Power-Law Modeling for Swift Viscoelastic Assessment in Biological Soft Tissues

In addressing the viscoelastic behavior of biological soft tissues, the precise and expeditious measurement methodologies hold paramount significance, given the intrinsic softness and heightened aqueous content of such substrates. We have introduced an expeditious modality for the characterization of viscoelasticity in biological soft tissues, hinged upon a power-law model. This method has been rigorously validated through ramp–hold tests conducted on mechanically stable hydrogels. Notably, during the Ramp phase, the viscoelastic parameters of the material can be readily extracted. Furthermore, we applied unconfined compression stress-relaxation/creep tests with three different ramp–strain rates, namely [Formula: see text], on both white and gray matter to enable rapid quantification. The results indicate that the predicted curves during the Hold phase exhibit notable consistency with experimental data. Moreover, under quasi-static loading conditions, an increase in strain rate significantly enhances the predictive adaptability. Nonetheless, it is crucial to be mindful of the sensitivity to initial stress conditions. This study offers a promising avenue for the expeditious characterization of soft tissue viscoelasticity. It underscores the feasibility of mechanical characterization metrics from a phenomenological model for the assessment of physiological variations and pathological mechanisms in tissue states.

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Publication Details

Journal
International Journal of Applied Mechanics
Published
2024-09-13
DOI
https://doi.org/10.1142/s1758825124501072
Citations
2
Primary Topic
Elasticity and Material Modeling
Type
article
Field-Weighted Citation Impact
0.37

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article

Power-Law Modeling for Swift Viscoelastic Assessment in Biological Soft Tissues

Yubo Fan, Lizhen Wang, Kang Wei, Qiao Li et al.
2 citations
International Journal of Applied Mechanics
Elasticity and Material Modeling
0.37
article

Power-Law Modeling for Swift Viscoelastic Assessment in Biological Soft Tissues

Yubo Fan, Lizhen Wang, Kang Wei, Qiao Li, Yanfei Li
article en
2 citations

Abstract

In addressing the viscoelastic behavior of biological soft tissues, the precise and expeditious measurement methodologies hold paramount significance, given the intrinsic softness and heightened aqueous content of such substrates. We have introduced an expeditious modality for the characterization of viscoelasticity in biological soft tissues, hinged upon a power-law model. This method has been rigorously validated through ramp–hold tests conducted on mechanically stable hydrogels. Notably, during the Ramp phase, the viscoelastic parameters of the material can be readily extracted. Furthermore, we applied unconfined compression stress-relaxation/creep tests with three different ramp–strain rates, namely [Formula: see text], on both white and gray matter to enable rapid quantification. The results indicate that the predicted curves during the Hold phase exhibit notable consistency with experimental data. Moreover, under quasi-static loading conditions, an increase in strain rate significantly enhances the predictive adaptability. Nonetheless, it is crucial to be mindful of the sensitivity to initial stress conditions. This study offers a promising avenue for the expeditious characterization of soft tissue viscoelasticity. It underscores the feasibility of mechanical characterization metrics from a phenomenological model for the assessment of physiological variations and pathological mechanisms in tissue states.

International Journal of Applied MechanicsVol. 16(09)
Zhejiang International Studies University (CN), Beihang University (CN)
National Natural Science Foundation of China, China Scholarship Council, Higher Education Discipline Innovation Project, National Key Research and Development Program of China, Fundamental Research Funds for the Central Universities, Academic Excellence Foundation of BUAA for PHD Students
Peace, Justice and strong institutions
Openalex Percentile: Top 44%
Elasticity and Material Modeling
0.37
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