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 envelope, 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 confirm 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 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.