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Open AccessArticle

A Novel Wavelet-Based Algorithm for Detection of QRS Complex

Department of Electrical Engineering, National Chin-Yi University of Technology, Taichung 411, Taiwan
Heart Center, Cheng Hsin General Hospital, Taipei 112, Taiwan
Faculty of Medicine, School of Medicine, National Yang Ming University, Taipei 112, Taiwan
Author to whom correspondence should be addressed.
Appl. Sci. 2019, 9(10), 2142;
Received: 22 April 2019 / Revised: 16 May 2019 / Accepted: 23 May 2019 / Published: 26 May 2019
(This article belongs to the Special Issue Applied Sciences Based on and Related to Computer and Control)
Accurate QRS detection is an important first step for almost all automatic electrocardiogram (ECG) analyzing systems. However, QRS detection is difficult, not only because of the wide variety of ECG waveforms but also because of the interferences caused by various types of noise. This study proposes an improved QRS complex detection algorithm based on a four-level biorthogonal spline wavelet transform. A noise evaluation method is proposed to quantify the noise amount and to select a lower-noise wavelet detail signal instead of removing high-frequency components in the preprocessing stage. The QRS peaks can be detected by the extremum pairs in the selected wavelet detail signal and the proposed decision rules. The results show the high accuracy of the proposed algorithm, which achieves a 0.25% detection error rate, 99.84% sensitivity, and 99.92% positive prediction value, evaluated using the MIT-BIT arrhythmia database. The proposed algorithm improves the accuracy of QRS detection in comparison with several wavelet-based and non-wavelet-based approaches. View Full-Text
Keywords: electrocardiogram (ECG); QRS detection; noise evaluation; biorthogonal wavelet transform electrocardiogram (ECG); QRS detection; noise evaluation; biorthogonal wavelet transform
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Lin, C.-C.; Chang, H.-Y.; Huang, Y.-H.; Yeh, C.-Y. A Novel Wavelet-Based Algorithm for Detection of QRS Complex. Appl. Sci. 2019, 9, 2142.

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