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基于小波模极大原理的脉象特征提取研究

Acquisition of Pulse Characteritics Based on Wavelet Module Maximum Principle.

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【作者】 王燕白涛康景利

【Author】 WANG Yan, BAI Tao, KANG Jing-li. College of Information and Mechanical Engineering, Beijing Institute of Graphic Communication, Beijing, 102600,China

【机构】 北京印刷学院信息与机电工程学院华为公司北京研究所北京理工大学机电工程学院 北京 102600北京 100085北京 100081

【摘要】 目的根据小波分析原理,研究脉象特征提取方法,以有效解决基于时域或频域的传统方法所无法准确提取脉象特征的问题。方法运用小波模极大方法进行脉象信号周期分割和基本分解,沿时间排列并符号化脉象波上升沿与下降沿的模极大特征点、脉象波谷底和波峰的模极大特征点。结果确定了不明显的重搏前波、重搏波,以及在主波上升沿和下降沿上出现的不规则脉波,并进一步准确提取了脉象信号的多尺度特征和各种时域特征。结论采用此方法进行脉象信号的特征点定位并进一步完成特征提取,具有简单、快速、准确等特点,为进一步进行脉象分类识别研究奠定了基础。

【Abstract】 Objective To study a wavelet method for acquiring the characters of pulse wave based on the principle of wavelet transform which can effectively solve the problem of inaccuracy of the conventional methods. Method The method of wavelet module maximum was used to divide the pulse wave according to periods and basically decomposed it, by arranging in time order and symbolizing the module maximum character points of pulse wave signal at the ascending and descending edges as well as the crest and trough. Result Through the method, the unobvious dicrotism, trail wave and the anomalistic wave appearing at the ascending and descending edge of the main wave, and multi-scale characters and all kinds of characters in time domain of pulse signal were further acquired more accurately. Conclusion Simplicity, quickness and accuracy are achieved by focusing on the character points of pulse signals. It provides a new means for further studies of classification and identification of pulse signals.

  • 【文献出处】 航天医学与医学工程 ,Space Medicine & Medical Engineering , 编辑部邮箱 ,2006年01期
  • 【分类号】R318
  • 【被引频次】26
  • 【下载频次】299
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