Yerworth, R;
Bayford, R;
(2013)
The effect of serial data collection on the accuracy of electrical impedance tomography images.
Physiological Measurement
, 34
(6)
pp. 659-669.
10.1088/0967-3334/34/6/659.
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Abstract
There has been a surge of interest in using electrical impedance tomography (EIT) for monitoring regional lung ventilation, however, EIT is an ill-conditioned problem, and errors/noise in the boundary voltages can have an undesirable effect on the quality of the final image. Most EIT systems in clinical usage use serial data collection hence data used to create a single image will have been collected at different times. This paper presents a study of the resulting image distortion, and proposes a method for correcting this lag in situations where the frame rate is insufficient to prevent significant image degradation. Significant correlation between the standard deviation of the time dependent reciprocity error and time delay dLe between the reciprocal electrode combinations was found for both adult and neonate data. This was reduced when the data was corrected for dLe. Original and corrected data was reconstructed with the GREIT algorithm and visible differences were found for the neonate data. Ideally EIT systems should be run at a frame rate of at least 50 times the frequency of the dominant and interesting physiological signals. Where this is not practical, the intra-frame system timings should be determined and lag corrected for.
Type: | Article |
---|---|
Title: | The effect of serial data collection on the accuracy of electrical impedance tomography images |
Location: | England |
Open access status: | An open access version is available from UCL Discovery |
DOI: | 10.1088/0967-3334/34/6/659 |
Publisher version: | http://dx.doi.org/10.1088/0967-3334/34/6/659 |
Language: | English |
Additional information: | Copyright © 2013 Institute of Physics and Engineering in Medicine. |
Keywords: | Adult, Computer Simulation, Data Collection, Electric Impedance, Electrodes, Female, Heart, Humans, Image Processing, Computer-Assisted, Infant, Newborn, Lung, Time Factors, Tomography |
UCL classification: | UCL UCL > Provost and Vice Provost Offices > UCL BEAMS UCL > Provost and Vice Provost Offices > UCL BEAMS > Faculty of Engineering Science UCL > Provost and Vice Provost Offices > UCL BEAMS > Faculty of Engineering Science > Dept of Med Phys and Biomedical Eng |
URI: | https://discovery-pp.ucl.ac.uk/id/eprint/1420583 |
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