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 μAU降低至12 μAU，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。

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 μAU to 12 μAU 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.