Design and nonlinear modeling of a sensitive sensor for the measurement of flow in mice.
Design and nonlinear modeling of a sensitive sensor for the measurement of flow in mice.
复制标题
用于测量小鼠流量的灵敏传感器的设计和非线性建模。
DOI：
10.1088/1361-6579/aacb1b
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发表时间：
2018-07-03
影响因子：
3.2
通讯作者：
Suki B
中科院分区：
文献类型：
--
作者：
Jawde SB;Smith BJ;Sonnenberg A;Bates JHT;Suki B
虽然许多研究依赖于呼吸道疾病小动物模型中的流量和压力测量，但此类测量结果可能不准确且难以获得。因此，本研究的目标是设计和实现一种易于制造且能够监测流量的精确传感器。我们设计并 3D 打印了流量计，并利用参数（电阻和惯性）和非参数（多项式和 Volterra 系列）系统识别来表征该设备。使用共模抑制比 (CMRR) 在封闭系统中测试传感器的表观流量。该传感器正确测量了自主呼吸小鼠的潮气量和呼吸频率。该设备用于评估呼吸机在肺损伤之前和之后输送规定量的能力。参数模型和多项式模型提供了独立测量流量的合理预测（确定系数（Cν）分别= 0.9591和0.9147），但具有六个时间点记忆的一阶、二阶和三阶Volterra级数提供了更好的拟合（Cν分别= 0.9775、0.9787和0.9954）。在小鼠呼吸频率（1-5 Hz）及以下时，CMRR 高于 40 dB。肺损伤后，传感器显示输送潮气量显着下降。我们证明，非参数非线性 Volterra 系列建模与 3D 打印技术相结合的应用可以廉价且快速地制造精确的流量传感器，用于连续测量各种生理条件下的小流量。
While many studies rely on flow and pressure measurements in small animal models of respiratory disease, such measurements can however be inaccurate and difficult to obtain. Thus, the goal of this study was to design and implement an easy to manufacture and accurate sensor capable of monitoring flow. We designed and 3-D printed a flowmeter and utilized parametric (resistance and inertance) and nonparametric (polynomial and Volterra series) system identification to characterize the device. The sensor was tested in a closed system for apparent flow using the common mode rejection ratio (CMRR). The sensor properly measured tidal volumes and respiratory rates in spontaneously breathing mice. The device was used to evaluate a ventilator’s ability to deliver a prescribed volume before and after lung injury. The parametric and polynomial models provided a reasonable prediction of the independently measured flow (Coefficient of determination (Cν)=0.9591 and 0.9147 respectively), but the Volterra series of the 1st, 2nd, and 3rd order with a memory of six time points provided better fits (Cν=0.9775, 0.9787, and 0.9954, respectively). At and below the mouse breathing frequency (1–5 Hz), CMRR was higher than 40 dB. Following lung injury, the sensor revealed a significant drop in delivered tidal volume. We demonstrate that the application of nonparametric nonlinear Volterra series modeling in combination with 3-D printing technology allows the inexpensive and rapid fabrication of an accurate flow sensor for continuously measuring small flows in various physiological conditions.
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