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Wavelet optimization for applying continuous wavelet transform to maternal electrocardiogram component enhancing |
Qiong Yu(于琼)1, Qun Guan(管群)2, Ping Li(李萍)2, Tie-Bing Liu(刘铁兵)2, Jun-Feng Si(司峻峰)1, Ying Zhao(肇莹)1, Hong-Xing Liu(刘红星)1, Yuan-Qing Wang(王元庆)1 |
1. School of Electronic Science and Engineering, Nanjing University, Nanjing 210023, China;
2. Nanjing General Hospital of Nanjing Military Command, Nanjing 210002, China |
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Abstract In the procedure of non-invasive fetal electrocardiogram (ECG) extraction, high-quality maternal R wave peak detection demands enhancing the maternal ECG component firstly. Among all the enhancing algorithms, the one based on the continuous wavelet transform (CWT) is very important and its effectiveness depends on the optimization of the used wavelet. However, up to now, there is still no clear conclusion on the optimal wavelet (including type and scale) for CWT to enhance the maternal ECG component of an abdominal ECG signal. To solve this problem, in this paper, we select several common used types of wavelets to carry out our research on what the optimal wavelets are. We first establish big-enough training datasets with different sampling rates and make a maternal QRS template for each signal in the training datasets. Second, for each type of selected wavelets, we find its optimal scale corresponding to each QRS template in a training dataset based on the principle of maximal correlation. Then calculating the average of all optimized wavelet scales results in the mean optimal wavelet of this type for the dataset. We use two original abdominal ECG databases to train and test the optimized mean optimal wavelets. The test results show that, as a whole, the mean optimal wavelets obtained are superior to the wavelets used in other publications for applying CWT to maternal ECG component enhancing.
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Received: 06 July 2017
Revised: 03 August 2017
Accepted manuscript online:
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PACS:
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87.85.Ng
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(Biological signal processing)
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Fund: Project supported by the National Natural Science Foundation of China (Grant No. 61271079). |
Corresponding Authors:
Hong-Xing Liu
E-mail: njhxliu@nju.edu.cn
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Cite this article:
Qiong Yu(于琼), Qun Guan(管群), Ping Li(李萍), Tie-Bing Liu(刘铁兵), Jun-Feng Si(司峻峰), Ying Zhao(肇莹), Hong-Xing Liu(刘红星), Yuan-Qing Wang(王元庆) Wavelet optimization for applying continuous wavelet transform to maternal electrocardiogram component enhancing 2017 Chin. Phys. B 26 118702
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