Optimal filtering of EIT data in spectral expansion analysis

The signal-to-noise rations for some EIT measurements are very low, and for in vivo EIT measurements these are dependent on the electrode positioning and the distance from the current drive. The effect of removing noisy measurements to produce higher-fidelity images was investigated for the case of gastric emptying data. A consequence of this filtering was the reduction in the size of the sensitivity matrix and its subsequent singular-value decomposition. Several different filters were tested and for each of these spectral expansion regularization filter was optimized using a chi 2 test. Filtering out the measurement made by the spinal electrode, where the spinal bone barrier lies directly in the current path to the stomach, produced improved images by reducing the artefact content in the spinal sector of the conductivity map. For stomach imaging little useful information is produced by the spinal electrode, and the benefits of filtering dominate. However artefact images may be generated. In contrast consistent small improvements were produced by filtering out some of the weakest signals.