基于低语通道模式光共振传感器的生物医学试剂诊断

V. Saetchnikov, E. Tcherniavskaia, A. Saetchnikov, G. Schweiger, A. Ostendorf
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引用次数: 1

摘要

本文给出了介电微球在大范围浓度下在抗生素溶液中低语通道模式的光学共振光谱实验数据。在小于1微瓦的激光功率下,可以检测到光学共振。用阿莫西林、阿奇霉素、头孢唑啉、氯霉素、左氧氟沙星、林可霉素、苄西林、利帕哌康等不同代抗生素在去离子水和生理溶液中进行测定。谱移和共振谱的结构都是本研究的重点。利用开发的多层感知器网络进行了阻力识别。设计的网络拓扑结构包括:多层感知器的若干隐藏层、每层中的若干神经元、神经网络的训练方法、各层的激活函数、接收值与要求值的偏差类型和大小。对于网络训练,采用了各种修正的反向传播误差方法。输入媒介对应于正在调查的6类生物物质。当每个区域代表空间中的某种物质:光共振最大值的相对谱移- WGM的相对激发效率单连通时,分类结果为正。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Diagnostics of biomedical agents by whispering gallery mode optical resonance based sensor
Experimental data on optical resonance spectra of whispering gallery modes of dielectric microspheres in antibiotic solutions under varied in wide range concentration are represented. Optical resonance was demonstrated could be detected at a laser power of less than 1 microwatt. Several antibiotics of different generations: Amoxicillin, Azithromycin, Cephazolin, Chloramphenicol, Levofloxacin, Lincomicin Benzylpenicillin, Riphampicon both in de-ionized water and physiological solution had been used for measurements. Both spectral shift and the structure of resonance spectra were of specific interest in this investigation. Drag identification has been performed by developed multilayer perceptron network. The network topology was designed included: a number of the hidden layers of multilayered perceptron, a number of neurons in each of layers, a method of training of a neural network, activation functions of layers, type and size of a deviation of the received values from required values. For a network training the method of the back propagation error in various modifications has been used. Input vectors correspond to 6 classes of biological substances under investigation. The result of classification was considered as positive when each of the region, representing a certain substance in a space: relative spectral shift of an optical resonance maxima - relative efficiency of excitation of WGM, was singly connected.
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