Simple empirical model for identifying rheological properties of soft biological tissues

Abstract

Understanding the rheological properties of soft biological tissue is a key issue for mechanical systems used in the health care field. We propose a simple empirical model using fractional dynamics and exponential nonlinearity (FDEN) to identify the rheological properties of soft biological tissue. The model is derived from detailed material measurements using samples isolated from porcine liver. We conducted dynamic viscoelastic and creep tests on liver samples using a plate-plate rheometer. The experimental results indicated that biological tissue has specific properties: (i) power law increase in the storage elastic modulus and the loss elastic modulus of the same slope; (ii) power law compliance (gain) decrease and constant phase delay in the frequency domain; (iii) power law dependence between time and strain relationships in the time domain; and (iv) linear dependence in the low strain range and exponential law dependence in the high strain range between stress-strain relationships. Our simple FDEN model uses only three dependent parameters and represents the specific properties of soft biological tissue.

Fractional viscoelastic models for power-law materials

“…To circumvent the above disadvantages inherent to springdashpot based approximations, empirical power-law expressions have been used as a simple way to capture experimental measurements. 29,32,33,98,99 These expressions are essentially a mathematical ansatz, formulated to capture the main qualitative features of the experimental data. The end result of this formulation is usually a single modulus of interest that may or may not be analytically converted into the other moduli, necessitating numerical analysis for the prediction of the material response to other external loading patterns.…”

Simulation study of two-dimensional viscoelastic imaging of soft tissues using the extended Kalman filter for tumor detection

“…Particle velocity in space, estimated along rays i = 2,60 (at SNR = 30 dB). The ideal particle velocity is v n in Equations (1) and (19), the noised particle velocity is y n in Equation (19), and the estimated particle velocity is b v n in Equation (22).…”

“…In this paper, we design a 2D CSM imaging method based on the EKF. Recently, Kobayashi et al 19 applied the EKF to identifying rheological properties of soft biological tissues. However, CSM imaging was not done in this study.…”

“…Noisy (y n in Equation(19)) and estimated (b v n in Equation (22)) particle velocities in time at point j = 10 of ray i = 60 (at SNR = 30 dB).…”

Experimental study of the optimum puncture pattern of robot-assisted needle insertion into hyperelastic materials

“…Study on interaction mechanics involving needle-tissue modeling, 20–23 puncture force, 7,21 needle deflection, 20 tissue deformation, 24 mechanical behavior of tissue, 25–27 and other aspects (e.g. force control algorithms) 28–30 has been the research focus in the field of robot-assisted insertion.…”