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R-Peak Detection Algorithm in ECG Signal Based on Multi-Scaled Primitive Signal
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 Title & Authors
R-Peak Detection Algorithm in ECG Signal Based on Multi-Scaled Primitive Signal
Cha, Won-Jun; Ryu, Gang-Soo; Lee, Jong-Hak; Cho, Woong-Ho; Jung, YouSoo; Park, Kil-Houm;
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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.
ECG;Primitive Signal;R-peak Detection;
 Cited by
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