Design and Implementation of a 16-Electrode Electrical Impedance Tomography Data Acquisition System for Medical Imaging

Authors

  • Aldo Nofrianto Politeknik Negeri Padang, Padang, Indonesia
  • Audy Politeknik Negeri Padang, Padang, Indonesia
  • Aditya Wardani Politeknik Negeri Padang, Padang, Indonesia

DOI:

https://doi.org/10.52435/complete.v6i2.752

Keywords:

EIT, data acquisition system, Current Injection, image reconstruction, medical imaging

Abstract

Electrical Impedance Tomography (EIT) is a non-invasive imaging modality that reconstructs the internal resistivity distribution of an object using electrical measurements acquired from boundary electrodes. This paper presents the design, implementation, and experimental validation of a 16-electrode EIT data acquisition system for medical imaging applications. The developed system consists of a signal generator, voltage-to-current converter (VCC), voltage measurement circuit, multiplexer/demultiplexer unit, microcontroller, and image reconstruction algorithm. Experimental evaluations were conducted to assess signal stability, current injection performance, and voltage measurement accuracy. The XR2206 signal generator produced stable output over a frequency range of 1 to 210 kHz with an output impedance of 0.0784 kohm. The LF412-based amplifier demonstrated linear operation up to 50 kHz, while the VCC generated stable injection currents ranging from 0.3 to 2 mA for load variations between 100 to 2000 ohms, with optimal stability at 10 kHz. Data acquisition was performed using the adjacent method on a 16-electrode phantom containing bovine bone as a resistive object. Image reconstruction using the iterative Newton-Raphson method with Tikhonov regularization successfully identified the position and boundaries of the object. The optimal imaging performance was achieved at an injection current of 0.3 mA and a frequency of 10 kHz. Overall, the system shows reliable imaging.

References

Y. Guo et al., “Electrical impedance tomography provides information of brain injury during total aortic arch replacement,” Scientific Reports, vol. 14, art. 14236, 2024. DOI: https://doi.org/10.1038/s41598-02465203-0

J. J. Wisse et al., “Electrical impedance tomography as a monitoring tool during weaning from mechanical ventilation,” Respiratory Research, vol. 25, art. 179, 2024. DOI: https://doi.org/10.1186/s12931-024-02801-6

A. Ramandha and Basari, “Performance optimization of electrode patterns in electrical impedance tomography,” Jurnal Informatika & Rekayasa Elektronik, vol. 7, no. 2, pp. 210–217, 2024. DOI: https://doi.org/10.36595/jire.v7i2.1224

R. Aisya et al., “Application of electrical impedance tomography for detecting biological tissue,”Indonesian Journal of Electronics, Electromedical Engineering, and Medical Informatics, vol. 7, no. 2, 2025. DOI: https://doi.org/10.35882/ijeeemi.v7i2.54

Z. Cui et al., “Technical principles and clinical applications of electrical impedance tomography in pulmonary monitoring,” Sensors, vol. 24, no. 14, art. 4539, 2024. DOI: https://doi.org/10.3390/s24144539

J. G. Webster, Electrical Impedance Tomography. Bristol, UK: Adam Hilger, 1990.

D. S. Holder, Electrical Impedance Tomography: Methods, History and Applications. London, UK: IOP Publishing, 2005.

B. H. Brown, “Electrical impedance tomography (EIT): A review,” Journal of Medical Engineering & Technology, vol. 27, no. 3, pp. 97–108, 2003. DOI: https://doi.org/10.1080/0309190021000059688

A. Hassan, M. A. Rahman, and S. Ibrahim, “Performance evaluation of excitation current and frequency selection in electrical impedance tomography systems,”IEEE Access, vol. 12, pp. 45621–45632, 2024. DOI: https://doi.org/10.1109/ACCESS.2024.3372196

M. Li, J. Sun, and X. Dong, “Improved image reconstruction in electrical impedance tomography using regularized Newton-based methods,” Measurement, vol. 223, art. 113825, 2024. DOI: https://doi.org/10.1016/j.measurement.2023.113825

Y. Wang, Z. Cui, X. Li, and H. Zhang, “Design and implementation of a multi-channel electrical impedance tomography system for biomedical applications,” Biomedical Signal Processing and Control, vol. 86, art. 105247, 2024. DOI: https://doi.org/10.1016/j.bspc.2023.105247

A. Adler and W. R. B. Lionheart, “Uses and abuses of EIDORS,” Physiological Measurement, vol. 27, no. 5, pp. S25–S42, 2006. DOI: https://doi.org/10.1088/0967-3334/27/5/S03

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Published

2025-12-31

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Section

Original Articles