Noninvasive Measurement of the Human RBC Concentration Based on BP NN Model
ZHANG Bao-ju1, LEI Qing1, LI Gang2, LIN Ling2, WANG Hui-quan2, Jean Gao1
1. College of Physics and Electronic Information, Tianjin Normal University, Tianjin 300387, China 2. School of Precision Instrument and Opto-Electronics Engineering, Tianjin University, Tianjin 300072, China
Abstract：In the present article, the BP neural network’s arithmetic model is applied to the noninvasive detection of the concentration of the red blood cell of human body. Due to the use of BP neural network in the modeling and analysis of the dynamic spectrum data and the actual measured value of the red blood cell, the authors get a better result which refers to that the output value tracks the expected result very well. The related coefficient R can reach 0.993. When predicting the output value in the way of the BP neural network model, the maximal relative error is only 4.7%, average relative error is 2.1%, so the authors can say that it has more ideal prediction ability. The experimental result shows that the BP neural network model can be accurate in dealing with the nonlinear relation between the dynamic spectrum data and human erythrocyte practical value and it can make the method of noninvasive blood analysis more useful in clinical application. So it has a high application value.
张宝菊1，雷 晴1，李 刚2，林 凌2，王慧泉2，Jean Gao1 . 基于BP神经网络的人体血液中红细胞浓度无创检测 [J]. 光谱学与光谱分析, 2012, 32(09): 2508-2511.
ZHANG Bao-ju1, LEI Qing1, LI Gang2, LIN Ling2, WANG Hui-quan2, Jean Gao1 . Noninvasive Measurement of the Human RBC Concentration Based on BP NN Model . SPECTROSCOPY AND SPECTRAL ANALYSIS, 2012, 32(09): 2508-2511.
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