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Sensitivity and packaging improvement of an LCP pressure sensor for intracranial pressure measurement via FEM simulation

International Journal of Electrical and Computer Engineering (IJECE) · Vol. 9 No. 5 (2019)

DOI
10.11591/ijece.v9i5.pp4044-4052
ISSN
2722-2578, 2088-8708
Published
2019-10-01
Publisher
Institute of Advanced Engineering and Science
License
creativecommons.org/licenses/by-sa/4.0

Abstract

A biocompatible liquid crystal polymer (LCP) pressure sensor is proposed for measuring intracranial pressure (ICP) in Traumatic Brain Injury (TBI) patients. Finite element method using COMSOL multiphysics is employed to study the mechanical behavior of the packaged LCP pressure sensor in order to optimize the sensor design. A 3D model of the 8x8x0.2 mm LCP pressure sensor is simulated to investigate the parameters that significantly influence the sensor characteristics under the uniform pressure range of 0 to 50 mmHg. The simulation results of the new design are compared to the experimental results from a previous design. The result shows that reducing the thickness of the sensing membrane can increase the sensitivity up to six times of that previously reported. An improvement of fabrication methodology is proposed to complete the LCP packaging.

Collaboration network of the authors

7 authors · 9 co-authorship links

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  • Mahidol University
  • Affiliation unknown
  • Different organisations
  • Same organisation
  • Affiliation unknown
  • Thicker line = more joint articles · bigger circle = more articles
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Co-authorOrganisationJoint articles
Sorayouth Chamnanvej M.DAffiliation unknown2
Branesh Madhavan PillaiMahidol University1
Chumpon WilasrusmeeMahidol University1
Sakol NakdhamabhornMahidol University1

Affiliations come from OpenAlex; journal OAI-PMH metadata carries none. Authors without an OpenAlex ID are matched by name, which can merge or split people.

This record comes from Crossref (what the publisher deposited), because the journal's own OAI-PMH endpoint could not be harvested.

Metadata source: Crossref API (cadangan, berdasarkan ISSN) https://api.crossref.org/journals/2088-8708/works, first harvested 27 Okt 2026, last seen 27 Okt 2026.
Metadata as oai_dc, converted from Crossref
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