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http://dx.doi.org/10.9717/kmms.2016.19.5.818

R-Peak Detection Algorithm in ECG Signal Based on Multi-Scaled Primitive Signal  

Cha, Won-Jun (Dept. of Electronic Eng., Kyungpook National University)
Ryu, Gang-Soo (Dept. of Information & Communications Eng., Graduate School, Gu-mi University)
Lee, Jong-Hak (Dept. of Information Technology Eng., Graduate School, Catholic University of Daegu)
Cho, Woong-Ho (Dept. of Electronic & Information., Graduate School, Daegu-Technical University)
Jung, YouSoo (Dept. of Electronic Eng., Kyungpook National University)
Park, Kil-Houm (Dept. of Electronic Eng., Kyungpook National University)
Publication Information
Journal of Korea Multimedia Society / v.19, no.5, 2016 , pp. 818-825 More about this Journal
Abstract
The existing R-peak detection research suggests improving the distortion of the signal such as baseline variations in ECG signals by using preprocessing techniques such as a bandpass filtering. However, preprocessing can introduce another distortion, as it can generate a false detection in the R-wave detection. In this paper, we propose an R-peak detection algorithm in ECG signal, based on primitive signal in order to detect reliably an R-peak in baseline variation. First, the proposed algorithm decides the primitive signal to represent the QRS complex in ECG signal, and by scaling the time axis and voltage axis, extracts multiple primitive signals. Second, the algorithm detects the candidates of the R-peak using the value of the voltage. Third, the algorithm measures the similarity between multiple primitive signals and the R-peak candidates. Finally, the algorithm detects the R-peak using the mean and the standard deviation of similarity. Throughout the experiment, we confirmed that the algorithm detected reliably a QRS group similar to multiple primitive signals. Specifically, the algorithm can achieve an R-peak detection rate greater than an average rate of 99.9%, based on eight records of MIT-BIH ADB used in this experiment.
Keywords
ECG; Primitive Signal; R-peak Detection;
Citations & Related Records
Times Cited By KSCI : 3  (Citation Analysis)
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