Limits...
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.


Error in reconstruction caused by large changes in conductivity as a function of frequency
© Copyright Policy - open-access
Related In: Results  -  Collection


getmorefigures.php?uid=PMC2211417&req=5

fig10: Error in reconstruction caused by large changes in conductivity as a function of frequency

Mentions: The simulation result depicted in Figure 10 is of a circular object with a radius of 10 mm at the center of a disk with a radius of 32.5 mm. The figure shows the RMS error as a function of the conductivity's dependence on frequency. The graph starts with 0% per kHz (no changes at all) and displays the results for changes of up to 3% per kHz. The relative errors are small and the image is reconstructed in a comprehensible manner up to changes of 1% per kHz. This is a large dispersion that is not common in most tissues. In this example, this dispersion demonstrates a successful reconstruction with a difference in conductivity of up to 15% across the frequency band. This demonstrates that it is possible to use much wider frequency bands and still obtain a good image with FDM EIT.


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

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

Error in reconstruction caused by large changes in conductivity as a function of frequency
© Copyright Policy - open-access
Related In: Results  -  Collection

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

fig10: Error in reconstruction caused by large changes in conductivity as a function of frequency
Mentions: The simulation result depicted in Figure 10 is of a circular object with a radius of 10 mm at the center of a disk with a radius of 32.5 mm. The figure shows the RMS error as a function of the conductivity's dependence on frequency. The graph starts with 0% per kHz (no changes at all) and displays the results for changes of up to 3% per kHz. The relative errors are small and the image is reconstructed in a comprehensible manner up to changes of 1% per kHz. This is a large dispersion that is not common in most tissues. In this example, this dispersion demonstrates a successful reconstruction with a difference in conductivity of up to 15% across the frequency band. This demonstrates that it is possible to use much wider frequency bands and still obtain a good image with FDM EIT.

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.