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Energy Efficiency in Measurement and Image Reconstruction Processes in Electrical Impedance Tomography

Author

Listed:
  • Barbara Stefaniak

    (Research & Development Centre Netrix S.A., 20-704 Lublin, Poland)

  • Tomasz Rymarczyk

    (Research & Development Centre Netrix S.A., 20-704 Lublin, Poland
    Institute of Computer Science and Innovative Technologies, WSEI University, 20-209 Lublin, Poland)

  • Dariusz Wójcik

    (Research & Development Centre Netrix S.A., 20-704 Lublin, Poland
    Institute of Computer Science and Innovative Technologies, WSEI University, 20-209 Lublin, Poland)

  • Marta Cholewa-Wiktor

    (Department of Management, Lublin University of Technology, 20-618 Lublin, Poland)

  • Tomasz Cieplak

    (Department of Management, Lublin University of Technology, 20-618 Lublin, Poland)

  • Zbigniew Orzeł

    (Institute of Computer Science and Innovative Technologies, WSEI University, 20-209 Lublin, Poland)

  • Janusz Gudowski

    (Institute of Computer Science and Innovative Technologies, WSEI University, 20-209 Lublin, Poland)

  • Ewa Golec

    (Institute of Computer Science and Innovative Technologies, WSEI University, 20-209 Lublin, Poland)

  • Michał Oleszek

    (Research & Development Centre Netrix S.A., 20-704 Lublin, Poland
    Institute of Computer Science and Innovative Technologies, WSEI University, 20-209 Lublin, Poland)

  • Marcin Kowalski

    (Institute of Computer Science and Innovative Technologies, WSEI University, 20-209 Lublin, Poland)

Abstract

This paper presents an energy optimization approach to applying electrical impedance tomography (EIT) for medical diagnostics, particularly in detecting lung diseases. The designed Lung Electrical Tomography System (LETS) incorporates 102 electrodes and advanced image reconstruction algorithms. Energy efficiency is achieved through the use of modern electronic components and high-efficiency DC/DC converters that reduce the size and weight of the device without the need for additional cooling. Special attention is given to minimizing energy consumption during electromagnetic measurements and data processing, significantly improving the system’s overall performance. Research studies confirm the device’s high energy efficiency while maintaining the accuracy of the classification of lung disease using the LightGBM algorithm. This solution enables long-term patient monitoring and precise diagnosis with reduced energy consumption, marking a key step towards sustainable medical diagnostics based on EIT technology.

Suggested Citation

  • Barbara Stefaniak & Tomasz Rymarczyk & Dariusz Wójcik & Marta Cholewa-Wiktor & Tomasz Cieplak & Zbigniew Orzeł & Janusz Gudowski & Ewa Golec & Michał Oleszek & Marcin Kowalski, 2024. "Energy Efficiency in Measurement and Image Reconstruction Processes in Electrical Impedance Tomography," Energies, MDPI, vol. 17(23), pages 1-15, November.
    • Handle: RePEc:gam:jeners:v:17:y:2024:i:23:p:5828-:d:1526151
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    References listed on IDEAS

    as
    1. Monika Kulisz & Grzegorz Kłosowski & Tomasz Rymarczyk & Jolanta Słoniec & Konrad Gauda & Wiktor Cwynar, 2024. "Optimizing the Neural Network Loss Function in Electrical Tomography to Increase Energy Efficiency in Industrial Reactors," Energies, MDPI, vol. 17(3), pages 1-17, January.
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