期刊
CIRCUITS SYSTEMS AND SIGNAL PROCESSING
卷 33, 期 4, 页码 1261-1276出版社
SPRINGER BIRKHAUSER
DOI: 10.1007/s00034-013-9691-3
关键词
ECG signal; EMD; Denoising; R-peak detection
资金
- National Natural Science Foundation of China [61177078, 61307094, 31271871]
- Specialized Research Fund for the Doctoral Program of Higher Education of China [20101201120001]
- Tianjin Research Program of Application Foundation and Advanced Technology [13JCYBJC16800]
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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