电信科学 ›› 2016, Vol. 32 ›› Issue (12): 93-98.doi: 10.11959/j.issn.1000-0801.2016321

• 研究与开发 • 上一篇    下一篇

基于双树复小波变换和形态学的脉搏信号去噪

李丹,王慧倩,柏桐,林金朝,庞宇,姜小明,蒋宇皓   

  1. 重庆邮电大学光电信息感测与传输技术重庆市重点实验室,重庆 400065
  • 出版日期:2016-12-20 发布日期:2017-04-26
  • 基金资助:
    国家科技支撑计划课题资助项目;国家自然科学基金资助项目;国家自然科学基金资助项目;国家自然科学基金资助项目;重庆市高校创新团队(智慧医疗与系统核心技术)建设计划资助项目;重庆邮电大学文峰创新创业基金资助项目

De-noising method of pulse signal based on double-tree complex wavelet transform and morphological filtering

Dan LI,Huiqian WANG,Tong BAI,Jinzhao LIN,Yu PANG,Xiaoming JIANG,Yuhao JIANG   

  1. Chongqing Key Laboratory of Photoelectronic Information Sensing and Transmitting Technology, Chongqing University of Posts and Telecommunications, Chongqing 400065, China
  • Online:2016-12-20 Published:2017-04-26
  • Supported by:
    The National Science & Technology Pillar Program;Chonqing National Natural Science Foundation of China;Chonqing National Natural Science Foundation of China;Chonqing National Natural Science Foundation of China;University Innovation Team Construction Plan of Chongqing of Smart Medical System and Core Technology;Wenfeng Talented Plan of CQUPT

摘要:

常见的医学信号(如脉搏信号)包含大量的噪声,具有强烈的非线性和非平稳性。针对传统的小波变换去噪方法的缺陷,提出了一种基于双树复小波变换和形态学的去噪算法,具有结构简单、计算复杂度低等优点,有效地克服了离散小波变换的平移敏感性和频率混淆。实验表明,该算法可以有效地去除脉搏信号中工频干扰及肌电干扰等高频噪声,其信噪比及均方差等定量指标均明显优于传统的阈值去噪算法,能得到较干净的脉搏信号波形。

关键词: 信号去噪, 双树复小波变换, 形态学滤波, 脉搏信号

Abstract:

Common medical signals such as pulse signals, contain a variety of noises, have strong nonlinear and non-stationary. According to the previous wavelet transformation method, a pulse signals de-noising algorithm based on dual-tree complex wavelet transform(DTCWT)was proposed. With the advantage of simple construction, clear mathematical implications and low computational complexity, this method overcame the shift sensitive and the frequency aliasing in the discrete wavelet transform. The simulation results show that this algorithm can remove the power line interference and EMG interference, and the quantitative index of SNR and mean square error is superior to the traditional threshold de-noising algorithm. Therefore, the dual-tree complex wavelet transform de-noising algorithm will obtain clear medical wave signals.

Key words: de-noising, DTCWT, morphological filtering, pulse signal

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