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Development of an Electrical Impedance Tomography Algorithm to Estimate the Scalp and Skull Conductivity

datacite.subject.fosDepartamento de Físicapt_PT
dc.contributor.advisorAndrade, Alexandre da Rocha Freire de, 1971-
dc.contributor.advisorMercadal, Borja
dc.contributor.authorCamarate, Catarina Heleno
dc.date.accessioned2023-04-12T11:17:23Z
dc.date.available2023-04-12T11:17:23Z
dc.date.issued2023
dc.date.submitted2022
dc.descriptionTese de mestrado, Engenharia Biomédica e Biofísica , 2022, Universidade de Lisboa, Faculdade de Ciênciaspt_PT
dc.description.abstractElectrical impedance tomography (EIT) is a technique used to estimate the conductivity value of biological tissues. EIT comprises two parts: forward and inverse solver. The forward solver aims measuring the electric potential in the brain after applying constant current directly on the scalp by at least two electrodes. Then, the inverse solver uses those electric potential values to predict the conductivity of the brain tissues. The project described in this report aimed to evaluate the possibility of using an EIT algorithm to predict scalp and skull conductivities to generate more realist head models. These heads models are used to generate transcranial direct current stimulation (tDCS) electrode montages for patients with mental disorders. This project took place in Neuroelectrics, a company already with a pipeline able to generate these montages based on the anatomy of the patient but using standard conductivity values for brain tissues. After testing the EIT algorithm, the project also aimed to evaluate the impact of using standard head models or personalized ones not only with the anatomy of the patient but also with the correct values for conductivity brain tissues on the generation of tDCS electrode montages. In fact, the results of this study showed that changes in the conductivity values can have a huge impact in the electric field applied in the brain, which means that it is important to generate a montage that takes the correct values into account instead of standard ones. In more detail, after comparing the error obtained with montages generated by template head model used in Neuroelectrics and montages generated by EIT template developed in this project, it was possible to state that there was a reduction around 21% in the error of the average of the electric field applied in the brain and a reduction around 10% in the error of the focality of the stimulation.pt_PT
dc.identifier.tid203493508
dc.identifier.urihttp://hdl.handle.net/10451/57079
dc.language.isoengpt_PT
dc.subjectTomografia de impedância elétricapt_PT
dc.subjectmodelos computacionais da cabeçapt_PT
dc.subjectestimulação direta transcranianapt_PT
dc.subjectcondutividade standardpt_PT
dc.subjectalgoritmopt_PT
dc.subjectTeses de mestrado - 2023pt_PT
dc.titleDevelopment of an Electrical Impedance Tomography Algorithm to Estimate the Scalp and Skull Conductivitypt_PT
dc.typemaster thesis
dspace.entity.typePublication
rcaap.rightsopenAccesspt_PT
rcaap.typemasterThesispt_PT
thesis.degree.nameTese de mestrado em Engenharia Biomédica e Biofísicapt_PT

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