自适应滤波在近红外无创生化分析中的应用

卢启鹏; 陈丛; 彭忠琦

doi:10.3788/OPE.20122004.0873

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自适应滤波在近红外无创生化分析中的应用

信息科学 | 更新时间：2020-08-12

- 自适应滤波在近红外无创生化分析中的应用
- Application of adaptive filter to noninvasive biochemical examination by near infrared spectroscopy
- 光学精密工程 2012年20卷第4期页码：873-879
- 作者机构：
  
  1. 中国科学院长春光学精密机械与物理研究所应用光学国家重点实验室,吉林长春,130033
  2. 中国科学院研究生院北京,100039
- 作者简介：
- 基金信息：
  
  国家自然科学基金资助项目(No.60878052,60938002,61078038)();中国科学院知识创新工程领域前沿资助项目(No.Y00232Q100)();应
- DOI：10.3788/OPE.20122004.0873
  中图分类号： Q503;O657.33
- 收稿日期：2011-03-15，
  
  修回日期：2011-04-08，
  
  网络出版日期：2012-04-22，
  
  纸质出版日期：2012-04-22
- 稿件说明：
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卢启鹏, 陈丛, 彭忠琦. 自适应滤波在近红外无创生化分析中的应用[J]. 光学精密工程, 2012,20(4): 873-879

LU Qi-peng, CHEN Cong, PENG Zhong-qi. Application of adaptive filter to noninvasive biochemical examination by near infrared spectroscopy[J]. Editorial Office of Optics and Precision Engineering, 2012,20(4): 873-879
卢启鹏, 陈丛, 彭忠琦. 自适应滤波在近红外无创生化分析中的应用[J]. 光学精密工程, 2012,20(4): 873-879 DOI： 10.3788/OPE.20122004.0873.

LU Qi-peng, CHEN Cong, PENG Zhong-qi. Application of adaptive filter to noninvasive biochemical examination by near infrared spectroscopy[J]. Editorial Office of Optics and Precision Engineering, 2012,20(4): 873-879 DOI： 10.3788/OPE.20122004.0873.

摘要

提出用血流容积差光谱相减法来消除近红外无创生化分析中组织背景的干扰。为提高光谱相减中所需获得的脉搏波近红外光谱信号的信噪比

研究了自适应滤波处理方法。介绍了最小均方算法(LMS)自适应滤波的基本原理

在此基础上提出了一种适用于处理本实验脉搏波光谱信号的自适应滤波方法;采用实验室自行研制的16元近红外脉搏波采集系统

获得人体脉搏波光谱信号;最后

利用提出的自适应滤波方法处理脉搏波光谱信号并分析其滤波效果。结果表明

利用该方法处理采集的脉搏波信号

可使血流容积光谱相减后血液光谱吸光度噪声由800 AU降低至12 AU

相邻波长的脉搏波相关系数由0.994 0提高至0.999 9。分析结果说明该自适应滤波方法可以有效地应用于近红外无创生化分析中。

Abstract

Subtracted blood volume spectrometry was employed to the noninvasive biochemical examination with near infrared spectroscopy(NIRS) to eliminate the influence of tissues.To raise the Signal to Noise Ratio(SNR) of the NIRS pulse wave signal needed by the spectral subtraction

an effective adaptive filter method was proposed to process the pulse wave signal. The principles of Least Mean Square(LMS) adaptive filter were described

and a new adaptive filtering way fit for the pulse wave signal of this experiment was proposed. Then

a 16-pixel near-infrared pulse wave acquisition system made by ourselves was used to collect the pulse wave signals of human body. Finally

the proposed adaptive filtering way was used to process the NIRS pulse wave signals and analyze the results. The result shows that the noise level of blood spectrum has reduced from 800 AU to 12 AU after spectral subtraction by using the proposed method

and the related coefficient of pulse wave of adjacent wavelength has raised from 0.994 0 to 0.999 9. The analysed result verifies that the method is effective in the NIR noninvasive biochemical examination area.

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references

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