Maximum and accurate information of blood components are expected by clinicians during medical sample detection and disease monitoring. Photoplethysmography (PPG) and its morphological features are commonly used for measurement and analysis but significant fundamental limitations including spectral noise, interaction of subjects’ variability portions (skin, fat and muscle) and the absorbing components (water, and blood) still affects the quality of the PPG morphology in optical based extractions of blood components and spectral monitoring. Dynamic spectrum (DS) is a potential clinical method to consider these effect in the physiological PPG sample. In this article, we proposed a novel filtering DS based method using adaptive time varying filter (ATVF) to consider the effect and meaning of spectral amplification of the physiological PPG signal. The spectrum PPG sample was partitioned into two equal halves of upper and lower (UL) sample to ensure spectral amplification and analysis with DS. The results from 184 clinical volunteers confirms that spectrum PPG signal amplification significantly influences the accuracy of the noninvasive optical analysis of blood components by adding noise effect due to signal weakening but increases the spectral component. A radial basis function (RBF) neural network modeling of the calibration and prediction data sets shows the performance of the proposed ATVF-UL extraction by reducing significantly the induced noise effect for smooth DS component and maximum detection of blood components.

临床医生期望在医学样本检测和疾病监测期间获得最大和准确的血液成分信息。光电容积描记术（PPG）及其形态特征通常用于测量和分析，但是显着的基本局限性包括光谱噪声，受试者可变性部分（皮肤，脂肪和肌肉）和吸收成分（水和血液）的相互作用仍然会影响质量PPG形态在基于光学的血液成分提取和光谱监测中的应用 动态光谱（DS）是一种潜在的临床方法，可以考虑在生理PPG样品中产生这些效应。在本文中，我们提出了一种使用自适应时变滤波器（ATVF）的基于滤波DS的新颖方法，以考虑生理PPG信号频谱放大的效果和含义。将光谱PPG样品分为上下相等（UL）样品的两等份，以确保光谱放大和使用DS进行分析。184位临床志愿者的结果证实，频谱PPG信号放大通过增加信号减弱引起的噪声效应，显着影响血液成分的非侵入性光学分析的准确性，但会增加频谱成分。校准和预测数据集的径向基函数（RBF）神经网络建模通过显着减少平滑的DS分量和最大程度地检测血液分量的感应噪声效果，显示了拟议ATVF-UL提取的性能。来自184名临床志愿者的结果证实，频谱PPG信号放大通过增加信号减弱引起的噪声效应，显着影响血液成分的非侵入性光学分析的准确性，但会增加频谱成分。校准和预测数据集的径向基函数（RBF）神经网络建模通过显着减少平滑的DS分量和最大程度地检测血液分量的感应噪声效果，显示了拟议ATVF-UL提取的性能。184位临床志愿者的结果证实，频谱PPG信号放大通过增加信号减弱引起的噪声效应，显着影响血液成分的非侵入性光学分析的准确性，但会增加频谱成分。校准和预测数据集的径向基函数（RBF）神经网络建模通过显着减少平滑的DS分量和最大程度地检测血液分量的感应噪声效果，显示了拟议ATVF-UL提取的性能。