谐波分量提高动态光谱法无创血液成分检测精度

为增加动态光谱数据的信噪比，提高预测模型稳定性和预测精度，提出将多次谐波分量计入动态光谱数据频域数据处理的改进方法。对110名志愿者进行临床采集，依据其脉搏波信号质量和谐波分布状况，确定其中60例样本为研究对象。在提取样本动态光谱时，以是否加入谐波分量为标准分成实验组和对照组。分别建立两组动态光谱和人体血红蛋白含量的BP神经网络模型，结果显示实验组预测集相关系数为0.91，远大于对照组预测集相关系数0.80，其余各项指标均有明显改善。实验证明利用谐波分量可提高动态光谱数据信噪比，有利于推动基于动态光谱的无创血液成分检测技术的进一步发展。

Increasing the Precision of the Noninvasive Blood Components Measurement Based on DS Method Using Harmonic Waves

To improve the signal-to-noise ratio (SNR) of the dynamic spectrum (DS) data and to increase the stability of the model and the prediction accuracy, the harmonic waves of DS data were introduced into DS method. Sixty samples were determined as the research objects according to the quality of the pulse wave and the distribution of the harmonic waves after further analysis of 110 volunteers’ data acquired in vivo. This paper took whether adding the energy of harmonic waves into the DS data as the division standard to generate two groups. BP artificial neural network was used to establish the calibration model of subjects’ hemoglobin values against DS. The correlation coefficients of the predicted values and the true values in experimental group, containing the energy of harmonic waves, was 0.91, much higher than 0.80 in the control group. Other indexes were all improved too. The results showed that the modified method can enhance the SNR of DS method and accelerate the development of noninvasive blood components measurement based on DS method.