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While soft robotics is an emerging frontier of the robotics field, accurate modeling of large deformations for soft hyperelastic materials remains a challenge. Herein, we build on the existing open-source Multiphysics Object Oriented Simulation Environment (MOOSE) to accurately model neo-Hookean hyperelastic materials under user-defined loads and large strains. Excellent agreement between the simulated and theoretical results is obtained for simple geometries. Next, we show that our application can accurately model and predict the response of a real soft pneumatic actuator. To conclude, we demonstrate that the open-source nature of our simulation environment enables direct control over simulation parameters, allowing users to tailor the accuracy, convergence, and speed of their simulations.

The present study, modeling the mechanical behavior of the bladder is very important and vital for clinical applications. All techniques do not easily success to assess the biomechanical alterations in bladder wall layers under various pressure loading conditions. In the finite element method, several hyperelastic theories are used for studying and modeling the urinary bladder extension during filling phase. All layers of the bladder have different mechanical features generate high extension when exposed to the various pressure loading. The present study computational analysis of bladder wall layers has comparable data for experimental analysis by ultrasound imaging: both shows that the study here provides further understanding of the changes in the thickness values that happen in bladder wall layers. Finite element method can be utilized as a predictive tool to determine the deformation of three layers. The detrusor muscle lessens to (1.619324) mm from (2.8) mm registering a 42.167% change in its thickness at 19kPa pressure loading. The thickness of mucosa layer lessens between (0.8-0.3) mm by 62.5% decreasing proportion. The serona layer lessens from 0.7 mm to 0.2554 mm by 63.51% decreasing proportion.

A number of pneumatic soft robots are made of hyperelastic silicone rubber. The dynamic modeling and control of the soft robot require the establishment of a constitutive model of the silicone rubber. The Neo-Hookean constitutive model was established according to the material properties of silicone rubber. In this study, using the optimization module of COMSOL Multiphysics, we fitted uniaxial and equibiaxial measured data against the Neo-Hookean constitutive model. We obtained the stretch-stress relationship of the silicone rubber material from the uniaxial tension test. For the uniaxial and equibiaxial measured data, different weights are assigned to improve fitting accuracy. For silicone rubber with a large range of stretch factor, the measured data are fitted piecewise against the Neo-Hookean model. The Neo-Hookean material model fits both test data quite well for the case of different weight and piecewise fitting for uniaxial and equibiaxial data set.

The virtual training system of vascular interventional surgery can improve the operation level of novice interventional surgeons and reduce the training cost. The deformation simulation of vascular tissue is the key part of the virtual training system for vascular interventional surgery. This paper presents a vascular tissue model based on nonlinear viscoelastic tensor-mass method (NVTMM), which can realize real-time visual feedback and haptic feedback. The hyperelastic model is used to simulate the nonlinear viscoelastic behavior of blood vessels. Meanwhile, the Euler's implicit integration scheme is used to make the simulation results more stable. In addition, a haptic force feedback device is introduced for the interaction between the vascular model and the virtual medical instrument, which improves the authenticity of the simulation. Finally, the real-time performance and accuracy of NVTMM, MSM and FEM are compared through experiments. The results show that NVTMM method has high real-time performance and can reflect the nonlinear viscoelastic behavior of blood vessels to a certain extent.

Recently, microneedle patches have been explored for extracting interstitial fluid with the goal of extracting temporally relevant, clinical-grade information for human health monitoring. As compared to traditional hypodermic needles, the sub-millimeter scale of microneedles allows for the creation of micropores providing access into human skin interstitial fluid while minimizing interactions with blood vessels and nerves, leading to painless insertion with little to no bleeding. An essential sub-component is the actuator, responsible for driving the microneedle into the skin with a precise force and velocity to ensure reliable insertion. Reliability, in this case, consists of two criteria: the ability of the microneedle to 1) penetrate the skin, and 2) withstand penetration forces without mechanical failure. Evaluation of these criteria requires a thorough understanding of the non-linear, time-dependent interactions between the microneedle and the skin during insertion, including rupture and tearing of the skin on the micron scale, and the resultant stresses on the microneedle. To this end, a comprehensive finite-element model was developed to simulate the microneedle insertion process. This analysis yielded a prediction of complete microneedle insertion without failure of the microneedle and an estimated insertion force of 0.055 N per microneedle, well within the capability of the actuator system considered. This insertion force was validated using experimental data obtained through microneedle insertion in whole skin samples. The model was then used to perform several parametric studies, yielding valuable insights for possible future design improvements.

Soft robots are known for their ability to comply and having superior extensibility. However, one of the limitations of most of these robots is that they can stand only a limited amount of load before buckling, and they feature a non-negligible initial height. Hybrid soft-rigid actuators seem to offer a trade-off between compliance and the amount of load they can withstand, but only a few simple models have been proposed to describe the behavior of these actuators. In this paper, we propose a design, model and experimental validation of a soft actuator based on stackable Hyperelastic Ballooning Membranes (HBMA). This actuator shows an extensibility higher than 179%, as well as an ability to stand more than 20 times its own weight at a pressure as low as 35 kPa. Two models, giving the dynamic behavior of the HBMA in terms of displacement and pressure, have been derived from different hyperelastic models (Neo-Hookean and Mooney-Rivlin) and compared in terms of accuracy and robustness. Finally, an example of a hybrid soft-rigid continuum ballooning robot built with HBMAs is presented and characterized experimentally.

Different changes such as developing benign and malignant lesions in tissues lead to specific variations in their macroscopic and microscopic structure, which are associated with the alteration of their mechanical properties. In the present study, the mechanical parameters of different breast tissue lesions were noninvasively estimated with high precision based on the displacement data by using the powerful neural network method in order to detect the type of tumor in the breast tissue. The displacement data of various breast tissues, as well as the corresponding mechanical properties were acquired to develop and train the neural network models. For simulating breast tissue behavior and extracting the relevant displacement data to train the neural networks, the finite element modeling was applied using Abaqus software. Ogden and Yeoh hyperelastic models which are precise for expressing the hyperelastic behavior of soft tissues, specifically the breast, were used to create the finite element model for tumor-containing breast tissue. With the aim of obtaining a robust neural network model, the displacement data extracted from the finite element model and white noise summated to simulate laboratory conditions while deriving tissue data from finite element model. As indicated by the results, the trained neural network models represent high precision and efficiency in appraising the mechanical parameters of various breast tissues according to the displacement data, which promises its use for carefully diagnosing the type of breast lesion.

Currently, the researches on flexible mechanical fingers are mainly focused on motor-driven rigid fingers and soft robotic gripper. Unlike previous research, we have designed a soft bionic finger that can actuate multiple finger joints independently, which is more like a human finger. In the future, the fingers will not only provide the function of the catch but also used for rehabilitation treatment for patients with hand disability. In this paper, firstly, on the basis of tensile test for superelastic materials, the hyperelastic constitutive model is determined. Through the comparison of three different chambers structural forms of soft actuators, the internal longitudinal section shape of the model was optimized and the optimization results show that the semicircular internal cavity has better performance. Meanwhile, the FEM analysis method is applied to establish the motion model of the soft actuator. Finally, compared to traditional bionic fingers, experiments have verified that Three-joint soft finger proposed in this paper has better flexibility.

In this communication, we analyze the compression behavior of typical silicone rubbers used in soft robotics applications at elevated temperatures. In particular, compression experiments according to ISO 7743 are performed with three mixing ratios (base polymer to curing agent) of Sylgard, Elastosil, and Ecoflex at 24 °C (room temperature), 30 °C, 40 °C, 50 °C, and 60 °C. Furthermore, typical hyperelastic material models are fitted to the measured stress-strain curves for room temperature. It is shown that the (third-order) Yeoh model shows the best overall fit, and the corresponding model parameters are stated.

Shear-wave elastography is a useful tool in imaging mechanical properties of soft-tissue. It has great potential to improve the predictive accuracy of preterm birth. This imaging modality, however, has high inter- and intra-observer variability. This is due its sensitivity to changes in pressure and the natural variation in elasticity across the cervix. The aim of this study is to use the artefacts caused by the pressure-dependent increase in shear-wave speed to derive fourth order hyperelastic elasticity tensor of the tissue. The method proposed is as follows: the strain-map of the tissue is extracted by tracking the deformation of the cervix in two raw B-mode images of the ultrasound. Each B-mode image is correlated to a shear-wave map acquired at the same pressure. The relation of the shear-wave speed to the strain is used to derive the parameters of the hyperelastic material model of cervical tissue. A continuous measure of the cervical elasticity parameters is taken. The maps of the parameters are then used to predict the delivery date. In this paper, this method is demonstrated through simulation in FEBio in preparation for a large-scale clinical study at the Royal Prince Alfred Hospital. In the simulation, a tissue of Mooney Rivilin hyperelastic material is indented from 0 mm to 6 mm using a model of the ultrasound probe. The maximum factor increase in shear modulus was 2.63 times which translates to 62 % increase in measured shear-wave speed. The function of the change in shear-wave speed is unique to the parameters of the model.

The intervertebral disc (IVD) plays an important role in the normal functioning of the spine and acts as an interface to hold the vertebra together. IVDs have been subjected to different tests to find out their mechanical models. Different species of animal models are used for in vivo and in vitro for spinal column researches. Many studies have found similarities between sheep and human spines in terms of anatomy and geometry. The study of biomechanical similarities is essential for the improvement of diseases and surgical techniques. Obtaining precise mechanical behavior of IVDs is great importance for researching. In this study we try to investigate the hyperelastic behavior of sheep intervertebral disc and also find the appropriate mathematical model for describing of that. In order to do this, after isolating intervertebral disc from sheep uniaxial compression tests with constant strain rate carried out and the achieved data were used to fitted by three conventional hyper-elastic models, i.e. Moony-Rivlin, Neo-Hookean and Yeoh to report the best hyperelastic model for IVD.

Due to momentous clinical applications, modeling soft tissues and studying their mechanical properties such as elasticity and hyperelasticity were highly highlighted during the last decade. Because of differences between the mechanical properties of normal and cancerous tissues, precise modeling of mechanical behavior of soft tissues and distinguishing the types of tissues based on their responses to applied stimulations would facilitate the diagnosis of cancerous tissues. The present study sought to noninvasively recognize the mechanical behavior of prostate tissue and its cancerous masses. In this regard, the mechanical parameters of cancerous tissues were accurately estimated using the potent neural network method based on the displacement data. The displacement data related to various tissues and corresponding mechanical properties are required for developing and training neural network models. The finite element modeling using Abaqus software was implemented to simulate prostate tissue behavior and extract the required data for training neural networks. The nonlinear tissue behavior should be considered in soft tissue modeling. For representing the hyperelastic behavior of soft tissues, Ogden and Yeoh models are accurate, which were utilized in the study to prepare the finite element model of prostate tissue containing tumor. In addition, white noise was added into the displacement data obtained by the finite element model for simulating laboratory conditions during extracting tissue data from the model in order to achieve robust neural network models. The results indicate high accuracy and efficiency of the trained neural network models in estimating the mechanical parameters of cancerous prostate tissues based on the displacement data, which is promising outcome for the exact diagnosis of cancerous tissues.

The recent development of Dielectric Elastomer Actuators (DEA) requires a new approach to the description of hyperelastic material when the architectures are more complex than a film of material. In this paper, we propose a new technique of identification of the model parameters based on the comparison between measurements and results from an analytical modelling for a cylindrical DEA. This method allows to obtain an accurate description of the behavior of the actuator compared to results obtained with hyperelastic parameters determined with a classic approach.

In this paper, a two-degree-of-freedom (DOF) anthropomorphic pneumatic flexible joint is designed by using a silicone based hyperelastic material. The flexible joint consists of three chambers, which are distributed at 120 degrees, and they are not connected with each other. The pneumatic flexible joint is controlled by inflating high pressure gas to its chambers. Bending properties and motion space of the pneumatic flexible joint is analysed. And the influence of the chambers’ sizes and intervals on the joint’s curvature and motion space is analyzed through a series of finite element models (FEMs). Finally, the design of the geometrical sizes of the pneumatic flexible joint is studied qualitatively. Finite element analysis (FEA), under gas pressure of 10 kPa, 15 kPa, 20 kPa and 25 kPa, respectively, showes that the designed structure could realize two-degree-offreedom motion of the pneumatic flexible joint, which makes up for the deficiency of traditional one-degree-of-freedom pneumatic flexible joints.

Soft pneumatic actuators grasping tasks is one of the essential rules in robot manipulation methods. The grasping forces can be adapted to handle delicate and hard objects without leaving any damages on the object surfaces. This paper investigates the influence of the inclination angle of the soft pneumatic actuator (SPA) on its gripping force at its end tip. A range of inclination angles for SPA is analyzed using Finite Element Analysis (FEA) to estimate the gripping force at the end tip regarding SPA inner faces pressure. FEA study is conducted based on Hyperelastic material modeling employing non-linear analysis. Experimental validation is performed for three different air pillow inclined angle of SPAs fabricated by Fused Deposition Modeling (FDM) 3D printing. Experimental and FEA simulated data are compared to each other. Finally, a regression-based mathematical model is developed to obtain a direct correlation between the SPAs gripping force behavior concerning the inclination angle and applied pressure based on FEA data.

Low dose computed tomography (LDCT) is the current gold-standard for lung cancer diagnosis. However, accuracy of diagnosis is limited by the radiologist's ability to discern cancerous from non-cancerous nodules. To assist with diagnoses, a 4D-CT lung elastography method is proposed to distinguish nodules based on tissue stiffness properties. The technique relies on a patient-specific inverse finite element (FE) model of the lung solved using an optimization algorithm. The FE model incorporates hyperelastic material properties for tumor and healthy regions and was deformed according to respiration physiology. The tumor hyperelastic parameters and trans-pulmonary pressure were estimated using an optimization algorithm that maximizes similarity between the actual and simulated tumor and lung image data. The proposed technique was evaluated using an in-silico study where the lung tumor elastic properties were assumed. Following that evaluation, the technique was applied to clinical 4D-CT data of two lung cancer patients. Results from the evaluation study show that the elastography technique recovered known tumor parameters with only 6% error. Tumor hyperelastic properties from the clinical data are also reported. Results from this proof of concept study demonstrate the ability to perform lung elastography with 4D-CT data alone. Advancements in the technique could lead to improved diagnoses and timely treatment of lung cancer.

Full-field deformation measurements are crucial as it offers detailed information to better understand both micro and macroscopic nature of material behavior. The practice of employing Digital Image Correlation (DIC) based measuring techniques in experiments has increased due to its ability to generate full-field deformation information with minimal effort. Even though DIC systems are commercially available, the affordability of those systems is questionable in local context due to high capital costs. Most of the past studies related to DIC were focused on testing concrete, masonry and metallic alloy specimens, and little effort has been made on materials with recoverable large elongations. This paper presents a 3D full-field deformation measuring system that has been developed with a special focus on hyperelastic materials. The proposed system requires two common digital cameras for image acquisition, as the depth information is of interest. Images are then processed using the MATLAB-based algorithm developed to produce the full-field deformation map. Hyperelastic specimens of two different thicknesses were tested over 70% strain and the accuracy of the strain measurement using the proposed system is validated against physical measurements. The results have shown that the strains can be captured to an accuracy greater than 90% using the proposed technique.

The focus of this paper is to study the reliability of a wearable electrocardiogram sensor leadset under tight bending conditions using numerical simulations and experiments. In these simulations, appropriate material models are selected and fitted for each material layer, including a hyperelastic model for TPU, an elastic-plastic model for PET, and linear elastic models for the silver ink, carbon ink, and dielectric layers. The results from the numerical simulations are compared and validated using an analytical model as well as experimental data. Recommendations are made for acceptable operating conditions of the leadset.

We have fabricated a composite optical fiber with hyperelastic silicone cladding and silica core, and demonstrated a simple and highly sensitive pressure sensor based on the light coupling between two such composite fibers twisted together. The hyperelastic silicone has very low Young's modulus which makes the fiber deformation easier even under small pressure and hence improves the light coupling and pressure sensitivity. Both simulation and experiment show that the light coupling based pressure sensor using the composite fibers is very sensitive to small pressure (e.g., several newtons) compared with those using conventional silica fibers and polymethyl methacrylate resin polymer fibers, which almost have no response to small pressure. With excellent sensitivity and fast response time ( $\ll 1\;{\rm{s}}$ ), both static and dynamic side pressure have been successfully detected. The sensing configuration is simple without any complicated structures and would be a cost-effective candidate for highly sensitive small pressure monitoring.

This paper presents the mathematical derivation and experimental validation of a computational model, which accurately predicts static, large-strain deformations of tendon driven non-slender soft-arm manipulators subjected to gravity. The large strain behaviors are captured by employing the Green-Lagrange strain and by deriving analytical expressions for the variation of the equivalent Young modulus of the structure due to the large strains. No simplifying assumptions are made regarding the curvature of the structure, the stretching or the compression. Furthermore the paper proposes an iterative method for numerically solving the resultant non-linear system of coupled differential equations and demonstrates a number of application scenarios. The model is experimentally validated using a set-up comprising one segment of tendon driven soft-arm, which integrates stretchable and compressible hyperelastic (rubber-type) materials into its non-homogeneous back bone structure.

Compared with conventional robots, soft structures such as living octopus arms and various soft-robot arms have more degrees of freedom (DOFs) and greater flexibility. Soft robot arms have a considerable range of applications. However, it is arduous to establish a mechanical model for them, because of the hyper-redundant DOFs, and the hyperelasticity and nonlinearity of the soft material. In this study, to investigate the deformation of soft octopus robot arms, the simplified closed-form analytical equations for the curvature and torsion were derived according to the Cosserat theory. A closed-form model for axial constriction was developed. The analytical equations were experimentally validated, and a dynamical simulation of the multi-flexible bodies was performed for a cable-driven soft-robot arm inspired by the octopus. The results show satisfactory accuracy.

Many materials like wood, biological tissue, composites or rock have anisotropic mechanical properties. They become increasingly important in modern material, earth, and life sciences. The stress-strain response of such materials can be characterized (to first-order) by the three-dimensional fourth-order stiffness tensor. There are different anisotropy classes, i.e. material symmetries, that differ in the number and orientation of symmetry planes characteristic of the material. A three-dimensional fourth-order stiffness tensor of a hyperelastic material has up to 21 independent coefficients representing both moduli and orientation information which challenges any visualization method. Therefore, we use a fourth-order tensor decomposition to compute the anisotropy classes and the position of the corresponding symmetry planes. To facilitate judgment of the significance of the amount of anisotropy, we construct an isotropic material. Based on these computations, we design a glyph that represents the stiffness tensor. We demonstrate our method in a finite deformation setting of an initially isotropic hyperelastic material of Ogden class which is often modeling biological tissue. Upon deformation, the stiffness tensor can evolve along with its symmetry creating an inhomogeneous, unsteady fourth-order tensor field in three dimensions.

Soft end-effectors have great potential on object manipulation. The top-down approach using origami spring structure to create robots is increasingly spreading, with capabilities of simplification and acceleration for the design and fabrication procedure at low cost. In this study, a synergy is achieved through combination of origami pattern with 3D-printed soft robotics. In this letter, we have developed a monolithic soft gripper which deforms based on the constrained configuration space induced by origami structure. A geometric design method is proposed to model the hyperelastic deformation of elastomer material and the trajectory of fingertips is iteratively computed with residuals in geometric objective as approximated deformation using Newton's minimization method. Two characteristic tests quantifying the gripping capability of the soft gripper and a grasping demonstration of daily objects are conducted to show its practical performance. The experimental results indicate the linear relationship between input and output variables with a scale factor of 3.79 on the displacement amplification, showing that the required control scheme could be simple. Besides, handling a range of target objects presents the versatility and universality of the manipulator in daily life.

Manual palpation for the detection of anomalies is not possible through the small incisions of Robotic Minimally Invasive Surgery. The proposed novel approach allows robotic palpation by deforming the tissue surface with an indenter and analyzing the corresponding induced surface shape for indications of the abnormalities underneath. Three-dimensional hyperelastic finite element models were used to simulate the tool-tissue interaction of a hemispherical indenter pushing downwards onto the tissue surface. Curve fitting methods were employed to characterize the indentation curve of the deformed surface of either normal or abnormal tissue with an empirical equation. By analyzing these equations, we developed volume-based and gradient-based methods to investigate how the tumor position affects the surface deformation behavior of the tissue.The results of the simulations indicate that there are obvious differences in the surface deformation between healthy and diseased tissue, due to the higher stiffness of the tumor. A significant advantage of the proposed method is that it greatly broadens the detection area by providing estimates on the direction and distance of the tumor from the surrounding area of the indentation site, compared with previous studies only predicting the presence of a tumor in the contact area.

Behaviour laws in biomechanics are highly non-linear and contain multiple material parameters that require identification. With a set of material parameters, one deformation field spectrum should be obtained. In order to investigate this, an example of a hyperelastic model for the intervertebral disc will be studied in the context of a uni-axial deformation test. Results show different solutions for deformation using the same set of material parameters. Moreover, results were dependant on optimization algorithms, genetic algorithms and gradient-based, that were employed.

Leakages not only add to the cost, they are also a great threat to the safety of men, machines and the environment as well. Seals and gaskets have evolved as a perfect solution to the problem of leakages. Amongst the various types of gaskets, hyperelastic gaskets have long maintained their dominance in the industrial as well as domestic appliances because of their characteristic advantages. Hyperelasticity is defined for ideally elastic materials by constitutive models where the relations of stress and strain are derived from the strain energy density function denoted by ‘W’ - a scalar-valued quantity that gives the relationship of a material’s strain energy density to its rate of deformation. The constitutive models that explain hyperelasticity, include older Neo-Hookean, Generalized Rivlin and Mooney-Rivlin models as well as Blatz-Ko, Ogden and Arruda-Boyce models. All these models are expressed through different interpretations of W . The selection of the model to be used amongst the mentioned constitutive models depends upon the types of materials and geometric and loading profiles for effective prediction of behavior and results. An effort has been made to present a comparative analysis of 16 hyperelastic models, which are different variants of Mooney Rivlin, Ogden, Blatz-Ko, Yeoh, Gent, Polynomial and Arruda Boyce models. In this study, the above-mentioned hyperelastic models are applied to examine the behavior of a neoprene gasket under uniaxial tensile loading. The study is concluded with determining a hyperelastic constitutive model that predicts with reasonable exactness and safety margin when less or no experimental data is available for the neoprene gasket.

Assessing elastic material properties from shear wave propagation following an acoustic radiation force impulse (ARFI) excitation is difficult in anisotropic materials because of the complex relations among the propagation direction, shear wave polarizations, and material symmetries. In this paper, we describe a method to calculate shear wave signals using Green’s tensor methods in an incompressible, hyperelastic material with uniaxial stretch. Phase and group velocities are determined for SH and SV propagation modes as a function of stretch by constructing the equation of motion from the Cauchy stress tensor determined from the strain energy density. The Green’s tensor is expressed as the sum of contributions from the SH and SV propagation modes with the SH contribution determined using a closed-form expression and the SV contribution determined by numerical integration. Results are presented for a Mooney-Rivlin material model with a tall Gaussian excitation similar to an ARFI excitation. For an experimental configuration with a tilted material symmetry axis, results show that shear wave signals exhibit complex structures such as shear splitting that are characteristic of both the SH and SV propagation modes.

Hyperelasticity plays a vital role in the advancement of the biological materials used in the medical science. The hyperelastic deformation sometimes leads to an unstable state, and this phenomenon is quite undesirable from a practical standpoint. At the unstable state, the deformation becomes highly nonuniform, and it may result a premature failure. In the present paper, we analyze the stability of a hyperelastic tube subjected to an internal pressure under large deformation. The deformation response of a hypere-lastic tube is formulated through a new strain energy density function. An existing energy density function is modified in line with the limiting chain extensibility models. The existence of the modified energy function at its minimum potential state is ensured followed by the principle of polyconvexity. Additionally, we also developed the limiting conditions on the material parameters for a hyperelastic tube under large deformation. The stability criteria of a hyperelastic tube is examined through the distribution curve of the inflation pressure versus volume expansion ratio with the variation of the material parameters. The present study may provide a valid reference to design a hyperelastic tube for its numerous engineering and medical field applications.

Nonlinear guided waves mixing technology gains an ascending attention in nondestructive testing field as its capability to resist measuring device nonlinearity. However, recent studies in this topic mainly focus on theoretical analysis. In this article, Lamb waves counter-propagating mixing is explored using a numerical simulation method. Two fundamental Lamb modes(S0 at 1.13 and S0 at 1.82MHz) are selected based on the internal resonance criteria. The mixing wave mode is S1 at 2.95 MHz. A local microdefect is simulated by employing hyperelastic material properties in some regions. Results show that there is a positive correlation of nonlinear acoustic parameter and material degradation level in mixing zone and there is no correlation between nonlinear acoustic parameter and material degradation in fundamental waves propagating routine, which indicate that mixing signal is sensitive to local material defects.

Tactile sensors are essential for robotic systems to safely and effectively interact with the environment and humans. In particular, tri-axis tactile sensors are crucial for dexterous robotic manipulations by providing shear force, slip, or contact angle information. The soft inductive tactile sensor (SITS) is a new type of tactile sensor that measures inductance variations caused by eddy-current effect. In this paper, we present a soft tri-axis tactile sensor using the configuration of four planar coils and a single conductive film with a hyperelastic material in between them. The working principle is explained and the design methods are outlined. A 3-D finite-element model was developed to characterize the tri-axis SITS and to optimize the target design through parameter study. Prototypes were fabricated, characterized, and calibrated, and a force measurement resolution of 0.3 mN is achieved in each axis. Demonstrations show that the sensor can clearly measure light touch (a few mN normal force) and shear force pulses (10–30 mN) produced by a serrated leaf when it is moved across the sensor surface. The presented sensor is low cost, high performance, robust, durable, and easily customizable for a variety of robotic and healthcare applications.

Unlike traditional rigid robots, soft robots can deform in a wide range to suit environment and contact compliantly with operating objects. Therefore, soft robots have wide potential application prospects in terms of physical rehabilitation, minimally invasive surgery and other fields. In this paper, we present an omni-directional flexural inflatable flexible arm model, which consists of three independent controllable pneumatic components. The components have different elongations under the effect of pressure and flexible arm is bending deformation. Under ideal conditions, it can be achieved 90° bending and 360° twisting. Based on the Yeoh model of hyperelastic rubber material and the geometric analysis method, we present the mathematical model of the flexible arm and FEM capabilities. We use finite element analysis to simulate the actuation characteristics of these modules. We compared the analytical and computational results to experimental results and can be used for the future design and control of soft robotic actuators.

Due to microstructural damages in composite structures, for example caused by cyclic loads, material degradation may occur, changing material properties. Over time these damages are likely to accumulate and can lead to an abrupt structural failure. Therefore, it is necessary to investigate or detect material degradation as a result of cyclic loading at an early stage. For this purpose, the generation of so-called cumulative second harmonic modes [1] is employed. In this work the authors will deal with numerical simulation of Lamb-wave propagation in symmetric cross-ply laminates (CPL). Based on existing work in this area for isotropic and unidirectional materials [2], the numerical investigation is extended to CPL. The aspects of material stability as well as of conditions of existence regarding cumulative second harmonic generation in CPL will be discussed.

Soft actuators are ideal candidates for wearable biomedical devices, their inherent compliance, robustness, lightweight and the possibility to be washable take advantage over rigid actuators. Thus, a soft pneumatic fabric-polymer bending actuator as a base component for a robotic device for lymphedema treatment is reported in this work. The actuator is composed of two mechanical elements, one made of fabric and the other one made of a hyperelastic polymer which is stuck on the fabric element. The fabric element is designed and fabricated with a curved shape longer than the polymer element, that is a hyperelastic beam. To assemble both elements, the fabric element was folded before sticking in order to match the length of the polymer beam. Once the air is pumped into the fabric, it bends towards its original curved shape. Once the air is removed, the hyperelastic beam allows the actuator to recover its initial position. This actuator is capable of exerting compression and lateral force on a human arm mimicking manual lymphatic drainage. A mathematical model is presented which is in good agreement with the experimental data, it could serve to predict the actuator motion. An end-tip free bending displacement of about 2.2 cm and a bending force of about 0.35 N were achieved at 12.5 kPa. A proof-of-concept system for lymphedema treatment is presented as well.

Common mechanical actuators are composed of rigid parts, and cannot adapt to unstructured environment. Water hydraulic flexible manipulator is made of soft materials. It has a good flexibility and green feature, which is suitable in a small and complex environment. The most typical manipulator is composed of contractive braided artificial muscles. Another type of manipulator is composed of elongate spring-wrapped artificial muscles. The comparative study of them has rarely been discussed before, In order to design a more flexible and manageable manipulator, the two kinds of manipulators are designed in this paper. The mathematical models of them are established, and the hyperelasticity simulation are performed. Then the manipulators are experimented underwater to analyze their load capacities and work spaces. The results show the different advantages of them in dynamic process.

To achieve better interactivity in virtual surgery system, based on the exposure of surgery view using retractors, which is the basic surgery operation, study in the interaction technology in virtual surgery was carried out. In this paper, we presented a solution to solve the problem that the current methods cannot achieve good accuracy in location and high quality in visual feedback while satisfying the refresh rate. We chose handle to be the interactive equipment, the combination of inertial sensor location method and laser positioning method was applied to spatial location of handle, which can not only guarantee the accuracy, but also make the final output data smoother and the update rate soars. Visual feedback is the main function in the human body model interaction, we proposed an improved Mass Spring Damper model, which includes both surface grid and skeleton grid, and in addition connects particles on the surface grid and internal skeleton grid through the spring, to effectively support the mesh surface and prevent hyperelastic deformation. Finally, experiments were conducted and results show that the methods above achieve higher accuracy and efficiency in interaction.

Single cell microinjection is widely used in biological sciences, especially in genetic engineering and cytopathology. To investigate mechanical responses of the adherent cell in microinjection, a general geometrical description of adherent cells in microinjection is proposed. Based on finite strain theory in isotropic hyperelasticity and minimal potential energy principle, a hyperelastic model of the adherent cell is developed. Factors affecting the interaction force and the stress distribution in the adherent cell penetration are revealed and analyzed. The force-deformation relationship obtained in the proposed model shows high similarity with classical Hertz model, while more detailed mechanical behaviours of the adherent cell in microinjection can be discovered from the proposed model.

Pneumatic artificial muscles (PAMs) are frequently used actuators in soft robotics due to their structural flexibility. They are generally characterized by the tensile force due to the axial contraction and the radial force with volume expansion. To date, most applications of P AMs have utilized axial contractions. In contrast, we propose a novel way to control radial expansions of particular P AMs using anisotropic behaviors. P AMs generally consist of a cylindrical rubber bladder that expands with injection of air and multiple flexible but inextensible strings or mesh that surround the bladder to generate axial contraction force. We propose methods of generating radial expansion force in two ways. One is to control the spatial density of the strings that hold the bladder, and the other is to give asymmetric patterns directly to the bladder for geometrical anisotropy. To evaluate the performance of the actuators, soft sensors made of a hyperelastic material and a liquid conductor were attached to the P AMs for measuring local strains and pressures of the PAMs. We also suggest use of the proposed PAMs to a wearable therapeutic device for treating text neck symptoms as an application. The P AMs were used to exert a pressure to the back of the neck to recover the original spinal alignment from the deformed shape.

In this work we introduce a variational registration model admitting large deformations. The regularizer is described by the energy function of the Saint Venant-Kirchhoff material which is known to be isotropic, homogeneous and hyperelastic. The additional term controls the change of the areas and the change of the volumes. We compute the polyconvex envelope of the resulted energy, derive a relaxed problem associated to the original one and prove the existence of minimizers and Γ-convergence of the relaxed problem.

A FEM simulation of AFM indentation of soft biomaterials was made in ANSYS based on five-parameter hyperelastic Mooney Rivlin model. The simulation result shows that: The finite thickness film behavior is stiffer than the thicker film at larger indentations.

Continuum manipulators can exhibit behaviors similar to snakes, elephant's trunks, and octopus tentacles, which possess incredible dexterity and intrinsic compliance for safe interaction with unstructured environments. However, the lack of enough stiffness limits their scope and application. In this paper, we introduce four different structures of continuum manipulators, including a simple structure with three elastic actuated rods, a structure with a passive rigid kinematic chain, a structure with a hyperelastic notochord and a segmental structure inspired from the spine without articular structure. This paper presents an experimental comparison of four continuum manipulators and aims to explore approaches to enhance the stiffness of a continuum manipulator and maintain the simple constant curvature kinematics as far as possible simultaneously. Results of this paper contribute to guiding the design of a continuum manipulator for achieving desired stiffness properties.

With the purpose of accurate detection and classification of various pathologies in soft tissues in a noninvasive way, a variety of elastography techniques has been introduced in the last two decades. The linear and nonlinear constitutive models of soft tissues have been exploited in several elastography techniques. In this paper, we discuss a technique for estimating the mechanical properties of soft tissue, which uses the nonlinear hyperelastic constitutive model as the basis. The limitations of detecting tumors on the basis of the linear constitutive model, that some of them have been mentioned in this paper, impel us to employ the hyperelastic model as a more realistic strategy for detecting lesions in the soft tissue. The estimated hyperelastic parameters of the polynomial model for a simulated phantom are presented in this paper, which have been obtained by utilizing appropriate regularization methods and considering proper regularization parameter, initial condition and hypothetical hyperelastic parameters. The hyperelastic parameters have been estimated after simulating the response of the phantom to the compression and computing some mechanical variables such as the displacement for the phantom. The propounded explanations and results indicate that the determination of hyperelastic parameters of soft tissues could culminate in the superior detection of their lesions.

This paper describes the design and manufacturing of soft artificial skin with an array of embedded soft strain sensors for detecting various hand gestures by measuring joint motions of five fingers. The proposed skin was made of a hyperelastic elastomer material with embedded microchannels filled with two different liquid conductors, an ionic liquid and a liquid metal. The ionic liquid microchannels were used to detect the mechanical strain changes of the sensing material, and the liquid metal microchannels were used as flexible and stretchable electrical wires for connecting the sensors to an external control circuit. The two heterogeneous liquid conductors were electrically interfaced through flexible conductive threads to prevent the two liquid from being intermixed. The skin device was connected to a computer through a microcontroller instrumentation circuit for reconstructing the 3-D hand motions graphically. The paper also presents preliminary calibration and experimental results.

In skin research area particularly on the development of skin substitutes or synthetic skin, the determination of the mechanical properties of skin and hyperelastic materials has always been challenging but yet interesting to be explored. To date there is no appropriate model ideally used to denote the skin. Known as a potential skin substitute material, Silicone rubber behaviour is also difficult to characterise. Therefore, this study for the first time attempts to assess the deformation behaviour of silicone rubber materials via the experimental approach, along with modelling and computation adapting hyperelastic constitutive model (i.e. neo-Hookean). Initially, uniaxial tensile test is performed to measure the stress-stretch response silicone rubber based materials employing ASTM D412 testing standards. All samples behave in a similar way and this data is acceptable as it possesses a slight percentage of variance which is less than 5% showing the consistency of the experiment performed. Neo- Hookean hyperelastic constitutive equation has been adopted to represent the materials behaviour in terms of materials constant. The experimental stress-stretch data were used as an input in order to analytically compute the materials constant of silicone rubber. Engineering stress-stretch (sE -- ?) curve plot from analytical results has been fitted to the experimental data curve plot. Results indicate that the neo-Hookean model is capable to provide reliable data in describing the deformation behaviour of Silicone Rubber based materials. The neo- Hookean material constant (C1) value is found to be 1.3078 MPa. Therefore it can be concluded that neo-Hookean constitutive model is suitable in representing the deformation behaviour of silicone rubber materials. Also the current study has contributed significantly to the knowledge of potential skin substitute materials especially for silicone rubber materials in modelling and computing its deformation behaviour.

Simulation of human heart mitral valves is a challenging biomechanical problem due to its complex anatomical structure, material properties and time dependent loading conditions. This study presents a modeling and simulation of human mitral valve behavior considering the effects of material nonlinearity and Chordae tendineae rupture via a numerical analysis. Three-dimensional sized geometrical model obtained from anatomically measurement used as structural model The transient finite element method including inertia effects and time dependencies implemented for numerical solution. Two different material models have been considered to illustrate the effect of material nonlinearity on the stress and strain imposed by leaflets. On the other hand Chordae tendineae rupture caused by bacterial endocarditis, rheumatic valvular disease or trauma can be a deadly defect leads to malfunction of human heart. Chordae tendineae rupture has been also simulated to investigate the effects on leaflet stresses and strains. Based on the results, although the linear elastic model exhibits an acceptable correlation in the location of high stress regions with the hyperelastic model but Stress magnitudes differ between the elastic and hyper elastic model Depending on the strain energy function used to describe the nonlinear material, different stress magnitudes release from the analyses. Chordae rupture causes an unintended increase in the magnitude of leaflet stresses and the closed valve configuration. The increment value depends on the location and number of ruptured chordae.

The strain-stiffening property of tendons is a key feature to prevent muscle from damage during vigorous contraction. Tendon injuries are usually associated with declination of such property. Shear wave elasticity imaging (SWEI) has emerged as a promising tool to non-invasively evaluate this property in injured tendons and monitor its deterioration or recovery after treatment. In our previous work, we found that the shear wave velocities increase linearly when tendons subjected to increasing loads. However, the Young's modulus derived from shear wave velocities (i.e. E=3π 2 2) can't be coincided with the Young's modulus measured by uniaxial tensile test. In other words, there are few quantitative models available to interpret the SWEI results measured in tendons due to their complex architecture and nonlinear mechanical behaviors. In this study, we developed a numerical model using ABAQUS to characterize the non-linear and strain-stiffening properties of tendons measured from SWEI and mechanical stretching tests. Normal and injured tendons were modeled based on the material properties measured from experiments. An anisotropic hyperelastic model was employed and shear wave propagation was simulated in the modeled tendons when they were pre-stretched by loads varying from 0 to 3 N. Our preliminary results successfully recapitulated the trend of changes of shear wave velocities with respect to different pre-stretches observed in SWEI. The simulated velocity of shear waves propagating along the longitudinal axis of the control tendons increased from 15.9 to 23.61 m/s. On the other hand, the simulated velocity of shear waves propagating along the longitudinal axis of the injured tendons increased from 14.26 to 16.43 m/s. In addition, both the shear wave velocities and tensile moduli of the normal/injured tendons increased as the pre-stretches increased. Our work provides a quantitative basis to explain the strain-stiffening behaviors of tendons measured by SWEI and highlights the potential of applying SWEI to quantitatively assess mechanical dysfunction of injured tendons.

Failure behavior characterization and prediction of fatigue life of elastomers became important issues due to the wide usage of elastomeric components in Aerospace applications. Thus, the understanding of the fatigue crack initiation micro-mechanisms and their link to the local stress or strain history were particularly essential. Crackscould initiate and propagate over a long period of time since 90% of the fatigue life was spent in the crack stage. Cracks were found to initiate at defects associated with the sample geometry and processing, then propagated systematically in the direction given by the maximal principal strain reached during the cycle, evenunder non-proportional loading. In this study a general methodology derived fromcontinuum damage mechanics and the material fatigue damage to the number of cycles was proposed, in which the Mullin's effect was also discussed. The shell shape specimen was used for fatigue life prediction based on FE simulation using Ogden hyperelastic material model determined from the tensile, shear and biaxial tension tests of the natural rubber. lt was shown that the fatigue life prediction results were good agreement with the experimental results.

The current trend in soft robotic solutions is to pneumatically actuate chambers within manipulators that feature elastomeric material. This work describes the development of a repeating module actuator with each module capable of producing 3 degrees of freedom, as well as longitudinal expansion, intended for use as a laparoscopic tool in minimal invasive surgery. The design of the manipulator geometry as well as the choice of suitable material is dependent on the application, range of motion, and the suitable actuation pressure. This work describes the use of finite element analysis to simulate the range of motion of the hyperelastic response of two different soft silicones. Different geometry ratios and channel designs of the actuator are then optimized in terms of bending angle, maximum stress generated, radial expansion due to air pressure, and the amount of free area that the design allows in the actuator for other tools necessary in laparoscopic surgery. The optimum geometries are then selected as candidates for the development of the repeating module design, and the addition of skins to the module is investigated for the optimized module design.

Heart valves control the blood flow and play an extremely important role in the functioning of heart. Either due to congenital defects or due to the changes with remodeling, the leaflets functionality is altered sometimes resulting in less efficient heart output. Such problems are difficult to diagnose at an early stage and may lead to heart failure if left untreated. In this work, we present a method for determining the functional properties of heart valve leaflets from non-invasive imaging modules. As a first step, we use in-vitro experimental data from porcine bioprosthetic heart valve in a flow loop. We present the details of inverse model, its validation against experimental data and sensitivity to various input parameters and optimization constraints. In addition, we briefly touch upon other components of this in-vivo assessment tool - the average fiber architecture and the pre-strain in valve leaflets. This information when combined with the inverse model presented in this work will lead to an in-vivo assessment tool for heart valves and help diagnose problems in the mechanical functionality at an early stage. Additionally, this approach will have the potential to serve as a general-purpose in-vivo assessment tool for heart valves - for evaluating the performance of replaced prosthetic valves as well as monitoring the progression of valve diseases.

The reliability of long-term recording of implantable neural probes depends on several factors, including adverse tissue response which forms astroglial sheath scarring around the probe. Brain micromotion is one of the possible causes of this tissue reaction. It creates localized strain around the probe tip, leading to shear-induced inflammation at the implant site. Although the strain induced by brain micromotion may exceed the accepted linear range for biological tissues, linear brain models have been employed in most modeling studies. Hence, the aim of this investigation is to verify the validity of assuming small-strain deformation used for linear brain tissue models in brain micromotion studies. Finite element (FE) models, utilizing both elastic and hyperelastic brain models, are developed to study the strains at the probe-tissue interface, for longitudinal and lateral brain micromotion. The results show that the strain around the probe tip for both material models, exceeds commonly accepted linear strain range. This finding suggests that use of a nonlinear elastic model to model brain micromotion is more realistic. Moreover, the neural `kill zone', denoting distances within which the strains are greater than 5%, is estimated to extend to more than 20 μm from the probe tip for longitudinal micromotion displacement.