Monitoring the properties of biological samples (BS) is expensive in terms of time consumption and cost in resources and human effort. There are monitoring methods using different techniques, depending on the type of biological sample (cells, tissues, blood, etc.). In this thesis, we improve the accuracy of the ECIS (electrical cell-substrate impedance spectroscopy) technique of bioimpedance (BI) measurement of a monolayer cell-culture (CC), which measures the electrical response of a CC when an alternating current is applied to it at several frequencies. Specifically, this dissertation is focused on the modeling of the cell-electrode (CE) block, and the real-time monitoring and acquisition of the cell concentration in a CC assay experiment. In addition, using as a database the CE model obtained in the modeling stage, a toolbox has been built to perform efficient electrical real-time simulations with Ngspice, launching these simulations from Matlab. Herein, the BI measurement is applied indirectly. Instead of injecting a signal, the CE block is connected to an electronic oscillator, which fulfills the Barkhausen Stability Criterion (BSC) to ensure that self-maintained and self-sustained oscillations are generated. The technique is known as Oscillation Based Test (OBT) [1]. Instead of measuring the changes between the output and input signal, the oscillation frequency and amplitude are acquired and, using the BSC, the parameters of the CE model used can be obtained on the fly. As can be seen, this technique is much more powerful than injecting a signal, since instead of obtaining the BI for a given frequency, the whole CE electrical model of the CE block is obtained. The CE model used is based on previous work, but some improvements are introduced to increase its accuracy. The data base for this work are real measurements made by the research group in CC assays with three different cell lines using an OBT circuit. From these data, the parameters of the CE model block are successfully obtained. The modeling technique is tested on some variations of the CE model, reaching better results by increasing its complexity, making the model closer to reality or introducing Fractional Oden (FO) elements. Data from real experiments, and the best variants of the electrical model are used to build a simulator of a CC assay experiment. The simulator calculates model parameters and cell concentration in real-time (without taking into account future measurements) using the minimization of a cost function (CF). The minimization of an appropriate CF ensures that the oscillation requirements are satisfied and that the obtained CE model parameter values are consistent with the theoretical values. The acquired results are very satisfactory since the simulation of a real-time experiment demonstrates that the technique of minimizing a CF can be used to obtain the cell concentration in real-time. As a result, cell concentration data are attained whose trend and values present a relatively low error when compared to the cell concentration achieved by traditional optical cell counting methods. Electrical simulations of an electronic circuit are very useful during the design and testing process prior to the build of the circuit. The model parameters obtained during the simulation of a CC assay experiment, in addition to showing the feasibility of the technique, can be used in electrical simulations of the OBT circuit. For future improvements of the OBT measurement circuit, which are discussed at the end of this dissertation, electrical simulations must be performed with realistic data to ensure that the measurement circuit will work robustly. To perform such simulations, a toolbox has been built in Matlab, which performs electrical simulations using Ngspice (open-source Spice simulator) in an efficient way. This toolbox is applied to the oscillator circuit simulation successfully, being able to perform multiple simulations, varying the CE model automatically, in an efficient way. In addition, it can be applied to any electronic circuit to launch electrical simulations from Matlab.
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