Non-invasive prediction of hemoglobin levels by principal component and back propagation artificial neural network
Non-invasive prediction of hemoglobin levels by principal component and back propagation artificial neural network
复制标题
通过主成分和反向传播人工神经网络对血红蛋白水平进行无创预测
DOI：
10.1364/boe.5.001145
复制
发表时间：
2014-04-01
影响因子：
3.4
通讯作者：
Peng, Zhongqi
中科院分区：
文献类型：
--
作者：
Ding, Haiquan;Lu, Qipeng;Peng, Zhongqi
为便于贫血的非侵入性诊断，研制了专用设备，研究了基于反向传播人工神经网络(BP-ANN)的血红蛋白无创检测方法。本文将由9个LED组成的宽带光源与光栅式光谱仪和硅光电二极管阵列相结合，研制了一种高性能的分光光度系统。利用该仪器对109名志愿者的指尖光谱进行了测量。为了消除冗余数据的干扰，采用主成分分析对采集的光谱数据进行降维处理。然后将光谱的主成分作为BP-ANN模型的输入。在此基础上，得到了最优的网络结构，其中输入层、隐含层和输出层的节点数分别为9、11和1。用校准和校正样本集分析无创血红蛋白测量的精度，用预测样本集检验模型的适应性。用该方法建立的网络模型的相关系数为0.94，校正、校正和预测的标准误差分别为11.29g/L、11.47g/L和11.01g/L。结果表明，三个样本集的频谱与实际血红蛋白水平之间存在较好的相关性，模型具有较好的稳健性。结果表明，该分光光度系统具有BP-ANN与主成分分析相结合的无创检测Hb水平的潜力。(C)2014年美国光学学会
To facilitate non-invasive diagnosis of anemia, specific equipment was developed, and non-invasive hemoglobin (HB) detection method based on back propagation artificial neural network (BP-ANN) was studied. In this paper, we combined a broadband light source composed of 9 LEDs with grating spectrograph and Si photodiode array, and then developed a high-performance spectrophotometric system. By using this equipment, fingertip spectra of 109 volunteers were measured. In order to deduct the interference of redundant data, principal component analysis (PCA) was applied to reduce the dimensionality of collected spectra. Then the principal components of the spectra were taken as input of BP-ANN model. On this basis we obtained the optimal network structure, in which node numbers of input layer, hidden layer, and output layer was 9, 11, and 1. Calibration and correction sample sets were used for analyzing the accuracy of non-invasive hemoglobin measurement, and prediction sample set was used for testing the adaptability of the model. The correlation coefficient of network model established by this method is 0.94, standard error of calibration, correction, and prediction are 11.29g/L, 11.47g/L, and 11.01g/L respectively. The result proves that there exist good correlations between spectra of three sample sets and actual hemoglobin level, and the model has a good robustness. It is indicated that the developed spectrophotometric system has potential for the non-invasive detection of HB levels with the method of BP-ANN combined with PCA. (C) 2014 Optical Society of America