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[改进小波阈值在心电图信号去噪中的应用]

[Application of Improved Wavelet Threshold in Denoising of ECG Signals].

作者信息

Tan Xue, Ye Jilun, Zhang Xu, Li Chenyang, Zhou Jingjing, Dou Kejian

机构信息

School of Biomedical Engineering Department, Shenzhen University, Shenzhen, 518060.

Shenzhen Key Lab for Biomedical Engineering, Shenzhen, 518060.

出版信息

Zhongguo Yi Liao Qi Xie Za Zhi. 2021 Feb 8;45(1):1-5. doi: 10.3969/j.issn.1671-7104.2021.01.001.

Abstract

The ECG signal is susceptible to interference from the external environment during the acquisition process, affecting the analysis and processing of the ECG signal. After the traditional soft-hard threshold function is processed, there is a defect that the signal quality is not high and the continuity at the threshold is poor. An improved threshold function wavelet denoising is proposed, which has better regulation and continuity, and effectively solves the shortcomings of traditional soft and hard threshold functions. The Matlab simulation is carried out through a large amount of data, and various processing methods are compared. The results show that the improved threshold function can improve the denoising effect and is superior to the traditional soft and hard threshold denoising.

摘要

心电信号在采集过程中易受外部环境干扰,影响心电信号的分析与处理。传统软硬阈值函数处理后存在信号质量不高、阈值处连续性差的缺陷。提出了一种改进的阈值函数小波去噪方法,其具有更好的调节性和连续性,有效解决了传统软硬阈值函数的不足。通过大量数据进行Matlab仿真,并比较了各种处理方法。结果表明,改进后的阈值函数能提高去噪效果,优于传统软硬阈值去噪。

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