吉林大学学报(工学版) ›› 2014, Vol. 44 ›› Issue (3): 847-853.doi: 10.13229/j.cnki.jdxbgxb201403043

• 论文 • 上一篇    下一篇

基于动态差分阈值的脉搏信号峰值检测算法

张爱华1,2,王平1,2,丑永新1,2   

  1. 1.兰州理工大学 电气工程与信息工程学院, 兰州730050;
    2.甘肃省科技厅 甘肃省工业过程先进控制重点实验室, 兰州730050
  • 收稿日期:2012-12-17 出版日期:2014-03-01 发布日期:2014-03-01
  • 作者简介:张爱华(1964),女,教授,博士生导师.研究方向:生物医学信号检测与处理.E-mail:lutzhangah@163.com
  • 基金资助:
    国家自然科学基金项目(81360229);高等学校博士学科点专项科研基金项目(20116201110002);甘肃省自然科学基金项目(1014RJZA013).

Peak detection of pulse signal based on dynamic difference threshold

ZHANG Ai-hua1,2, WANG Ping1,2,CHOU Yong-xin1,2   

  1. 1.College of Electrical and Information Engineering, Lanzhou University of Technology, Lanzhou 730050, China;
    2.Gansu Provincial Sci. & Tech. Department, Key Laboratory of Gansu Advanced Control for Industrial Processes, Lanzhou 730050, China
  • Received:2012-12-17 Online:2014-03-01 Published:2014-03-01

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摘要： 针对传统幅度阈值法在脉搏信号峰值检测中所存在的问题,同时为了避免脉搏信号中的干扰段对信号分析所带来的风险,提出了基于动态阈值的脉搏信号峰值检测方法。采用动态差分阈值提取脉搏信号峰值,并在其提取过程中依据阈值适时应用符号化信号近似匹配的方法检测脉搏信号干扰段。通过对视觉疲劳试验过程中采集的脉搏信号进行分析,结果表明:该方法能够准确地提取脉搏主波位置和脉搏峰值,效果明显优于传统幅度阈值法。

关键词: 信息处理技术, 脉搏信号, 幅度阈值, 干扰段检测, 动态差分阈值

Abstract: Using traditional pulse analysis method could bring serious influence on the accuracy and reliability of pulse signal feature detection. In order to overcome the shortcoming of the traditional threshold algorithm in peak detection of pulse signal, also to avoid the risk caused by the interference segment of pulse signal on signal analysis, a dynamic threshold method was presented to extract the peak of pulse wave. The symbolic aggregate approximation algorithm was timely used according to the difference and amplitude threshold to detect interference segment in the process. The pulse signals collected in the experiment of video display terminal fatigue were analyzed by this method. The results show that the proposed method can accurately extract the pulse peak and the position. It is obviously superior to the traditional method.

Key words: information processing, pulse signal, amplitude threshold, interference detection, dynamic difference threshold

中图分类号: 

  • TN911.73
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