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dc.contributor.authorGarcía, Elviraes_ES
dc.contributor.authorPérez, Pabloes_ES
dc.contributor.authorOlmo, Albertoes_ES
dc.contributor.authorDíaz, Robertoes_ES
dc.contributor.authorHuertas, Gloriaes_ES
dc.contributor.authorYúfera, A.es_ES
dc.date.accessioned2019-11-13T13:08:47Z-
dc.date.available2019-11-13T13:08:47Z-
dc.date.issued2019-
dc.identifier.citationSensors, 19, 4639 (2019)es_ES
dc.identifier.urihttp://hdl.handle.net/10261/194547-
dc.description.abstractHigh-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 di erent 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 di erent cell lines, provided a representative volume of data from the cell culture growth is available, sorting out the di culties 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 applicationses_ES
dc.language.isoenges_ES
dc.publisherMultidisciplinary Digital Publishing Institutees_ES
dc.relation.isversionofPublisher's versiones_ES
dc.rightsopenAccesses_ES
dc.subjectLaboratory automationes_ES
dc.subjectCell culturemonitoringes_ES
dc.subjectElectrical impedancees_ES
dc.subjectData analyticsmodelinges_ES
dc.titleArticle Data-Analytics Modeling of Electrical Impedance Measurements for Cell Culture Monitoringes_ES
dc.typeartículoes_ES
dc.identifier.doihttp://dx.doi.org/10.3390/s19214639-
dc.description.peerreviewedPeer reviewedes_ES
dc.relation.publisherversionhttp://dx.doi.org/10.3390/s19214639es_ES
dc.rights.licenseCreative Commons Attribution License (CC BY 4.0)es_ES
dc.relation.csices_ES
oprm.item.hasRevisionno ko 0 false*
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