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Frequency-division multiplexing for electrical impedance tomography in biomedical applications.

Granot Y, Ivorra A, Rubinsky B - Int J Biomed Imaging (2007)

Bottom Line: This is achieved by injecting current through all of the current injecting electrodes simultaneously, and measuring all of the resulting voltages at once.Another significant issue arises when we are recording data in a dynamic environment where the properties change very fast.We discuss the FDM EIT method from the biomedical point of view and show results obtained with a simple experimental system.

View Article: PubMed Central - PubMed

Affiliation: School of Computer Science and Engineering, Hebrew University of Jerusalem, 78b Ross Building, Jerusalem 91904, Israel.

ABSTRACT
Electrical impedance tomography (EIT) produces an image of the electrical impedance distribution of tissues in the body, using electrodes that are placed on the periphery of the imaged area. These electrodes inject currents and measure voltages and from these data, the impedance can be computed. Traditional EIT systems usually inject current patterns in a serial manner which means that the impedance is computed from data collected at slightly different times. It is usually also a time-consuming process. In this paper, we propose a method for collecting data concurrently from all of the current patterns in biomedical applications of EIT. This is achieved by injecting current through all of the current injecting electrodes simultaneously, and measuring all of the resulting voltages at once. The signals from various current injecting electrodes are separated by injecting different frequencies through each electrode. This is called frequency-division multiplexing (FDM). At the voltage measurement electrodes, the voltage related to each current injecting electrode is isolated by using Fourier decomposition. In biomedical applications, using different frequencies has important implications due to dispersions as the tissue's electrical properties change with frequency. Another significant issue arises when we are recording data in a dynamic environment where the properties change very fast. This method allows simultaneous measurements of all the current patterns, which may be important in applications where the tissue changes occur in the same time scale as the measurement. We discuss the FDM EIT method from the biomedical point of view and show results obtained with a simple experimental system.

No MeSH data available.


Example of an inhomogeneity near any of the electrodes and its reconstruction. (a) The simulated inhomogeneity. (b) The reconstructed map. The scale shows the impedance in  cm.
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fig7: Example of an inhomogeneity near any of the electrodes and its reconstruction. (a) The simulated inhomogeneity. (b) The reconstructed map. The scale shows the impedance in  cm.

Mentions: Figure 7 depicts an example of a synthetic inhomogeneity that was positioned next to one of the electrodes and its reconstructed image. For each inhomogeneity, the injected currents were simulated and the resulting voltage measurements were computed. With the computed voltages as an input, the reconstruction process was run to obtain the estimated impedance inside the tank. These values were then compared to the true impedance with which we started and thus the error was obtained. We repeated the same process with the trigonometric current pattern [28] implemented using half of the electrodes for current injection and half for voltage measurement. In this current pattern, the electrodes inject a combination of sine and cosine functions at the same frequency and the process is repeated 16 times: each time changing the injected current in the electrodes. It is worthwhile noting that the trigonometric current pattern we have used does not have a particularly high current density near any of the current electrodes. Comparing the errors of the two patterns will allow us to determine whether the FDM current pattern has any particular regions of better or worse accuracy.


Frequency-division multiplexing for electrical impedance tomography in biomedical applications.

Granot Y, Ivorra A, Rubinsky B - Int J Biomed Imaging (2007)

Example of an inhomogeneity near any of the electrodes and its reconstruction. (a) The simulated inhomogeneity. (b) The reconstructed map. The scale shows the impedance in  cm.
© Copyright Policy - open-access
Related In: Results  -  Collection

Show All Figures
getmorefigures.php?uid=PMC2211417&req=5

fig7: Example of an inhomogeneity near any of the electrodes and its reconstruction. (a) The simulated inhomogeneity. (b) The reconstructed map. The scale shows the impedance in  cm.
Mentions: Figure 7 depicts an example of a synthetic inhomogeneity that was positioned next to one of the electrodes and its reconstructed image. For each inhomogeneity, the injected currents were simulated and the resulting voltage measurements were computed. With the computed voltages as an input, the reconstruction process was run to obtain the estimated impedance inside the tank. These values were then compared to the true impedance with which we started and thus the error was obtained. We repeated the same process with the trigonometric current pattern [28] implemented using half of the electrodes for current injection and half for voltage measurement. In this current pattern, the electrodes inject a combination of sine and cosine functions at the same frequency and the process is repeated 16 times: each time changing the injected current in the electrodes. It is worthwhile noting that the trigonometric current pattern we have used does not have a particularly high current density near any of the current electrodes. Comparing the errors of the two patterns will allow us to determine whether the FDM current pattern has any particular regions of better or worse accuracy.

Bottom Line: This is achieved by injecting current through all of the current injecting electrodes simultaneously, and measuring all of the resulting voltages at once.Another significant issue arises when we are recording data in a dynamic environment where the properties change very fast.We discuss the FDM EIT method from the biomedical point of view and show results obtained with a simple experimental system.

View Article: PubMed Central - PubMed

Affiliation: School of Computer Science and Engineering, Hebrew University of Jerusalem, 78b Ross Building, Jerusalem 91904, Israel.

ABSTRACT
Electrical impedance tomography (EIT) produces an image of the electrical impedance distribution of tissues in the body, using electrodes that are placed on the periphery of the imaged area. These electrodes inject currents and measure voltages and from these data, the impedance can be computed. Traditional EIT systems usually inject current patterns in a serial manner which means that the impedance is computed from data collected at slightly different times. It is usually also a time-consuming process. In this paper, we propose a method for collecting data concurrently from all of the current patterns in biomedical applications of EIT. This is achieved by injecting current through all of the current injecting electrodes simultaneously, and measuring all of the resulting voltages at once. The signals from various current injecting electrodes are separated by injecting different frequencies through each electrode. This is called frequency-division multiplexing (FDM). At the voltage measurement electrodes, the voltage related to each current injecting electrode is isolated by using Fourier decomposition. In biomedical applications, using different frequencies has important implications due to dispersions as the tissue's electrical properties change with frequency. Another significant issue arises when we are recording data in a dynamic environment where the properties change very fast. This method allows simultaneous measurements of all the current patterns, which may be important in applications where the tissue changes occur in the same time scale as the measurement. We discuss the FDM EIT method from the biomedical point of view and show results obtained with a simple experimental system.

No MeSH data available.