On the viscoelastic characterization of thin tissues via surface-wave sensing

This paper establishes a theoretical and computational framework for the development of a novel piezoelectric sensor array for the monitoring of surficial tissue motion that can be used as a basis for the reconstruction of layered viscoelastic skin properties. This is accomplished by the scale reduction of the so-called Multi-channel Analysis of Surface Waves (MASW), a methodology that is successfully used in engineering geophysics for the seismic-wave reconstruction of vertical geological profiles. The utility of the new sensor, containing an array of hair-like PVDF sensors that are sensitive to surficial tissue motion, is enhanced through a systematic solid-fiber interaction analysis that furnishes integral information, cumulative over the length of each fiber, about the attenuation and dispersion of surface waves. On employing such a predictive model as a lynchpin of the full waveform back-analysis used to interpret electric charges generated by the fibers, the methodology allows for an effective reconstruction and viscoelastic characterization of cutaneous and subcutaneous tissue sublayers on a millimeter scale. The performance of the proposed sensor array and data interpretation framework is illustrated through numerical simulations, which point to the feasibility of cost-effective, in vivo mechanical characterization of skin sublayers.