Dual energy pulses for Electrical Impedance Spectroscopy with the stochastic Gabor function
Conference proceedings: ... Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Conference 08/2012; 2012:138-41. DOI: 10.1109/EMBC.2012.6345890
This paper introduces the stochastic Gabor function (SGF), an excitation waveform that can be used to design optimal excitation pulses for Electrical Impedance Spectroscopy (EIS) of the brain. The SGF is a Gaussian function modulated by uniformly distributed noise; it has wide frequency spectrum representation regardless of the stimuli pulse length. The SGF was studied in the time-frequency domain. As shown by frequency concentration measurements, the SGF is least compact in the sample frequency phase plane. Numerical results obtained by using a realistic human head model indicate that the SGF may allow for both shallow and deeper tissue penetration than is currently obtainable with conventional stimulus paradigms, potentially facilitating tissue subtraction assessment of parenchymal dielectric changes in frequency. This could be of value in advancing EIS of stroke and hemorrhage.
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ABSTRACT: This paper describes an improved Electrical Impedance Spectroscopy (EIS) stimulus paradigm, based on dual energy pulses using the Stochastic Gabor Function (SGF) that may more sensitively assess deep brain tissue impedance than current single pulse paradigms. The SGF is a uniformly distributed noise, modulated by a Gaussian envelop, with a wide frequency spectrum representation regardless of the stimuli energy, and is least compact in the sample frequency phase plane. Numerical results obtained using a realistic human head model confirms that two sequential SGF pulses at different energies can improve EIS depth sensitivity when used in a dual energy subtraction scheme. Specifically, although the two SGF pulses exhibit different tissue current distributions, they maintain the broadband sensing pulse characteristics needed to generate all the frequencies of interest. Moreover, finite difference time domain (FDTD) simulations show that this dual energy excitation scheme is capable of reducing the amplitude of weighted current densities surface directly underneath the electrodes by approximately 3 million times versus single stimulation pulses, while maintaining an acceptable tissue conductivity distribution at depth. This increased sensitivity for the detection of small, deep impedance changes might be of value in potential future EIS applications, such as the portable, point-of-care detection of deep brain hemorrhage or infarction.
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