  Most calibration schemes for reflection-based tissue spectroscopy in the
mm-wave/THz-frequency range are based on homogenized, frequency-dependent
tissue models where macroscopic material parameters have either been determined
by measurement or calculated using effective material theory. However, as the
resolution of measurement at these frequencies captures the underlying
microstructure of the tissue, here we will investigate the validity limits of
such effective material models over a wide frequency range (10 MHz - 200 GHz) .
Embedded in a parameterizable virtual workbench, we implemented a numerical
homogenization method using a hierarchical multiscale approach to capture both
the dispersive and tensorial electromagnetic properties of the tissue, and
determined at which frequency this homogenized model deviated from a full-wave
electromagnetic reference model within the framework of a Monte Carlo analysis.
Simulations were carried out using a generic hypodermal tissue that emulated
the morphology of the microstructure. Results showed that the validity limit
occurred at surprisingly low frequencies and thus contradicted the traditional
usage of homogenized tissue models. The reasons for this are explained in
detail and thus it is shown how both the lower "allowed" and upper "forbidden"
frequency ranges can be used for frequency-selective
classification/identification of specific material and structural properties
employing a supervised machine-learning approach. Using the implemented
classifier, we developed a method to identify specific frequency bands in the
forbidden frequency range to optimize the reliability of material
classification.
