Please use this identifier to cite or link to this item: https://ir.swu.ac.th/jspui/handle/123456789/12607
ชื่อเรื่อง: A comparison of bound-constrained and positivity-constrained optimization method to estimate head tissue conductivities by scalp voltage information
ผู้แต่ง: Ouypornkochagorn T.
Khattiyawech C.
Keatsiritawon N.
วันที่เผยแพร่: 2019
บทคัดย่อ: Electrical Impedance Tomography (EIT) is a noninvasive method used to estimate the conductivity of head tissues. Estimation based on the unconstrained Gauss-Newton (GN) method is conventional, but it may result in negative-value or extraordinary high-value estimates, which are unexpected. In this study, the bound-constrained method and the positivity-constrained optimization method were investigated and compared to the unconstrained optimization method. A two-dimensional model was created for conductivity estimation containing five head tissues, i.e., the scalp, the skull, the cerebrospinal fluid (CSF), grey matter (GM), and white matter (WM). The results showed that the accuracy, the robustness, and the estimation convergence of the estimation of this approach were significantly improved by constraining. All unexpected values also disappeared. The investigation proved that very high sensitivity of the skull region caused the unexpected outcome of the unconstrained cases. This high sensitivity can be significantly reduced by constraining. However, a degree of estimation nonlinearity can be increased by constraining as well, causing some estimation accuracies in the case of the positivity-constrained optimization method to be poor. Therefore, it is recommended to use only the bound-constrained optimization method. © 2019 J.J. Strossmayer University of Osijek , Faculty of Electrical Engineering, Computer Science and Information Technology. All rights reserved.
URI: https://ir.swu.ac.th/jspui/handle/123456789/12607
https://www.scopus.com/inward/record.uri?eid=2-s2.0-85080097455&doi=10.32985%2fijeces.10.1.4&partnerID=40&md5=4dd5a3de5127ad4402ace3164a665c4a
ISSN: 18476996
Appears in Collections:Scopus 1983-2021

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