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Systematic errors of EIT systems determined by easily-scalable resistive phantoms.
1Department of Anaesthesiological Research, University of Göttingen, Göttingen, Germany. ghahn@gwdg.de
Physiological Measurement
|June 12, 2008
Summary
We developed a simple resistive phantom method to identify systematic errors in electrical impedance tomography (EIT) systems. Systematic errors in EIT measurements often exceed noise, highlighting the need for improved accuracy in future system designs.
Area of Science:
- Biomedical Engineering
- Medical Imaging
Background:
- Electrical Impedance Tomography (EIT) systems are crucial for non-invasive monitoring.
- Accurate measurements in EIT are essential for reliable diagnostic and functional imaging.
- Systematic errors can significantly impact the precision of EIT-derived data.
Purpose of the Study:
- To present a straightforward method for quantifying systematic errors in EIT measurements.
- To evaluate the impact of various operational conditions and system parameters on measurement accuracy.
- To provide insights for improving the design of future EIT systems.
Main Methods:
- Utilized simple, scalable resistive phantoms with a 16-electrode adjacent drive pattern.
- Employed phantoms with constant output voltage and single-component trans-impedance, independent of electrode impedance.
- Investigated systematic errors by assessing crosstalk, channel accuracy, and signal-to-noise ratio on a Goe-MF II EIT system.
Main Results:
- Systematic measurement errors consistently surpassed stochastic noise levels in the tested EIT system.
- The Goe-MF II system was optimized for signal-to-noise ratio rather than absolute accuracy.
- Time difference imaging and functional EIT (f-EIT) showed reduced systematic errors compared to absolute EIT (a-EIT).
Conclusions:
- Systematic errors are a significant factor in EIT measurements, often overshadowing noise.
- Future EIT system design must prioritize the reduction of systematic errors for enhanced accuracy.
- The developed phantom method offers a valuable tool for characterizing and mitigating these errors.
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