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Denoising and R-Peak Detection of Electrocardiogram Signal Based on EMD and Improved Approximate Envelope

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Abstract

The electrocardiogram (ECG ) signal is prone to various high and low frequency noises, including baseline wandering and power-line interference, which become the source of errors in QRS and in other extracted features. This paper presents a new ECG signal-processing approach based on empirical mode decomposition (EMD) and an improved approximate envelope method. To reduce the number of the initial intrinsic mode functions (IMFs), a Butterworth lowpass filter is used to eliminate high frequency noises before the EMD. To correct baseline wandering and to eliminate low frequency noises, the two last-order IMFs are abandoned. An improved approximate envelope is proposed and applied after the Hilbert transform to enhance the energy of QRS complexes and to suppress unwanted P/T waves and noises. Then, an algorithm based on the slope threshold is used for R-peak detection. The proposed denoising and R-peak detection algorithm are validated using the MIT-BIH Arrhythmia Database. The simulation results show that the proposed method can effectively eliminate the Gaussian noise, baseline wander, and power-line interference added to the ECG signal. The method can also function reliably even under poor signal quality and with long P and T peaks. The QRS detector has an average sensitivity of Se=99.94 % and a positive predictivity of +P=99.87 % over the first lead of the MIT-BIH Arrhythmia Database.

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Acknowledgements

his paper is supported by the National Natural Science Foundation of China (Nos. 61177078, 61307094, 31271871), the Specialized Research Fund for the Doctoral Program of Higher Education of China (No. 20101201120001), and Tianjin Research Program of Application Foundation and Advanced Technology (No. 13JCYBJC16800).

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Authors and Affiliations

  1. School of Electronics and Information Engineering, Tianjin Polytechnic University, No. 399 Binshuixi Road, Xiqing District, Tianjin, 300387, China

    Hongqiang Li, Xiaofei Wang & Lei Chen

  2. School of Physics, Faculty of Engineering, University of Wollongong, Wollongong, NSW 2522, Australia

    Enbang Li

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  1. Hongqiang Li
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  2. Xiaofei Wang
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Correspondence to Hongqiang Li.

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Li, H., Wang, X., Chen, L. et al. Denoising and R-Peak Detection of Electrocardiogram Signal Based on EMD and Improved Approximate Envelope. Circuits Syst Signal Process 33, 1261–1276 (2014). https://doi.org/10.1007/s00034-013-9691-3

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  • DOI: https://doi.org/10.1007/s00034-013-9691-3

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