction Classification
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 Title & Authors
Detection of QRS Feature Based on Phase Transition Tracking for Premature Ventricular Contraction Classification
Cho, Ik-sung; Yoon, Jeong-oh; Kwon, Hyeog-soong;
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In general, QRS duration represent a distance of Q start and S end point. However, since criteria of QRS duration are vague and Q, S point is not detected accurately, arrhythmia classification performance can be reduced. In this paper, we propose extraction of Q, S start and end point RS feature based on phase transition tracking method after we detected R wave that is large peak of electrocardiogram(ECG) signal. For this purpose, we detected R wave, from noise-free ECG signal through the preprocessing method. Also, we classified QRS pattern through differentiation value of ECG signal and extracted Q, S start and end point by tracking direction and count of phase based on R wave. The performance of R wave detection is evaluated by using 48 record of MIT-BIH arrhythmia database. The achieved scores indicate the average detection rate of 99.60%. PVC classification is evaluated by using 9 record of MIT-BIH arrhythmia database that included over 30 premature ventricular contraction(PVC). The achieved scores indicate the average detection rate of 94.12% in PVC.
phase transition tracking;QRS pattern;QRS duration;Q, S start and end point;PVC;
 Cited by
헬스케어 환경에서 복잡도를 고려한 R파 검출과 이진 부호화 기반의 부정맥 분류방법,조익성;윤정오;

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적응형 문턱치와 QRS피크 변화에 따른 P파 검출 알고리즘,조익성;김주만;이완직;권혁숭;

한국정보통신학회논문지, 2016. vol.20. 8, pp.1587-1595 crossref(new window)
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