Session: 05-01: Biosensing

Paper Number: 110811

110811 - Development of a Laser Vibrometer-Based Shear Wave Sensing System for Characterizing Mechanical Properties of Viscoelastic Materials 

Characterizing the mechanical properties of viscoelastic materials is critical for biomedical applications such as detecting breast cancers, skin diseases, myocardial diseases, and hepatic fibrosis. However, previous methods for determining the mechanical properties of viscoelastic materials lack the consideration of dispersion relations that are functions of materials properties and shear wave frequency.

This paper presents a novel method that fuses noncontact shear wave sensing and dispersion analysis for characterizing the mechanical properties of viscoelastic materials. To develop this method, on the one hand, we established a new shear wave sensing system, which used a piezoelectric stack (PZT stack) to generate shear waves and a laser Doppler vibrometer (LDV) integrated on a 3D robotic stage to acquire shear waves in a non-contact manner. By automatically moving the laser focus position and acquiring shear wave signals at multiple points in a point-by-point manner, our novel PZT stack-LDV system was able to acquire a time-space wavefield, i.e., a wave amplitude function versus time and position. The wavefield contains a wealth of information about the propagation of shear waves in viscoelastic materials. On the other hand, to analyze the acquired time-space wavefield and determine the material properties, we established an inverse method that fuses multidimensional Fourier transform and frequency-wavenumber dispersion curve regression. The multidimensional Fourier transform can change a time-space wavefield to a frequency-wavenumber spectrum that reveals the frequency-wavenumber components of the acquired shear waves. This spectrum is further compared to a series of theoretical dispersion curves derived based on the Kelvin-Voigt model, and then the theoretical curve that best matches the experimental spectrum is found through a regression process. The material properties corresponding to that best-matching curve are considered to be the properties measured by our method. For the proof of concept, we performed experiments by using our method to measure the material properties of a customized synthetic gelatin phantom (160x120x30 mm). We showed that our system could successfully generate shear waves by using a PZT stack with a 5-cycle 200 Hz sine excitation signal modulated by a Hanning window. We also showed that our LDV integrated on a 3D robotic stage could acquire a time-space wavefield of shear waves in a viscoelastic material. Moreover, using our wavefield analysis method, two material properties (shear elasticity and shear viscosity) and shear wave velocities at different frequencies were successfully determined. Compared to a benchmark method, the velocity determination error is less than 5%. This experimental study proves the feasibility of our PZT stack-LDV system for characterizing the mechanical properties of viscoelastic materials. We expect this research to lead to a noncontact and efficient method for characterizing soft materials and monitoring their property changes.

Presenting Author: Bowen Cai Mississippi State University

Presenting Author Biography: Bowen Cai is a doctoral student in Aerospace Engineering at the Mississippi State University studying under Dr. Zhenhua Tian. He is also a research assistant who works for the Advanced Composite Institute of MSU. His main research direction is acoustic nondestructive testing. He also studies the application of ultrasound and vibration in other directions (such as composites, biomaterials). Before becoming a doctoral student, Bowen Cai conducted research on vibration control and finite element analysis of materials. He holds an M.S. in Mechanical Engineering from the University of Dayton, a B.S. in Mechanical Engineering from Tianjin University of Technology.