Please wait a minute...
Chin. Phys. B, 2017, Vol. 26(11): 118702    DOI: 10.1088/1674-1056/26/11/118702
INTERDISCIPLINARY PHYSICS AND RELATED AREAS OF SCIENCE AND TECHNOLOGY Prev   Next  

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
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.

Keywords:  maternal ECG component enhancing      continuous wavelet transform (CWT)      wavelet optimization      correlation  
Received:  06 July 2017      Revised:  03 August 2017      Published:  05 November 2017
PACS:  87.85.Ng (Biological signal processing)  
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

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

[1] Kuzilek J and Lhotska L 2013 Computing in Cardiology Conference IEEE 40 177
[2] Perlman O, Katz A and Zigel Y 2013 Computing in Cardiology Conference IEEE 40 169
[3] Maria C D, Duan W, Bojarnejad M, et al. 2013 Computing in Cardiology Conference IEEE 40 305
[4] Andreotti F, Riedl M, Himmelsbach T, Wedekind D, Wessel N, Stepan H, Schmieder C, Jank A, Malberg H and Zaunseder S 2014 Physiol. Meas. 35 1551
[5] Behar J, Oster J and Clifford G D 2014 Physiol. Meas. 35 1569
[6] Varanini M, Tartarisco G, Billeci L, Macerata A, Pioggia G and Balocchi R 2014 Physiol. Meas. 35 1607
[7] Varaninia M, Tartariscob G, Balocchia R, Maceratac A, Pioggiab G and Billeci L 2017 Comput. Biol. Med. 85 125
[8] Gupta P, Sharma K K and Joshi S D 2016 Computers in Biology & Medicine 68 121
[9] Pan J and Tompkins W J 1985 IEEE Trans. Biomed. Eng. 32 230
[10] Nygards M and Sommo L 1983 Med. Biol. Eng. Comput. 21 538
[11] Krasteva V and Jekova I 2007 Ann. Biomed. Eng. 35 2065
[12] Qi H B, Liu X F and Pan C 2010 IEEE ICICTA 1 22
[13] Karvounis E C, Papaloukas C, Fotiadis D I and Michalis L K 2004 Computers in Cardiology IEEE 31 737
[14] Legarreta I R, Addison P S, Grubb N and Clegg G R 2003 Computers in Cardiology IEEE 30 565
[15] Banerjee S, Gupta R and Mitra M 2012 Measurement 45 474
[16] Behbahani S and Dabanloo N J 2012 Computing in Cardiology IEEE 38 805
[17] Mehta P and M Kumari 2012 Int. Journal of applied Engineering Research 7 11
[18] Abdelliche F and Charef A 2009 International Conference on Electrical and Electronics Engineering IEEE Ⅱ 267
[19] Fard P J, Moradi M H and Tajvidi M R 2008 International Journal of Cardiology 124 250
[20] Wu S, Shen Y, Zhou Z, Lin L, Zeng Y and Gao X 2013 Comput. Biol. Med. 43 1622
[21] Acharyya A, Maharatna K, Al-Hashimi B M and Mondal S 2010 Conf. Proc. IEEE Eng. Med. Biol. Soc. 10 1142
[22] Daubechies I 1990 IEEE Transactions on Information Theory 36 961
[23] Mallat S G 1989 IEEE Transactions on Pattern Analysis & Machine Intelligence 11 674
[24] Zhang J M, Huang X L, Guan Q, Liu T B, Li P, Zhao Y and Liu H X 2015 Chin. Phys. B 24 442
[25] Clifford G D, Silva I, Behar J and Moody G B 2014 Physiol Meas. 35 1521
[26] Nagendra H, Mukherjee S and Kumar V 2011 International Journal of Engineering Science & Technology 3
[1] Intercalation of van der Waals layered materials: A route towards engineering of electron correlation
Jingjing Niu(牛晶晶), Wenjie Zhang(章文杰), Zhilin Li(李治林), Sixian Yang(杨嗣贤), Dayu Yan(闫大禹), Shulin Chen(陈树林), Zhepeng Zhang(张哲朋), Yanfeng Zhang(张艳锋), Xinguo Ren(任新国), Peng Gao(高鹏), Youguo Shi(石友国), Dapeng Yu(俞大鹏), Xiaosong Wu(吴孝松). Chin. Phys. B, 2020, 29(9): 097104.
[2] Lattice deformation in epitaxial Fe3O4 films on MgO substrates studied by polarized Raman spectroscopy
Yang Yang(杨洋), Qiang Zhang(张强), Wenbo Mi(米文博), Xixiang Zhang(张西祥). Chin. Phys. B, 2020, 29(8): 083302.
[3] Non-Gaussian statistics of partially coherent light inatmospheric turbulence
Hao Ni(倪昊), Chunhao Liang(梁春豪), Fei Wang(王飞), Yahong Chen(陈亚红), Sergey A. Ponomarenko, Yangjian Cai(蔡阳健). Chin. Phys. B, 2020, 29(6): 064203.
[4] Quantum coherence and correlation dynamics of two-qubit system in spin bath environment
Hao Yang(杨豪), Li-Guo Qin(秦立国), Li-Jun Tian(田立君), Hong-Yang Ma(马鸿洋). Chin. Phys. B, 2020, 29(4): 040303.
[5] Effects of electron correlation and the Breit interaction on one- and two-electron one-photon transitions in double K hole states of He-like ions (10≤Z≤47)
Xiaobin Ding(丁晓彬), Cunqiang Wu(吴存强), Mingxin Cao(曹铭欣), Denghong Zhang(张登红), Mingwu Zhang(张明武), Yingli Xue(薛迎利), Deyang Yu(于得洋), Chenzhong Dong(董晨钟). Chin. Phys. B, 2020, 29(3): 033101.
[6] Quantifying non-classical correlations under thermal effects in a double cavity optomechanical system
Mohamed Amazioug, Larbi Jebli, Mostafa Nassik, Nabil Habiballah. Chin. Phys. B, 2020, 29(2): 020304.
[7] Effect of system-reservoir correlations on temperature estimation
Wen-Li Zhu(朱雯丽), Wei Wu(吴威), Hong-Gang Luo(罗洪刚). Chin. Phys. B, 2020, 29(2): 020501.
[8] A review of experimental advances in twisted graphene moirè superlattice
Yanbang Chu(褚衍邦), Le Liu(刘乐), Yalong Yuan(袁亚龙), Cheng Shen(沈成), Rong Yang(杨蓉), Dongxia Shi(时东霞), Wei Yang(杨威), and Guangyu Zhang(张广宇). Chin. Phys. B, 2020, 29(12): 128104.
[9] Systematic error suppression scheme of the weak equivalence principle test by dual atom interferometers in space based on spectral correlation
Jian-Gong Hu(胡建功), Xi Chen(陈曦), Li-Yong Wang(王立勇), Qing-Hong Liao(廖庆洪), and Qing-Nian Wang(汪庆年)$. Chin. Phys. B, 2020, 29(11): 110305.
[10] Effect of degree correlation on edge controllability of real networks
Shu-Lin Liu(刘树林) and Shao-Peng Pang(庞少鹏)†. Chin. Phys. B, 2020, 29(10): 100202.
[11] Geometrical quantum discord and negativity of two separable and mixed qubits
Tang-Kun Liu(刘堂昆), Fei Liu(刘飞), Chuan-Jia Shan(单传家), Ji-Bing Liu(刘继兵). Chin. Phys. B, 2019, 28(9): 090304.
[12] Lamb waves topological imaging combining with Green's function retrieval theory to detect near filed defects in isotropic plates
Hui Zhang(张辉), Hai-Yan Zhang(张海燕), Meng-Yun Xu(徐梦云), Guo-Peng Fan(范国鹏), Wen-Fa Zhu(朱文发), Xiao-Dong Chai(柴晓冬). Chin. Phys. B, 2019, 28(7): 074301.
[13] Low-lying electronic states of aluminum monoiodide
Xiang Yuan(袁翔), Shuang Yin(阴爽), Yi Lian(连艺), Pei-Yuan Yan(颜培源), Hai-Feng Xu(徐海峰), Bing Yan(闫冰). Chin. Phys. B, 2019, 28(4): 043101.
[14] Relations between tangle and I concurrence for even n-qubit states
Xin-Wei Zha(查新未), Ning Miao(苗宁), Ke Li(李轲). Chin. Phys. B, 2019, 28(12): 120304.
[15] Theoretical analyses of stock correlations affected by subprime crisis and total assets: Network properties and corresponding physical mechanisms
Shi-Zhao Zhu(朱世钊), Yu-Qing Wang(王玉青), Bing-Hong Wang(汪秉宏). Chin. Phys. B, 2019, 28(10): 108901.
No Suggested Reading articles found!