Noncontact active sensing for viscoelastic parameters of tissue with coupling effect

Area of Science:

• Biomechanics
• Biomaterials Science
• Soft Tissue Engineering

Background:

• Living soft tissues exhibit complex mechanical behaviors under external forces.
• Key characteristics include the coupling effect (deformation at remote areas) and direction-dependent response (loading vs. unloading phases).
• Accurate modeling of these properties is crucial for understanding tissue mechanics and developing effective treatments.

Purpose of the Study:

• To propose a novel single-layered 3D tissue model.
• To represent the inherent characteristics of soft tissues, specifically the coupling effect and direction-dependent response.
• To determine unknown viscoelastic parameters using an inverse problem approach.

Main Methods:

• Developed a single-layered 3D tissue model using a network of stiffness and damping parameters.
• Employed an inverse problem-solving technique to identify four unknown viscoelastic parameters.
• Validated the model through both computational simulations and experimental data.

Main Results:

• The proposed model effectively captures the coupling effect in soft tissues.
• The model accurately represents the direction-dependent response (loading vs. unloading phases).
• Both simulation and experimental results confirm the model's ability to describe inherent soft tissue characteristics.

Conclusions:

• The developed 3D soft tissue model provides a robust framework for analyzing complex viscoelastic behaviors.
• This model can be utilized in various applications, including surgical simulation, medical device design, and understanding disease progression.
• Further research can extend this model to multi-layered tissues and incorporate more complex biological factors.