Sensitivity optimization of Printed Spiral Coil for Wireless Resistive Analog Passive (WRAP) Sensors using Genetic Algorithm
Sensitivity optimization of Printed Spiral Coil for Wireless Resistive Analog Passive (WRAP) Sensors using Genetic Algorithm
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DOI：
10.1109/embc.2018.8513187
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发表时间：
2018-07
期刊：
影响因子：
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通讯作者：
B. Noroozi;B. Morshed
中科院分区：
文献类型：
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作者：
B. Noroozi;B. Morshed
穿戴式无电池无线电阻模拟无源（WRAP）传感器可以在不引人注目的同时连续收集生理数据。一对印刷螺旋线圈（PSC）之间的感应连接消除了侵入线。主、次PSC的感应连接使我们能够利用感应链路探测身体信号。初级侧电压由次级PSC上的感应体信号调制。线圈的物理特性影响灵敏度，其定义为观察到的电压变化超过传感器的变化。我们之前报道了一种迭代方法，通过最大化从初级到次级的功率传输效率，在约束线圈轮廓尺寸的情况下优化线圈规格以获得最大灵敏度。在本研究中，首先通过驱动电路元件和物理特性的解析多变量方程来最大化灵敏度，然后在考虑尺寸和制造约束的情况下使用遗传算法（GA）来最大化灵敏度。将结果与其他方法进行比较，结果显示，与最佳替代方法（sqp）相比，结果在102范围内更高。它帮助我们在嘈杂的环境中探测到更小的生理信号。
Body-worn battery-less Wireless Resistive Analog Passive (WRAP) sensor can be unobtrusive while collecting physiological data continuously. Inductive connection between a pair of Printed Spiral Coils (PSC) eliminates the intrusive wires. Inductive connection of primary and secondary PSC enabled us to probe the body signals using the inductive link. The primary side voltage is modulated by the sensed body signal at the secondary PSC. The coil physical characteristics influence the sensitivity which is defined as observed voltage changes over the sensor variation. We have previously reported an iterative method to optimize the coil specifications for maximum sensitivity with constrained coil prof ile size by maximizing the power transfer efficiency from primary to secondary. In this study sensitivity is maximized by first, driving an analytical multivariable equation of circuit components and physical characteristics, and then using Genetic Algorithm (GA) to maximize it with considering the size and fabrication constraints. The results are compared to the other methods that shows a higher result in the range of 102 comparing to the best alternate methods (sqp). It helps us to detect smaller physiological signals in the noisy environment.