电化学阻抗谱层析成像（micro elelctrical impedance spectroscopic tomography,μEIST）技术是一种可集成于微流控芯片（Lab on a chip）上并且可以对异常细胞（如死细胞或癌细胞）的分离过程进行实时可视化监测的技术。本研究的主要目的是开发出可以在微流道内实现多种细胞分布的μEIST技术。研究对象为活、死以及其混合的酵母菌细胞溶液,其中活酵母菌细胞代表正常细胞,死酵母菌细胞为异常细胞。本研究中,为了达到研究目的,在理论研究的基础之上,将具体的μEIST检测研究分为三个步骤,其包括微型电阻抗成像（micro elelctrical impedance tomography,μEIT）、微型电化学阻抗谱（micro elelctrical impedance spectroscopy,μEIS）和μEIST技术。本研究具体内容及结论包括:首先,对基础理论的归纳和总结,其主要为微流道内流体特性和微电极电阻抗检测特性的相关研究。关于流体流动的研究表明,微流道内流体为稳定的层流,有利于电阻抗检测。在微电极电阻抗检测方面,通过现有的理论知识,结合仿真及实验的分析及验证,总结出了微电极和微型传感器检测电阻抗时的特征。研究表明,在采用微电极进行电阻抗检测时,其电极附近电压压降很大;电极和溶液表面的双电层（EDL）接触阻抗在检测电流频率较低时对于阻抗检测的影响非常大;在细胞检测方面,细胞溶液的低频电阻抗特征被接触阻抗所掩盖,因此微电极在低频段的电阻抗检测具有局限性。其次,在基础理论的支撑下,对μEIT技术进行研究。其目的是实现微流道内单一种类细胞分布的可视化检测。研究中在搭建μEIT系统软硬件之外,还对比分析了EIT反问题的成像算法,并且通过仿真分析了电极接触阻抗对μEIT成像的影响。其结果表明,接触阻抗影响越大,成像质量越差。在此基础上,通过实验对酵母菌细胞沉淀于微流道底部的分布进行可视化检测,其结果显示,当检测电流的频率较低时,由于电极双电层接触阻抗的影响,难以正确成像;当检测频率增加时,其接触阻抗的影响降低,画质提升。实验结果表明,在f=1MHz附近时,成像图像的画质最佳。再次,在μEIT技术实现单一种类细胞在微流道分布成像的基础上,通过μEIS技术来实现对微流道内多种细胞进行电阻抗检测。该研究通过建立检测对象的电阻抗模型,再通过实验来验证。其结果表明,细胞溶液的电阻抗值随着离子浓度的增大而减小。在此基础上开发出基于μEIS的可以定量检测混合活、死酵母菌细胞溶液中活细胞浓度的测量方法。其实验结果表明,混合活、死酵母菌细胞溶液中,活细胞由于细胞膜的高阻抗性,从而小于细胞培养液的导电率,而死细胞由于细胞膜破裂,其电导率最大。该理论也为μEIST分频成像中各种细胞寻找最佳成像频率提供了选择方法和依据。最后,基于μEIT的成像技术和μEIS的细胞特征频率的确定开发出了基于多频率检测的μEIST技术。μEIST对于不同的细胞采用其各自最佳的特征频率分别进行成像,然后采用调整函数对结果进行筛选,最后合成并正规化为一幅可以准确描述所有种类细胞分布的图像。在该研究中,由于受制于实验条件,本研究以仿真模拟来对混合活、死酵母菌细胞分离后的分布进行成像,最终仿真结果表明,μEIST技术相较于单一频率成像的μEIT技术图像质量有所提升。

设计并实现了一种基于STM32为核心的低成本高精度的电能测量装置,该测量装置设计主要由硬件电路和嵌入式软件来共同实现。阐述了测量装置的高精度电量信号采样、开关量输入、开关量输出的设计和成本控制,以及ModBus-RTU协议下的远程通信等内容。装置已在工程中得到应用,应用结果表明:该装置满足工业级的需求,运行稳定、可靠,通用性好,测量精度高,具有很强的实用性和推广价值。

Image reconstruction of Electrical Impedance Tomography (EIT) is a highly nonlinear ill-posed inverse problem, which is sensitive to the measurement noise and model errors. An improved Convolutional Neural Network (CNN) method is proposed for the EIT lung imaging. The proposed method is optimized based on the Visual Geometry Group (VGG) model, adding the batch normalization (BN) layer, ELU activation function, global average pooling (GAP) layer, and radial basis function (RBF) neural network. These optimizations help speed up network convergence, and improve reconstruction accuracy and robustness. Nearly 10 thousand EIT simulation models generated from chest CT images of 60 patients are used for the network training. The chest deformation, lung hyperdilation and atelectasis are randomly simulated during the model generation process. The proposed method after training is tested through a series of simulation data and experimental models. The reconstruction quality is quantitatively compared by calculating the root mean square error (RMSE) and image correlation coefficient (ICC). On average, the proposed method achieves 0.082 RMSE and 0.892 ICC through experimental results. The proposed method achieves high-resolution and robust shape reconstructions with multiphase conductivity for EIT lung imaging, especially in the presence of the measurement noise and interference. The proposed method is promising in providing quantitative images for potential clinical applications, such as human thorax imaging.
© 2001-2012 IEEE.

A portable Electrical Impedance Tomography (EIT) device has been developed for online thrombus detection in extracorporeal-circulation equipment. For the portable EIT device, circuits of multiplexer module are designed to expend channels, pipeline processing mechanism is introduced to increase processing speed, and data acquisition rate reaches 50 Frames Per Second (FPS) and the online tomography rate reaches 40 FPS with 8-electrode sensor. To test the characteristics of the proposed EIT device, a series of experiments are conducted. Firstly, small sensors with different size and plastic phantoms are used to test the static properties of the device. Testing results show that the quality of the reconstructed images is related to the diameter of sensor, and Image Correlation (IC) reaches 0.75 when diameter of sensor is 30 mm. Secondly, swine blood is used for making thrombus to verify the EIT device's image reconstruction ability of thrombus in stationary conditions instead of human blood. Experiments show that the reconstructed image error is 8.07% when diameter of the sensor is 10 mm, and it reduces to 1.49% when diameter is 30 mm. Finally, experiments are conducted to measure the position of flowing thrombus. Euclidean distance between voltage data is used to judge the occurrence of thrombus. Experimental results indicate that thrombus is clearly distinguished from the background solution in fluids. As a conclusion, the proposed EIT device is of great significance for online thrombus detection in extracorporeal-circulation system.

A novel position measurement approach for a single particle in a channel using Electrical Impedance Spectroscopy (EIS) only with two pairs of electrodes is proposed. The proposed approach is label-free, non-invasive and is very accurate in measurement domain by using machine learning method. Relationship between the single particle's position and the measured impedances is described by a set of nonlinear equations showing excellent fitting performance with R-square reaching 0.9999. Finding accurate analytical solution of the particle's position is the inverse problem, it is tackled by a well-trained Support Vector Regression (SVR) model with the help of multi-frequency EIS. The proposed approach is evaluated by simulation models with a single particle in 100 different positions. The results show that the approach performs an outstanding position measurement accuracy to reach 99.25%. Comparing with EIT, it has more simple structure, less measurement time and more accurate measurement results.
© 2020

A hybrid Genetic Algorithm (GA) and Levenberg-Marquardt (GA-LM) method is proposed for cell suspension measurement with electrical impedance spectroscopy. This algorithm combines the GA with global search ability and Levenberg-Marquardt (LM) algorithm with local search ability, which has the advantages of high accuracy and high robustness. First, GA-LM is compared with GA and LM algorithm separately by ideal simulation. Second, Gaussian noise is added to the ideal simulation data. The anti-noise ability of the GA-LM is discussed. Finally, experiments are conducted to verify the practicability of the proposed GA-LM method. In the experiment, GA-LM is used to fit the impedance spectrum of yeast suspensions with different volume fractions and active states. The results show that the GA-LM algorithm can converge to the real value that is set in the simulation under ideal numerical simulation conditions. In the simulation within 2% noise level, the mean relative error of the parameter solution is less than 4%, and the root mean square error of the fitting is less than 0.4. This method also performs well in fitting of the experimental data. In addition, the electric double layer resistance and cell membrane capacitance are selected as the main indicators for the identification of yeast suspension concentration and activity, respectively.
© 2020 Author(s).

微电流激励的生物阻抗测量方法在生物医学中具有广泛应用前景,其中能够驱动生物负载的电压控制电流源是生物阻抗测量的前提条件。本文提出一种具有高带宽、高输出阻抗、能驱动较大容性负载的电流源电路拓扑结构。首先,根据系统的传递函数分析系统不稳定的原因并引入容性负载对系统的影响;接着,使用双通道反馈补偿的方法弥补了系统高频不稳定的缺陷,并在反馈通路使用简单的阻容网络实现容性负载的补偿;然后,仿真分析得出电流源在100 Hz～1.2 MHz的带宽范围内具有较好的恒流特性,在1 MHz的输出阻抗达到为160.756 kΩ,并且当负载的复阻抗越大时,系统稳定裕度越高。最后,使用该电流源激励生物组织进行实验验证,在不同的频率下对比传统增强型Howland和三运放电流源,结果表明在800 KHz以上,其它两种电流源无法成像时该电流源仍具有很好的成像效果,也验证了该电流源在测量生物组织时的实用性。