Abstract
Imaging of electrical conductivity is a promising technique in biomedical field, which can reveal the impedance distribution within the region of interest. However, the contact measurement of traditional electrical impedance tomography (EIT) results in some challenging practical limitations on its applications. This paper introduces a novel capacitively coupled EIT to the biomaterial/biomedical field for resistivity imaging, and studies various aspects of this new contactless technique on practical applications. A 12-electrode experimental phantom is developed and the corresponding computational model is established to obtain the sensitivity matrix of the phantom. A hybrid image reconstruction method, which combines the Tikhonov regularization method and the simultaneous iterative reconstruction technique, is introduced to solve the inverse problem. In biomedical applications, the frequency-dependent conductivity aspect is very critical. Therefore, both the time-difference and frequency-difference imaging methods are investigated. A background calibration approach is proposed for the frequency-difference capacitively coupled EIT to overcome the frequency dependence of the background signal. Experiments were carried out with three kinds of biomaterials and three backgrounds with different conductivities. Results show the working principles and potential of the capacitively coupled EIT on biomaterial and biomedical applications.
Original language | English |
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Pages (from-to) | 27069-27079 |
Number of pages | 11 |
Journal | IEEE Access |
Volume | 6 |
DOIs | |
Publication status | Published - 16 May 2018 |
Keywords
- Electrical impedance tomography (EIT)
- biomaterial and biomedical application
- capacitively coupled EIT
- frequency-difference imaging
- time-difference imaging
ASJC Scopus subject areas
- General Computer Science
- General Materials Science
- General Engineering
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Manuchehr Soleimani
- Department of Electronic & Electrical Engineering - Professor
- Electronics Materials, Circuits & Systems Research Unit (EMaCS)
- Bath Institute for the Augmented Human
- Centre for Bioengineering & Biomedical Technologies (CBio)
- Centre for Digital, Manufacturing & Design (dMaDe)
Person: Research & Teaching, Core staff, Affiliate staff