ElectroCardioGram R-wave Recognition Algorithm Based on Ensemble Empirical Mode Decomposition and Signal Structure Analysis

Jinzhao LIN; Bilu LI; Guoquan LI; Zhengwen HUANG; Yu PANG

doi:10.11999/JEIT200915

Volume 43 Issue 8

Aug. 2021

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Article Navigation > Journal of Electronics & Information Technology > 2021 > 43(8): 2352-2360

Jinzhao LIN, Bilu LI, Guoquan LI, Zhengwen HUANG, Yu PANG. ElectroCardioGram R-wave Recognition Algorithm Based on Ensemble Empirical Mode Decomposition and Signal Structure Analysis[J]. Journal of Electronics & Information Technology, 2021, 43(8): 2352-2360. doi: 10.11999/JEIT200915

Citation:

Jinzhao LIN, Bilu LI, Guoquan LI, Zhengwen HUANG, Yu PANG. ElectroCardioGram R-wave Recognition Algorithm Based on Ensemble Empirical Mode Decomposition and Signal Structure Analysis[J]. Journal of Electronics & Information Technology, 2021, 43(8): 2352-2360. doi: 10.11999/JEIT200915

Citation:

Jinzhao LIN, Bilu LI, Guoquan LI, Zhengwen HUANG, Yu PANG. ElectroCardioGram R-wave Recognition Algorithm Based on Ensemble Empirical Mode Decomposition and Signal Structure Analysis[J]. Journal of Electronics & Information Technology, 2021, 43(8): 2352-2360. doi: 10.11999/JEIT200915

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ElectroCardioGram R-wave Recognition Algorithm Based on Ensemble Empirical Mode Decomposition and Signal Structure Analysis

doi: 10.11999/JEIT200915 cstr: 32379.14.JEIT200915

Jinzhao LIN^{1, 3},
Bilu LI^{1, 3},
Guoquan LI^{1, 3
,
,},
Zhengwen HUANG²,
Yu PANG³

1.
School of Communication and Information Technology, Chongqing University of Posts and Telecommunications, Chongqing 400065, China
2.
Department of Electronic and Computer Engineering, Brunel University London, London UB8-3PH, UK
3.
Key Laboratory of Photoelectric Information Sensing and Transmission Technology, Chongqing 400065, China

Funds: The National Key Research and Development Program (2019yfc1511300), The National Natural Science Foundation of China (61971079)，The General Program of Chongqing Natural Science Foundation (cstc2019jcyj-msxmx0666), The Sichuan Innovation Cooperation Program (2020YFQ0025), The Chongqing Creative Group Program (cstc2020jcyj-cxttX0002), The Science and Technology Research Program of Chongqing Education Committee (KJZD-K20200604)

Received Date: 2020-10-26
Rev Recd Date: 2021-07-21

Available Online: 2021-07-22

Publish Date: 2021-08-10

Abstract

Abstract

In view of the problem that the preprocessing process of most R-wave recognition algorithms affects the accuracy of recognition and spends more time, an algorithm based on Ensemble Empirical Mode Decomposition (EEMD) and signal structure analysis is proposed to recognize R-wave of ElectroCardioGram (ECG) signals with noise directly. Firstly, the ECG signal with noise is decomposed into a series of intrinsic mode components by EEMD. After that, the intrinsic components are analyzed as independent components to extract the most obvious component of R waves. Finally, the structure of the component is analyzed to realize the accurate positioning of R wave. The simulation results show that the proposed algorithm has better performance in R-wave recognition of noisy ECG signals and demonstrates obvious advantages especially for abnormal ECG signals.
- ElectroCardioGraphy (ECG),
- R-wave recognition,
- Ensemble Empirical Mode Decomposition (EEMD),
- Signal structure analysis

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References(28)

References

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