Hartinger Alzbeta Elizabeth, Gagnon Hervé, Guardo Robert
Institut de Génie Biomédical, Ecole Polytechnique de Montréal, Montréal H3T 1J4, Canada.
Physiol Meas. 2006 May;27(5):S51-64. doi: 10.1088/0967-3334/27/5/S05. Epub 2006 Apr 18.
Electrical impedance tomography (EIT) image reconstruction is an ill-posed problem requiring maximum measurement precision. Recent EIT systems claim 60 to 80 dB precision. Achieving higher values is hard in practice since measurements must be performed at relatively high frequency, on a living subject, while using components whose tolerance is usually higher than 0.1%. To circumvent this difficulty, a method for modelling the electronic circuits of an EIT system was developed in order to optimize the circuits and incorporate the model in the reconstruction algorithms. The proposed approach is based on a matrix method for solving electrical circuits and has been applied to the scan-head which contains the front-end electronic circuits of our system. The method is used to simulate the system characteristic curves which are then optimized with the Levenberg-Marquardt method to find optimal component values. A scan-head was built with the new component values and its simulated performance curves were compared with network analyser measurements. As a result of the optimization, the impedance at the operating frequency was increased to minimize the effects of variations in skin/electrode contact impedance. The transconductance and gain frequency responses were also reshaped to reduce noise sensitivity and unintended signal modulation. Integrating the model in the reconstruction algorithms should further improve overall performance of an EIT system.
电阻抗断层成像(EIT)图像重建是一个需要最高测量精度的不适定问题。最近的EIT系统声称精度可达60至80分贝。在实际中要实现更高的值很困难,因为测量必须在相对较高的频率下对活体进行,同时使用公差通常高于0.1%的组件。为了克服这一困难,开发了一种对EIT系统的电子电路进行建模的方法,以便优化电路并将该模型纳入重建算法。所提出的方法基于一种求解电路的矩阵方法,并已应用于包含我们系统前端电子电路的扫描头。该方法用于模拟系统特性曲线,然后用Levenberg-Marquardt方法对其进行优化,以找到最佳组件值。用新的组件值构建了一个扫描头,并将其模拟性能曲线与网络分析仪的测量结果进行了比较。优化的结果是,工作频率下的阻抗增加,以最小化皮肤/电极接触阻抗变化的影响。跨导和增益频率响应也进行了重塑,以降低噪声敏感性和意外信号调制。将该模型纳入重建算法应能进一步提高EIT系统的整体性能。