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
	Ding H. Q.; Lu Q. P.; Gao H. Z.; Peng Z. Q.
	2014
发表期刊	Biomedical Optics Express
ISSN	ISBN/2156-7085
卷号	5 期号:4 页码:1145-1152
摘要	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
收录类别	SCI ; EI
语种	英语
文献类型	期刊论文
条目标识符	http://ir.ciomp.ac.cn/handle/181722/44194
专题	中科院长春光机所知识产出
推荐引用方式 GB/T 7714	Ding H. Q.,Lu Q. P.,Gao H. Z.,et al. Non-invasive prediction of hemoglobin levels by principal component and back propagation artificial neural network[J]. Biomedical Optics Express,2014,5(4):1145-1152.
APA	Ding H. Q.,Lu Q. P.,Gao H. Z.,&Peng Z. Q..(2014).Non-invasive prediction of hemoglobin levels by principal component and back propagation artificial neural network.Biomedical Optics Express,5(4),1145-1152.
MLA	Ding H. Q.,et al."Non-invasive prediction of hemoglobin levels by principal component and back propagation artificial neural network".Biomedical Optics Express 5.4(2014):1145-1152.

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