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Development of an Electrical Impedance Tomography Algorithm to Estimate the Scalp and Skull Conductivity
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Resumo(s)
Electrical 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.
Descrição
Tese de mestrado, Engenharia Biomédica e Biofísica , 2022, Universidade de Lisboa, Faculdade de Ciências
Palavras-chave
Tomografia de impedância elétrica modelos computacionais da cabeça estimulação direta transcraniana condutividade standard algoritmo Teses de mestrado - 2023