An Effective and Robust Parameter Estimation Method in a Self-Developed, Ultra-Low Frequency Impedance Spectroscopy Technique for Large Impedances

Author:

Kuljic Bojan1,Vizvari Zoltan234ORCID,Gyorfi Nina45,Klincsik Mihaly36,Sari Zoltan346,Kovacs Florian7ORCID,Juhos Katalin7,Szakall Tibor1,Odry Akos89ORCID,Kovacs Levente10ORCID,Tadic Vladimir3111213ORCID,Siljegovic Mirjana14,Odry Peter311ORCID,Kecskes Istvan11

Affiliation:

1. Depaertment of Informatics, Subotica Tech College of Applied Sciences, Marka Oreškoviċa 16, 24000 Subotica, Serbia

2. Department of Environmental Engineering, Faculty of Engineering and Information Technology, University of Pecs, Boszorkany Str. 2, H-7624 Pecs, Hungary

3. Symbolic Methods in Material Analysis and Tomography Research Group, Faculty of Engineering and Information Technology, University of Pecs, Boszorkany Str. 6, H-7624 Pecs, Hungary

4. Multidisciplinary Medical and Engineering Cellular Bioimpedance Research Group, Szentagothai Research Centre, University of Pecs, Ifjusag Str. 20, H-7624 Pecs, Hungary

5. Institute of Physiology, Medical School, University of Pecs, Szigeti Str. 12, H-7624 Pecs, Hungary

6. Department of Technical Informatics, Faculty of Engineering and Information Technology, University of Pecs, Boszorkany Str. 6, H-7624 Pecs, Hungary

7. Department of Agro-Environmental Studies, Hungarian University of Agriculture and Life Sciences, Villányi Str. 29-43, H-1118 Budapest, Hungary

8. Department of Mechatronics and Automation, Faculty of Engineering, University of Szeged, Moszkvai Krt. 9, H-6725 Szeged, Hungary

9. Department of Control Engineering and Information Technology, University of Dunaújváros, Táncsics Mihály u. 1, H-2400 Dunaújváros, Hungary

10. Physiological Controls Research Center, University Research and Innovation Center, Óbuda University, Becsi Str. 96/b, H-1034 Budapest, Hungary

11. Institute of Information Technology, University of Dunaujvaros, Tancsics M. Str. 1/A, H-2401 Dunaujvaros, Hungary

12. John von Neumann Faculty of Informatics, Óbuda University, Becsi Str. 96/B, H-1034 Budapest, Hungary

13. Department of Mechanical Engineering, Electrical Engineering and Computer Science, Technical College of Applied Sciences in Zrenjanin, Đorđa Stratimirovića 23, 23000 Zrenjanin, Serbia

14. Department of Physics, Faculty of Sciences, University of Novi Sad, Trg Dositeja Obradovića 4, 21000 Novi Sad, Serbia

Abstract

Bioimpedance spectrum (BIS) measurements are highly appreciated in in vivo studies. This non-destructive method, supported by simple and efficient instrumentation, is widely used in clinical applications. The multi-frequency approach allows for the efficient extraction of the most information from the measured data. However, low-frequency implementations are still unexploited in the development of the technique. A self-developed BIS measurement technology is considered the pioneering approach for low (<5 kHz) and ultra-low (<100 Hz) frequency range studies. In this paper, the robustness of ultra-low frequency measurements in the prototypes is examined using specially constructed physical models and a dedicated neural network-based software. The physical models were designed to model the dispersion mainly in the ultra-low frequency range. The first set of models was used in the training of the software environment, while the second set allowed a complete verification of the technology. Further, the Hilbert transformation was employed to adjust the imaginary components of complex signals and for phase determination. The findings showed that the prototypes are capable of efficient and robust data acquisition, regardless of the applied frequency range, minimizing the impact of measurement errors. Consequently, in in vivo applications, these prototypes minimize the variance of the measurement results, allowing the resulting BIS data to provide a maximum representation of biological phenomena.

Publisher

MDPI AG

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