Denoising and R-peak detection of electrocardiogram signal based on EMD and improved approximate envelope

RIS ID

89209

Publication Details

Li, H., Wang, X., Chen, L. & Li, E. (2014). Denoising and R-peak detection of electrocardiogram signal based on EMD and improved approximate envelope. Circuits, Systems, and Signal Processing, 33 (4), 1261-1276.

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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Link to publisher version (DOI)

http://dx.doi.org/10.1007/s00034-013-9691-3