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Open AccessArticle

Data-Analytics Modeling of Electrical Impedance Measurements for Cell Culture Monitoring

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Departamento de Tecnología Electrónica, Escuela Técnica Superior de Ingeniería Informática, Universidad de Sevilla, Av. Reina Mercedes, SN, 41012 Sevilla, Spain
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Instituto de Microelectrónica de Sevilla, Universidad de Sevilla (IMSE-CNM-CSIC), Av. Américo Vespucio, 28, 41092 Sevilla, Spain
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R & D Department, Treelogic S.L. 28223 Pozuelo de Alarcón, Spain
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Departamento de Teoría de la Señal y Comunicaciones, Universidad Carlos III de Madrid, Av. De la Universidad 30, 28911 Leganés, Spain
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Departamento de Electrónica y Electromagnetismo, Facultad de Física, Universidad de Sevilla, Av. Reina Mercedes, SN, 41012 Sevilla, Spain
*
Author to whom correspondence should be addressed.
Sensors 2019, 19(21), 4639; https://doi.org/10.3390/s19214639
Received: 26 September 2019 / Revised: 18 October 2019 / Accepted: 23 October 2019 / Published: 25 October 2019
(This article belongs to the Special Issue Data Analysis for Smart Sensor Systems)
High-throughput data analysis challenges in laboratory automation and lab-on-a-chip devices’ applications are continuously increasing. In cell culture monitoring, specifically, the electrical cell-substrate impedance sensing technique (ECIS), has been extensively used for a wide variety of applications. One of the main drawbacks of ECIS is the need for implementing complex electrical models to decode the electrical performance of the full system composed by the electrodes, medium, and cells. In this work we present a new approach for the analysis of data and the prediction of a specific biological parameter, the fill-factor of a cell culture, based on a polynomial regression, data-analytic model. The method was successfully applied to a specific ECIS circuit and two different cell cultures, N2A (a mouse neuroblastoma cell line) and myoblasts. The data-analytic modeling approach can be used in the decoding of electrical impedance measurements of different cell lines, provided a representative volume of data from the cell culture growth is available, sorting out the difficulties traditionally found in the implementation of electrical models. This can be of particular importance for the design of control algorithms for cell cultures in tissue engineering protocols, and labs-on-a-chip and wearable devices applications. View Full-Text
Keywords: laboratory automation; cell culture monitoring; electrical impedance; data analytics modeling laboratory automation; cell culture monitoring; electrical impedance; data analytics modeling
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García, E.; Pérez, P.; Olmo, A.; Díaz, R.; Huertas, G.; Yúfera, A. Data-Analytics Modeling of Electrical Impedance Measurements for Cell Culture Monitoring. Sensors 2019, 19, 4639.

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