Published April 4, 2023 | Version v1
Dataset Open

Electrical Impedance Tomography (EIT) measurement monitoring the respiratory status

Authors/Creators

  • 1. Department of Anaesthesiology and Intensive Therapy, Kiskunhalas Semmelweis Hospital, Kiskunhalas, Hungary
  • 2. Department of Control Engineering and Information Technology, Faculty of Electrical Engineering and Informatics, Budapest University of Technology and Economics, Budapest, Hungary
  • 3. Institute of Technical Medicine (ITeM), Furtwangen University, Villingen-Schwenningen, Germany

Description

This dataset was used in a study titled "Structural priors represented by discrete cosine transform improve EIT functional imaging" which is currently pending publication. The dataset consists of Electrical Impedance Tomography (EIT) measurements that were collected during the monitoring of respiratory status in tested subjects. The data is stored as .get files, which can be imported into the Matlab® workspace using the codes provided on GitHub at https://github.com/rongqing-chen/DCT-EIT.

Using the dataset requires the citation of the following publication:

  • Lovas A, Chen R, Molnár T, Benyó B, Szlávecz Á, Hawchar F, et al. Differentiating Phenotypes of Coronavirus Disease-2019 Pneumonia by Electric Impedance Tomography. Frontiers in Medicine. 2022;9. doi: 10.3389/fmed.2022.747570
  • R. Chen, S. Krueger-Ziolek, A. Lovas, B. Benyó, S.J. Rupitsch, K. Moeller (2023) Structural priors represented by discrete cosine transform improve EIT functional imaging. PLoS ONE 18(5): e0285619. 10.1371/journal.pone.0285619

Files

Subjects Data.zip

Files (213.3 MB)

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