基于试验方差分析的血氧测量波长选取的研究

为了提高血氧饱和度光谱测量的精度和可靠性，增强血氧饱和度测量数据的有效性，提出了基于试验方差分析的血氧测量波长选取的方法。通过分析不同波长组合对应的血氧饱和度系数分布情况，合理地利用统计理论，从中选取较好的波长组合。实验中以不同血氧饱和度临床数据为基础，建立了不同波长组合(660和940 nm，660和805 nm，805和940 nm)计算出的血氧饱和度系数的单因素试验方差分析模型，参照分析模型中的F指标和p参数，比较分析不同波长组合的显著性，进而从光谱数据中选取出相对较好的波长组合，为进一步建模分析提供了可靠的中间数据。结果表明，选取660和805 nm的波长组合引入的总误差相对较小，能更显著的代表血氧饱和度的变化，相比其他的波长组合进行分析能够提高血氧测量精度。本研究将试验方差分析方法用于血氧测量中波长组合的优选，效果显著，为血氧饱和度的测量和其他相关光谱的特征波长选取以及定量分析提供了新思路。试验方差分析方法有助于从光谱中提取代表被测量的有效信息。

Wavelength Selection of the Oximetry Based on Test Analysis of Variance

In order to improve the precision and reliability of the spectral measurement of blood oxygen saturation，and enhance the validity of the measurement, the method of test analysis of variance was employed. Preferred wavelength combination was selected by the analysis of the distribution of the coefficient of oximetry at different wavelength combinations and rational use of statistical theory. Calculated by different combinations of wavelengths (660 and 940 nm, 660 and 805 nm and 805 and 940 nm) through the clinical data under different oxygen saturation，the single factor test analysis of variance model of the oxygen saturation coefficient was established, the relative preferabe wavelength combination can be selected by comparative analysis of different combinations of wavelengths from the photoelectric volume pulse to provide a reliable intermediate data for further modeling. The experiment results showed that the wavelength combination of 660 and 805 nm responded more significantly to the changes in blood oxygen saturation and the introduced noise and method error were relatively smaller of this combination than other wavelength combination，which could improve the measurement accuracy of oximetry. The study applied the test variance analysis to the selection of wavelength combination in the blood oxygen result measurement，and the result was significant. The study provided a new idea for the blood oxygen measurements and other related spectroscopy quantitative analysis. The method of test analysis of variance can help extract the valid information which represents the measured values from the spectrum.