Please use this identifier to cite or link to this item: https://scidar.kg.ac.rs/handle/123456789/10895
Title: Smeared multiscale finite element model for electrophysiology and ionic transport in biological tissue
Authors: Kojić M.
Milosevic, Miljan
Dragojević Simić V.
Geroski V.
Ziemys, Arturas
Filipovic, Nenad
Ferrari M.
Journal: Computers in Biology and Medicine
Issue Date: 1-May-2019
Abstract: © 2019 Basic functions of living organisms are governed by the nervous system through bidirectional signals transmitted from the brain to neural networks. These signals are similar to electrical waves. In electrophysiology the goal is to study the electrical properties of biological cells and tissues, and the transmission of signals. From a physics perspective, there exists a field of electrical potential within the living body, the nervous system, extracellular space and cells. Electrophysiological problems can be investigated experimentally and also theoretically by developing appropriate mathematical or computational models. Due to the enormous complexity of biological systems, it would be almost impossible to establish a detailed computational model of the electrical field, even for only a single organ (e.g. heart), including the entirety of cells comprising the neural network. In order to make computational models feasible for practical applications, we here introduce the concept of smeared fields, which represents a generalization of the previously formulated multiscale smeared methodology for mass transport in blood vessels, lymph, and tissue. We demonstrate the accuracy of the smeared finite element computational models for the electric field in numerical examples. The electrical field is further coupled with ionic mass transport within tissue composed of interstitial spaces extracellularly and by cytoplasm and organelles intracellularly. The proposed methodology, which couples electrophysiology and molecular ionic transport, is applicable to a variety of biological systems.
URI: https://scidar.kg.ac.rs/handle/123456789/10895
Type: journal article
DOI: 10.1016/j.compbiomed.2019.03.023
ISSN: 00104825
SCOPUS: 85064435240
Appears in Collections:Faculty of Engineering, Kragujevac
Institute for Information Technologies, Kragujevac

Page views(s)

77

Downloads(s)

1

Files in This Item:
File Description SizeFormat 
PaperMissing.pdf
  Restricted Access
29.86 kBAdobe PDFThumbnail
View/Open


Items in SCIDAR are protected by copyright, with all rights reserved, unless otherwise indicated.