A High Sensitivity Sensor for Reconstruction of Conductivity Distribution in Region of Interest

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The proceedings of the 16th Annual Conference of China Electrotechnical Society

Part of the book series: Lecture Notes in Electrical Engineering ((LNEE,volume 889))

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Abstract

Electrical impedance tomography (EIT) is potential in industrial and biomedical applications. It offers an alternative for visualizing conductivity distribution. However, due to soft-field effect of sensitive field and ill-posedness of reconstruction, it is rather difficult to obtain high imaging quality. Different from EIT with traditional uniform arrangement of electrodes, this work proposes a novel high sensitivity sensor with offset electrode arrangement. It is supposed to enhance sensitivity in region of interest of a head-shaped region. Sparse L1 regularization is introduced to address the ill-posed problem. Imaging of inclusions with high conductivity against background is simulated. Simultaneous imaging of inclusions with high conductivity and low conductivity is also performed. Compared with traditional uniform electrode arrangement, the results show that reconstruction quality is enhanced as sensitivity in ROI is improved under the offset arrangement of electrodes.

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Acknowledgement

This work is supported in part by National Natural Science Foundation of China under Grant 61903127 and 51837011, in part by Postdoctoral Research Foundation of China under Grant 2020M673664, and in part by Scientific and Technological Innovation Program for Universities in Henan Province of China under Grant 21HASTIT018.

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Correspondence to Yanyan Shi .

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Tian, Z., Shi, Y., Fu, F., Wu, Y., Gao, Z., Lou, Y. (2022). A High Sensitivity Sensor for Reconstruction of Conductivity Distribution in Region of Interest. In: Yang, Q., Liang, X., Li, Y., He, J. (eds) The proceedings of the 16th Annual Conference of China Electrotechnical Society. Lecture Notes in Electrical Engineering, vol 889. Springer, Singapore. https://doi.org/10.1007/978-981-19-1528-4_54

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  • DOI: https://doi.org/10.1007/978-981-19-1528-4_54

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  • Publisher Name: Springer, Singapore

  • Print ISBN: 978-981-19-1527-7

  • Online ISBN: 978-981-19-1528-4

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