Computer Engineering and Applications ›› 2018, Vol. 54 ›› Issue (15): 29-33.DOI: 10.3778/j.issn.1002-8331.1805-0352

Previous Articles     Next Articles

ECG denoising method based on adaptive wavelet threshold selection

WANG Lei, SUN Wei, CHEN Yibo, LI Peng, ZAHO Lingxiao   

  1. Suzhou Institute of Biomedical Engineering and Technology, Chinese Academy of Sciences, Suzhou, Jiangsu 215163, China
  • Online:2018-08-01 Published:2018-07-26


王  磊,孙  玮,陈奕博,李  鹏,赵凌霄   

  1. 中国科学院 苏州生物医学工程技术研究所,江苏 苏州 215163

Abstract: Multiresolution has strong dependence on the choice of wavelet threshold and wavelet function design, and the difference in the effect of noise reduction for different individuals’ ECG signals is much obviously. In this work, an adaptive wavelet threshold selection method based on heuristic threshold optimization is proposed, in which the wavelet decomposition layer number and level influence factor are incorporated. More reasonable signal decomposition and noise reduction are realized by dynamically adjusting the threshold calculation function of each layer for wavelet coefficients. The experimental results show that the proposed algorithm achieves better performance for reducing the noise of ECG to meet the needs of clinical application.

Key words: electrocardiogram, denoising, wavelet transform, threshold selection, signal-to-noise ratio

摘要: 多尺度分析对于小波阈值的选取以及小波函数的设计依赖性较强,针对不同个体心电信号的降噪效果差异性较大。提出一种自适应的小波阈值计算和选取方法,该方法在启发式阈值优化方法基础上融入了小波分解层数和层级影响因子,通过动态调整每一层小波系数的阈值计算函数实现更加合理的信号分解与降噪处理。实验结果表明所提出算法在心电信号降噪效果方面获得了较好的表现,能够满足临床应用需求。

关键词: 心电信号, 降噪, 小波变换, 阈值选取, 信噪比