Quasi-linear Viscoelastic Research Articles

Primary Creep Characterization in Porcine Lumbar Spine Subject to Repeated Loading.

Low back pain (LBP) is a common medical condition worldwide, though the etiology of injuries causing most LBP is unknown. Flexion and repeated compression increase lumbar injury risk, yet the complex viscoelastic behavior of the lumbar spine has not been characterized under this loading scheme. Characterizing the non-injurious primary creep behavior in the lumbar spine is necessary for understanding the biomechanical response preceding injury. Fifteen porcine lumbar spinal units were loaded in repeated flexion-compression with peak compressive stresses ranging from 1.41 to 4.68MPa. Applied loading simulated real loading exposures experienced by high-speed watercraft occupants. The strain response in the primary creep region was modeled for all tests using a generalized Kelvin-Voigt model. A quasilinear viscoelastic (QLV) approach was used to separate time-dependent (creep) and stress-dependent (elastic) responses. Optimizations between the models and experimental data determined creep time constants, creep coefficients, and elastic constants associated with this tissue under repeated flexion-compression loading. Average R2 for all fifteen models was 0.997. Creep time constants optimized across all fifteen models were 24s and 580s and contributed to 20 ± 3% and 30 ± 3% of the overall strain response, respectively. The non-transient behavior contributed to 50 ± 0% of the overall response. Elastic behavior for this porcine population had an average standard deviation of 24.5% strain across the applied stress range. The presented primary creep characterization provides the response precursor to injurious behavior in the lumbar spine. Results from this study can further inform lumbar injury prediction and kinematic models.

Single-cell mechanical characterization in constriction-based cytometry

Mechanical characterization of suspended cells by constriction-based microfluidic devices has currently various limitations related to the available analysis models. In this work, we propose a new methodology to analyze the experiments. This approach is based on numerical simulations to describe fluid forces and cell deformation and on an extension of the quasi-linear viscoelasticity theory developed by Fung. The cells are considered visco-hyperelastic, homogeneous, and isotropic. The approach allows for assessing the mechanical parameters of individual cells, which is not possible using previous approaches, notably increasing the power of the constriction-based microfluidic technique. A practical procedure to compute mechanical parameters is proposed and demonstrated by analyzing experiments with suspended cells. The methodology developed in this work provides a convenient tool to overcome critical limitations of the state of the art and to leverage the potential of these microfluidic devices.

Viscoelastic constitutive artificial neural networks (vCANNs) – A framework for data-driven anisotropic nonlinear finite viscoelasticity

The constitutive behavior of polymeric materials is often modeled by finite linear viscoelastic (FLV) or quasi-linear viscoelastic (QLV) models. These popular models are simplifications that typically cannot accurately capture the nonlinear viscoelastic behavior of materials. For example, the success of attempts to capture strain (rate)-dependent behavior has been limited so far. To overcome this problem, we introduce viscoelastic Constitutive Artificial Neural Networks (vCANNs), a novel physics-informed machine learning framework for anisotropic nonlinear viscoelasticity at finite strains. vCANNs rely on the concept of generalized Maxwell models enhanced with nonlinear strain (rate)-dependent properties represented by neural networks. The flexibility of vCANNs enables them to automatically identify accurate and sparse constitutive models of a broad range of materials. To test vCANNs, we trained them on stress-strain data from Polyvinyl Butyral, the electro-active polymers VHB 4910 and 4905, and a biological tissue, the rectus abdominis muscle. Different loading conditions were considered, including relaxation tests, cyclic tension-compression tests, and blast loads. We demonstrate that vCANNs can learn to capture the behavior of all these materials accurately and computationally efficiently without human guidance. Our source code is available at https://github.com/ConstitutiveANN/vCANN.

Investigating Viscoelastic Properties of Myofibrils Isolated From hiPSC-CMs Using Atomic Force Microscopy and Quasi-Linear Viscoelastic Model

Abstract Knowing the mechanical properties of cardiac myofibrils isolated from human induced pluripotent stem cell-derived cardiomyocytes (hiPSC-CMs) can provide valuable insight into the structure and function of the heart muscle. Previous studies focused mostly on studying myofibrillar stiffness using simplified elastic models. In this study, the mechanical properties of myofibrils isolated from hiPSC-CMs were measured using atomic force microscopy (AFM). The quasi-linear viscoelastic (QLV) model was used to interpret the elastic and viscous properties of myofibrils. Since there have been no previous studies on the viscoelastic properties of myofibrils extracted from hiPSC-CMs, myofibrils extracted from porcine left-ventricular (LV) tissue were used to compare and verify experimental processes and QLV model parameters. The elastic modulus of myofibrils extracted from porcine LV tissue was determined to be 8.82 ± 6.09 kPa which is consistent with previous studies which reported that porcine LV tissue is less stiff on average than mouse and rat cardiac myofibrils. The elastic modulus of myofibrils extracted from hiPSC-CMs was found to be 9.78 ± 5.80 kPa, which is consistent with the range of 5–20 kPa reported for myofibrils extracted from the adult human heart. We found that myofibrils isolated from hiPSC-CMs relax slower than myofibrils extracted from porcine LV tissue, particularly in the first 0.25 s after the peak stress in the stress relaxation test. These findings provide important insights into the mechanical behavior of hiPSC-CMs and have implications for the development of treatments for heart diseases.

A Novel Quasilinear Viscoelastic Model of the Bending of a Steerable Catheter

Abstract The present study proposes a novel model that establishes the relationship between the bending moment and the curvature of a steerable catheter. The catheters exhibit a nonlinear viscoelastic tendency, so the moment-curvature relationship is modeled as a bending of a quasi-linear viscoelastic (QLV) cantilever beam. Stress relaxation tests with multiple magnitudes are performed on a catheter, and the parameter tuning is carried out with the test results to find out the coefficients of the model. The form of the instantaneous moment response, which is an important term within the QLV equation, is selected as a logarithmic form by analyzing the test results. This differentiates the accuracy of the model from using the commonly used exponential form. The performance of the logarithmic QLV model is compared to the conventional models by checking the curvature range each model can cover with a certain accuracy. The covering range for elastic, linear viscoelastic, and exponential QLV models are 22.1%, 64.4%, and 55.5%, respectively, whereas the covering range of the logarithmic QLV model is 100%.

Automated model discovery for muscle using constitutive recurrent neural networks

The stiffness of soft biological tissues not only depends on the applied deformation, but also on the deformation rate. To model this type of behavior, traditional approaches select a specific time-dependent constitutive model and fit its parameters to experimental data. Instead, a new trend now suggests a machine-learning based approach that simultaneously discovers both the best model and best parameters to explain given data. Recent studies have shown that feed-forward constitutive neural networks can robustly discover constitutive models and parameters for hyperelastic materials. However, feed-forward architectures fail to capture the history dependence of viscoelastic soft tissues. Here we combine a feed-forward constitutive neural network for the hyperelastic response and a recurrent neural network for the viscous response inspired by the theory of quasi-linear viscoelasticity. Our novel rheologically-informed network architecture discovers the time-independent initial stress using the feed-forward network and the time-dependent relaxation using the recurrent network. We train and test our combined network using unconfined compression relaxation experiments of passive skeletal muscle and compare our discovered model to a neo Hookean standard linear solid, to an advanced mechanics-based model, and to a vanilla recurrent neural network with no mechanics knowledge. We demonstrate that, for limited experimental data, our new constitutive recurrent neural network discovers models and parameters that satisfy basic physical principles and generalize well to unseen data. We discover a Mooney–Rivlin type two-term initial stored energy function that is linear in the first invariant I1 and quadratic in the second invariant I2 with stiffness parameters of 0.60 kPa and 0.55 kPa. We also discover a Prony-series type relaxation function with time constants of 0.362s, 2.54s, and 52.0s with coefficients of 0.89, 0.05, and 0.03. Our newly discovered model outperforms both the neo Hookean standard linear solid and the vanilla recurrent neural network in terms of prediction accuracy on unseen data. Our results suggest that constitutive recurrent neural networks can autonomously discover both model and parameters that best explain experimental data of soft viscoelastic tissues. Our source code, data, and examples are available at https://github.com/LivingMatterLab.

Nonlinear time-dependent mechanical behavior of mammalian collagen fibrils.

The viscoelastic mechanical behavior of collagenous tissues has been studied extensively at the macroscale, yet a thorough quantitative understanding of the time-dependent mechanics of the basic building blocks of tissues, the collagen fibrils, is still missing. In order to address this knowledge gap, stress relaxation and creep tests at various stress (5-35 MPa) and strain (5-20%) levels were performed with individual collagen fibrils (average diameter of fully hydrated fibrils: 253±21 nm) in phosphate buffered saline (PBS). The experimental results showed that the time-dependent mechanical behavior of fully hydrated individual collagen fibrils reconstituted from Type I calf skin collagen, is described by strain-dependent stress relaxation and stress-dependent creep functions in both the heel-toe and the linear regimes of deformation in monotonic stress-strain curves. The adaptive quasilinear viscoelastic (QLV) model, originally developed to capture the nonlinear viscoelastic response of collagenous tissues, provided a very good description of the nonlinear stress relaxation and creep behavior of the collagen fibrils. On the other hand, the nonlinear superposition (NSP) model fitted well the creep but not the stress relaxation data. The time constants and rates extracted from the adaptive QLV and the NSP models, respectively, pointed to a faster rate for stress relaxation than creep. This nonlinear viscoelastic behavior of individual collagen fibrils agrees with prior studies of macroscale collagenous tissues, thus demonstrating consistent time-dependent behavior across length scales and tissue hierarchies. STATEMENT OF SIGNIFICANCE: Pure stress relaxation and creep experiments were conducted for the first time with fully hydrated individual collagen fibrils. It is shown that collagen nanofibrils have a nonlinear time-dependent behavior which agrees with prior studies on macroscale collagenous tissues, thus demonstrating consistent time-dependent behavior across length scales and tissue hierarchies. This new insight into the non-linear viscoelastic behavior of the building blocks of mammalian collagenous tissues may serve as the foundation for improved macroscale tissue models that capture the mechanical behavior across length scales.

Asymptotic Stability for a Quasilinear Viscoelastic Equation with Nonlinear Damping and Memory

Asymptotic Stability for a Quasilinear Viscoelastic Equation with Nonlinear Damping and Memory

Constituent-based quasi-linear viscoelasticity: a revised quasi-linear modelling framework to capture nonlinear viscoelasticity in arteries

Arteries exhibit fully nonlinear viscoelastic behaviours (i.e. both elastically and viscously nonlinear). While elastically nonlinear arterial models are well established, effective mathematical descriptions of nonlinear viscoelasticity are lacking. Quasi-linear viscoelasticity (QLV) offers a convenient way to mathematically describe viscoelasticity, but its viscous linearity assumption is unsuitable for whole-wall vascular applications. Conversely, application of fully nonlinear viscoelastic models, involving deformation-dependent viscous parameters, to experimental data is impractical and often reduces to identifying specific solutions for each tested loading condition. The present study aims to address this limitation: By applying QLV theory at the wall constituent rather than at the whole-wall level, the deformation-dependent relative contribution of the constituents allows to capture nonlinear viscoelasticity with a unique set of deformation-independent model parameters. Five murine common carotid arteries were subjected to a protocol of quasi-static and harmonic, pseudo-physiological biaxial loading conditions to characterise their viscoelastic behaviour. The arterial wall was modelled as a constrained mixture of an isotropic elastin matrix and four families of collagen fibres. Constituent-based QLV was implemented by assigning different relaxation functions to collagen- and elastin-borne parts of the wall stress. Nonlinearity in viscoelasticity was assessed via the pressure dependency of the dynamic-to-quasi-static stiffness ratio. The experimentally measured ratio increased with pressure, from 1.03 pm 0.03 (mean pm standard deviation) at 80–40 mmHg to 1.58 pm 0.22 at 160–120 mmHg. Constituent-based QLV captured well this trend by attributing the wall viscosity predominantly to collagen fibres, whose recruitment starts at physiological pressures. In conclusion, constituent-based QLV offers a practical and effective solution to model arterial viscoelasticity.

Growth mechanics of the viscoelastic membranes

Living membranes can grow as a response to their environment, and they are also known as viscoelastic materials. However, the growth phenomenon and the viscoelastic behavior of these membranes have been studied separately up to now. The main goal of this paper is to develop a general formulation that can account for growth and viscoelastic behaviors in membranes, simultaneously. Therefore, we propose a formulation for growing quasi-linear viscoelastic membranes. The growth model begins with a multiplicative decomposition of the gradient deformation tensor into elastic and growth tensor, where the growth of the membrane is considered as a single scalar-valued parameter. Furthermore, the quasi-linear viscoelasticity theory is utilized in the elastic configuration as additive decomposition of the second Piola–Kirchhoff stress tensor. To solve the evolution equations for both growth and quasi-linear viscoelastic relations, two implicit second order accuracy integration methods are employed. Moreover, strain-driven and stress-driven growth phenomena are accounted for based on a Total Lagrangian (TL) finite element formulation. The developed formulations can capture growth phenomena and viscoelastic properties of the membranes, individually, and it also enables to model co-existence of growth and viscoelasticity. Eventually, to evaluate the applicability of the developed formulation, several examples are investigated and compared to those available in the literature.

A Constitutive Model to Characterize In Vivo Human Palmar Tissue.

In vivo characteristics of palmar soft tissue can be used to improve the accuracy of human models to explore and simulate a range of contact scenarios. Tissue characteristics can help to assess injury prevention strategies and designing technologies that depend on quantified physical contacts such as prosthetics, wearables, and assistive devices. In this study, a simplified quasi-linear viscoelastic (QLV) model was developed to quantify large deformation, in vivo soft tissue relaxation characteristics of the palm. We conducted relaxation tests on 11 young adults (6 males, 5 females, 18 < age < 30, mean age: 25 ± 4 yr) and 9 older adults (6 males, 3 females, age > 50, mean age: 61.5 ± 11.5 yr) using a 3 mm indenter to a depth of 50% of each participant's soft tissue thickness. The relaxation parameters of the QLV model were found to differ with age and sex, emphasizing the importance of using targeted material models to represent palmar soft tissue mechanics. Older adults showed on average 2.3-fold longer relaxation time constant compared to younger adults. It took 1.2-fold longer for young males to reach equilibrium than for young females; however, young females had a higher level of relaxation (36%) than young males (33%). Differences in specific QLV model parameters, P1, P2, and α were also found between age and sex groups. QLV characteristics differentiated by age and sex, add biofidelity to computational models which can provide a better representation of the diversity of tissue properties in the population.

Strain-dependent stress relaxation behavior of healthy right ventricular free wall

The increasing evidence of stress-strain hysteresis in large animal or human myocardium calls for extensive characterizations of the passive viscoelastic behavior of the myocardium. Several recent studies have investigated and modeled the viscoelasticity of the left ventricle while the right ventricle (RV) viscoelasticity remains poorly understood. Our goal was to characterize the biaxial viscoelastic behavior of RV free wall (RVFW) using two modeling approaches. We applied both quasi-linear viscoelastic (QLV) and nonlinear viscoelastic (NLV) theories to experimental stress relaxation data from healthy adult ovine. A three-term Prony series relaxation function combined with an Ogden strain energy density function was used in the QLV modeling, while a power-law formulation was adopted in the NLV approach. The ovine RVFW exhibited an anisotropic and strain-dependent viscoelastic behavior relative to anatomical coordinates, and the NLV model showed a higher capacity in predicting strain-dependent stress relaxation than the QLV model. From the QLV fitting, the relaxation term associated with the largest time constant played the dominant role in the overall relaxation behavior at most strains from early to late diastole, whereas the term associated with the smallest time constant was pronounced only at low strains at early diastole. From the NLV fitting, the parameters showed a nonlinear dependence on the strain. Overall, our study characterized the anisotropic, nonlinear viscoelasticity to capture the elastic and viscous resistances of the RVFW during diastole. These findings deepen our understanding of RV myocardium dynamic mechanical properties. Statement of significanceAlthough significant progress has been made to understand the passive elastic behavior of the right ventricle free wall (RVFW), its viscoelastic behavior remains poorly understood. In this study, we originally applied both quasi-linear viscoelastic (QLV) and nonlinear viscoelastic (NLV) models to published experimental data from healthy ovine RVFW. Our results revealed an anisotropic and strain-dependent viscoelastic behavior of the RVFW. The parameters from the NLV fitting showed nonlinear relationships with the strain, and the NLV model showed a higher capacity in predicting strain-dependent stress relaxation than the QLV model. These findings characterize the anisotropic, nonlinear viscoelasticity of RVFW to fully capture the total (elastic and viscous) resistance that is critical to diastolic function.

Viscoelastic Characterization of a Thermoplastic Elastomer Processed through Material Extrusion.

Objective. We aim to characterize the viscoelastic behavior of Polyether-Block-Amide (PEBA 90A), provide reference values for the parameters of a constitutive model for the simulation of mechanical behaviors, and paying attention to the influence of the manufacturing conditions. Methods. Uniaxial relaxation tests of filaments of PEBA were used to determine the values of the parameters of a Prony series for a Quasi-Linear Visco-Elastic (QLVE) model. Additional, fast cyclic loading tests were used to corroborate the adequacy of the model under different test criteria in a second test situation. Results. The QLVE model predicts the results of the relaxation tests very accurately. In addition, the behavior inferred from this model fits very well with the measurements of fast cyclic loading tests. The viscoelastic behavior of PEBA under small strain polymer fits very well to a six-parameter QLVE model.

Frictional resistance model for a capsule and an intestine with different central axes based on the intestinal nonlinear constitutive relationship

A magnetically controlled capsule endoscopy has a broad application for the detection of gastrointestinal diseases. The frictional resistance between a capsule and an intestine will affect the position control of the capsule. A quasi-linear viscoelastic (QLV) model is developed to describe the biomechanics of small intestines of a rabbit under the finite deformation. When the capsule is moving inside the intestine whose centerline is deviated from that of the capsule, a frictional resistance prediction model is created based on the established intestinal constitutive relationship, and the model is further validated by the frictional resistance experiment for the capsules with different diameters in small intestines of a rabbit. The work can help to design and optimize the magnetically controlled capsule endoscope.

A comparative study of different tissue materials for bioprosthetic aortic valves using experimental assays and finite element analysis

Background and objectiveExtracting the mechanical behaviors of bioprosthetic aortic valve leaflets is necessary for the appropriate design and manufacture of the prosthetic valves. The goal of this study was to opt a proper tissue for the valve leaflets by comparing the mechanical properties of the equine, porcine, and donkey pericardia with those of the bovine pericardium and human aortic valve leaflets. MethodsAfter tissue fixation in glutaraldehyde, the mechanical behaviors of the pericardial tissues were experimentally evaluated through computational methods. The relaxation tests were performed along the tissue fiber direction. The Mooney-Rivlin model was utilized to describe the hyperelastic behavior of the tissues at the ramp portion. The viscous behaviors at the hold portion were extracted using the Fung quasi-linear viscoelastic (QLV) model. Furthermore, the extracted parameters were used in the modeling of the bovine, equine, porcine, and donkey pericardia through finite element analysis (FEA). ResultsBased on the results, relaxation percentages of the equine, donkey, and bovine pericardia were greater than that of the porcine pericardium and similar to the native human aortic valve leaflets. Indeed, the equine and donkey pericardia were found more viscous and less elastic than the porcine pericardium. Compared with the porcine pericardium, the mechanical properties of the equine and donkey pericardia were rather closer to those of the native human leaflets and bovine pericardium. The computational analysis demonstrated that the donkey pericardium is preferable over other types of pericardium due to the low stress on the leaflets during the systolic and diastolic phases and the large geometric orifice area (GOA). ConclusionThe donkey pericardium might be a good candidate valve leaflet material for bioprosthetic aortic valves.

Acoustoelastic analysis of soft viscoelastic solids with application to pre-stressed phononic crystals

The effective dynamic properties of specific periodic structures involving rubber-like materials can be adjusted by pre-strain, thus facilitating the design of custom acoustic filters. While nonlinear viscoelastic behaviour is one of the main features of soft solids, it has been rarely incorporated in the study of such phononic media. Here, we study the dynamic response of nonlinear viscoelastic solids within a ‘small-on-large’ acoustoelasticity framework, that is we consider the propagation of small amplitude waves superimposed on a large static deformation. Incompressible soft solids whose behaviour is described by the Fung–Simo quasi-linear viscoelasticity theory (QLV) are considered. We derive the incremental equations using stress-like memory variables governed by linear evolution equations. Thus, we show that wave dispersion follows a strain-dependent generalised Maxwell rheology. Illustrations cover the propagation of plane waves under homogeneous tensile strain in a QLV Mooney–Rivlin solid. The acoustoelasticity theory is then applied to phononic crystals involving a lattice of hollow cylinders, by making use of a dedicated perturbation approach. In particular, results highlight the influence of viscoelastic dissipation on the location of the first band gap. We show that dissipation shifts the band gap frequencies, simultaneously increasing the band gap width. These results are relevant to practical applications of soft viscoelastic solids subject to static pre-stress.

Shear shock formation in incompressible viscoelastic solids

Experiments have shown that shear waves induced in brain tissue can develop into shock waves, thus providing a possible explanation of deep traumatic brain injuries. Here, we study the formation of shock waves in soft viscoelastic solids subject to an imposed velocity at their boundary. We consider the plane shearing motion of a semi-infinite half-space, which corresponds to a spatially one-dimensional problem. Incompressible soft solids whose behaviour is described by the Fung–Simo quasi-linear viscoelasticity theory (QLV) are considered, where the elastic response is either exponential or polynomial of Mooney–Rivlin–Yeoh type. Waveform breaking can occur at the blow-up of acceleration waves, leading to one sufficient condition for the formation of shocks. A slow scale analysis based on a small amplitude parameter yields a damped Burgers-like equation, thus leading to another shock formation condition. Numerical experiments performed using a dedicated finite volume scheme show that these estimates have limited accuracy. Their validity is restricted in the elastic limit too, where exact shock formation conditions are known.

Quasi-linear viscoelastic behavior of fresh porcine ureter.

To evaluate the viscoelastic properties of the fresh porcine ureter. Prove the QLV theory can sufficiently model the stress relaxation function of porcine ureters, and determine the QLV model constants which may provide insight into the synthesis of ureteral scaffolds with biomimetic viscoelastic properties in tissue engineering. Hysteresis tests were applied to study the differences in dissipated energy ratio for each different strain group. In stress relaxation tests, samples were sub-grouped and quickly ramping up to 5%, 20%, and 30% strain in each group and gradually relaxed to a corresponding level. Bringingtogether the quasi-linear viscoelasticity (QLV) theory and stress relaxation function to determine the eight constants of the ureteral tissue, and fitting the raw data with the model via MATLAB. The hysteresis response measurement results revealed that the porcine ureter was a highly dissipative material and there were differences between toe and linear region in stress-stain curve. The stress relaxation results revealed ureters responded with time-dependent decay of stress. The eight constants of the ureteral QLV model were determined for three different strain groups, and we proved that the QLV model can sufficiently adapt the experimental data of the ureter stress relaxation. This study investigated the time-dependent properties of the porcine ureter, and demonstrated the QLV theory could be used to evaluate the viscoelastic properties of the porcine ureteral tissue.

Constituent-Based Quasi-Linear Viscoelasticity: A Revised Quasi-Linear Modelling Framework to Capture Non-Linear Viscoelasticity in Arteries

Constituent-Based Quasi-Linear Viscoelasticity: A Revised Quasi-Linear Modelling Framework to Capture Non-Linear Viscoelasticity in Arteries

Multidirectional mechanical properties and constitutive modeling of human adipose tissue under dynamic loading

The mechanical behavior of subcutaneous adipose tissue (SAT) affects the interaction between vehicle occupants and restraint systems in motor vehicle crashes (MVCs). To enhance future restraints, injury countermeasures, and other vehicle safety systems, computational simulations are often used to augment experiments because of their relative efficiency for parametric analysis. How well finite element human body models (FE-HBMs), which are often used in such simulations, predict human response has been limited by the absence of material models for human SAT that are applicable to the MVC environment. In this study, for the first time, dynamic multidirectional unconfined compression and simple shear loading tests were performed on human abdominal SAT specimens under conditions similar to MVCs. We also performed multiple ramp-hold tests to evaluate the quasilinear viscoelasticity (QLV) assumption and capture the stress relaxation behavior under both compression and shear. Our mechanical characterization was supplemented with scanning electron microscopy (SEM) performed in different orientations to investigate whether the macrostructural response can be related to the underlying microstructure. While the overall structure was shown to be visually different in different anatomical planes, a preferred orientation of any fibrous structures could not be identified. We showed that the nonlinear, viscoelastic, and direction-dependent responses under compression and shear tests could be captured by incorporating QLV in an Ogden-type hyperelastic model. Our comprehensive approach will lead to more accurate computational simulations and support the collective effort on the research of future occupant protection systems. Statement of significanceThere is an urgent need to characterize the mechanical behavior of human adipose tissue under multiple dynamic loading conditions, and to identify constitutive models that are able to capture the tissue response under these conditions. We performed the first series of experiments on human adipose tissue specimens to characterize the multi-directional compression and shear behavior at impact loading rates and obtained scanning electron microscope images to investigate whether the macrostructural response can be related to the underlying microstructure. The results showed that human adipose tissue is nonlinear, viscoelastic and direction dependent, and its mechanical response under compression and shear tests at different loading rates can be captured by incorporating quasi-linear viscoelasticity in an Ogden-type hyperelastic model.