Signal separation in electrical impedance tomography: Applying harmonic analysis on simulated voltage data

Erik Stein; Alberto Battistel; Rongqing Chen; Knut Möller

Proceedings on Automation in Medical Engineering
Vol. 2 No. 1 (2023): Proc AUTOMED

Measurement technology and diagnostics, ID 758

Signal separation in electrical impedance tomography: Applying harmonic analysis on simulated voltage data

Erik Stein (Institute of Technical Medicine (ITeM) - Furtwangen University), Alberto Battistel (Institute of Technical Medicine (ITeM) - Furtwangen University), Rongqing Chen (Institute of Technical Medicine (ITeM) - Furtwangen University), Knut Möller (Institute of Technical Medicine (ITeM) - Furtwangen University)

This work is licensed under a Creative Commons Attribution 4.0 International License.

Abstract

The separation of respiration and cardiac activity in electrical impedance tomography is commonly carried out after image reconstruction. We investigated whether the harmonic analysis approach is capable of separating respiration and cardiac activity based on raw voltage data. In other words, we separated the two signal components before image reconstruction and thus made the separation process independent of it. The harmonic analysis approach separated respiration and cardiac activity well when applied on the raw voltage data created from a simulation model. The mean absolute error and residuals were < 2.5e-3 and < 2e-2, respectively.

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