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      Extracting Parasite Effects of Electrical Bioimpedance Measurements

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          Abstract

          The objective of this work is to develop a technique for filtering parasitic effects from the impedance spectra (IS) measured in biological material phantoms. IS data are contaminated with unexpected capacitive and inductive effects from cable, input/output amplifiers capacitances, electrode polarization, temperature and contact pressure when collecting data. It is proposed a model which contains an RLC-network in series with the Cole model (RSC), then called RLC-Cole. It was built four circuits composed by resistors, capacitors and inductors. An impedance analyzer (HF2IS) was used to perform the measurements in the frequency range of 1 to 3000 kHz. Data were fitted into the model and comparisons to the nominal values were made. In order to validate the proposed model, a gelatin phantom and a chicken breast muscle impedance spectra were also collected and analyzed. After filtering, Cole fitting was performed. Results showed a maximum root-mean-square error of 1% for the circuits, 2.63% for the gelatin phantom, whereas 2.01% for the chicken breast. The RLC-Cole model could significantly remove parasitic effects out of a tissue impedance spectrum measured by a 4-point electrode probe. This may be highly important in EIS systems whose objective is to discriminate a normal tissue from a cancerous one.

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          The concepts of bias, precision and accuracy, and their use in testing the performance of species richness estimators, with a literature review of estimator performance

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            Reflections on the history of electrochemical impedance spectroscopy

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              A review of electrical impedance techniques for breast cancer detection.

               Y. L. Zou,  Z Guo (2003)
              Some evidence has been found that malignant breast tumors have lower electrical impedance than surrounding normal tissues. Although the separation of malignant tumors from benign lesions based on impedance measurements needs further investigation, electrical impedance could be used as an indicator for breast cancer detection. In this paper, we provide a systematic technical review of the existing electrical impedance techniques proposed for breast cancer detection, with an emphasis on noninvasive impedance imaging techniques. The electrical impedance of human breast tissue is first introduced, with tabulation of previous in vitro impedance measurement results on cancerous and normal breast tissues, and a brief description on the limited in vivo impedance measurements completed with invasive, or noninvasive, non-imaging techniques. A detailed review on noninvasive impedance imaging techniques for breast cancer detection, such as electrical impedance tomography (EIT) and electrical impedance mapping (EIM), is then presented. We suggest that for better breast cancer detection, an invasive impedance technique may be enhanced by combination with other cancer indicators. 3D EIT should be improved through collective efforts. EIM using a pair of electrode arrays is a viable method with great potential. Magnetic induction tomography and other magnetic induction based impedance imaging for breast cancer detection are promising and merit further exploration as well.
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                Author and article information

                Journal
                J Electr Bioimpedance
                J Electr Bioimpedance
                joeb
                joeb
                Journal of Electrical Bioimpedance
                Sciendo
                1891-5469
                January 2018
                31 December 2018
                : 9
                : 1
                : 115-122
                Affiliations
                [1 ]Department of Electrical Engineering, University of Santa Catarina State , Joinville, Brazil
                Author notes
                Article
                joeb-2018-0016
                10.2478/joeb-2018-0016
                7852010
                © 2018 D. Dutra, P. Bertemes-Filho published by Sciendo

                This work is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 3.0 License.

                Page count
                Pages: 8
                Categories
                Research Articles

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