基于神经网络的SRR负载贴片天线无创血糖监测设计

2019 4th International Conference on Information Systems and Computer Networks (ISCON) Pub Date : 2019-11-01 DOI:10.1109/ISCON47742.2019.9036239

Palak Tripathi, Praveen Kumar, Saurabh Raj, S. Tripathi, V. Tripathi

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引用次数: 4

摘要

本文提出了一种用于监测人体血糖浓度的宽带天线的新设计。设计的天线在辐射贴片上使用了一种以分环谐振器(SRR)形式加载的超材料。它有一个紧凑的大小$(14\ × 17\ × 1.57)\ \text{mm}^{3}$。该天线在21.65 GHz和25.35 GHz频率下分别实现了约6.96 dBi和3.65 dBi增益。它的宽带为6.49 GHz，范围从21.097 GHz到27.59 GHz，也涵盖了5G频段。在实验室模拟制作了基于SRR加载贴片天线的射频传感器，并与人体组织的三维模型进行了叠加，以研究其性能。此外，一种被称为人工神经网络(ANN)的优化技术也被用于在带宽方面优化天线参数。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

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ANN Based Design of SRR Loaded Patch Antenna for Non-Invasive Blood Glucose Monitoring

A novel design of a wideband antenna is proposed in this paper for monitoring the blood glucose concentration in the human body. The designed antenna uses a metamaterial in the form of a split-ring resonator (SRR) loading on a radiating patch. It has a compact size of $(14\times 17\times 1.57)\ \text{mm}^{3}$. The proposed antenna has realized a gain of about 6.96 dBi and 3.65 dBi at frequencies 21.65 GHz and 25.35 GHz respectively. It has a wide band of 6.49 GHz ranging from 21.097 GHz to 27.59 GHz which covers the 5G frequency band as well. The proposed RF sensor based on SRR loaded patch antenna is simulated and fabricated in the lab for stacking with 3D models of human tissues to investigate its performance. Further, an optimization technique called, Artificial Neural Network (ANN) has also been used to optimize the antenna parameters in terms of bandwidth.

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来源期刊

2019 4th International Conference on Information Systems and Computer Networks (ISCON)

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