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| Research on an Improved Algorithm for Wavelet Denoising of ECG |
| Zheng Minmin1*, Gao Xiaorong2, Xie Haihe1 |
1 (School of Mechanical and Electrical Engineering, Putian University, Putian 351100, Fujian, China)
2(Biomedical Engineering Department, Tsinghua University, Beijing 100084, China) |
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[1] 江依法,周青,叶含笑,等.基于扩散模型的心电信号基线漂移去除法[J].中国生物医学工程学报,2013,32(5):631-635.
[2] 郭新蕾,杨开林,郭永鑫.基于阈值自学习小波算法的压力信号去噪方法[J].数据采集与处理,2008,23(3):322-326.
[3] 苏丽,赵国良,张仁彦.基于改进小波阈值法的平移小波不变心电信号去噪[J].哈尔滨工程大学学报,2006,27(6):839-843.
[4] Zhao Zhidong,Chen Yuquan.Research of threshold value selections and applications for generalized threshold functions[J].Chinese Journal of Sensors and Actuators,2007,20(3):601-605.
[5] Blanco-Velasco M, Weng B, Barner KE.ECG signal denoising and baseline wander correction based on the empirical mode decomposition [J].Computers in Biology and Medicine, 2008,38(1):1-13.
[6] Poornachandra S. Wavelet-based denoising using subband dependent threshold for ECG signals[J].Digital Signal Processing, 2008,18(1):49-55.
[7] Yan Jingyu, Lu Yan, Liu Jia. Self-adaptive model-based ECG denoising using features extracted by mean shift algorithm[J].Biomedical Signal Processing and Control, 2010,5(2):103-113.
[8] Mustaffa I, Trenado C, Schwerdtfeger K, et al. Denoising of single-trial matrix representations using 2D nonlinear diffusion filtering[J].Journal of Neuroscience Methods, 2010,185(2):284-292.
[9] Pal S, Mitra M. Empirical mode decomposition based ECG enhancement and QRS dectection[J].Computers in Biology and Medicine, 2012,42(1):83-92.
[10] 张翠娜.心电信号去噪算法的研究[D].桂林: 桂林理工大学, 2012.
[11] 杨建国.小波分析及其工程应用[M].北京:机械工业出版社,2005.
[12] 刘卫东,刘尚合,胡小锋,等.小波阈值去噪函数的改进方法分析[J].高电压技术,2007, 33(10):59-63. |
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Wang Zhiqiong, Wu Chengyang, Xin Junchang, Zhao Yue, Li Xiang. Algorithm of Left Bundle Branch Block Diagnosis Based on ELM[J]. Chinese Journal of Biomedical Engineering, 2017, 36(3): 293-299. |
| [2] |
Wang Ruirong, Yu Xiaoqing, Wang Min, Ye Yang. Implementation of the Algorithm for Premature Ventricular Contraction Discrimination Based on Extreme Learning Machine[J]. Chinese Journal of Biomedical Engineering, 2017, 36(2): 158-164. |
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