Constitutive modeling of menisci tissue: a critical review of analytical and numerical approaches.

Menisci are fibrocartilaginous disks consisting of soft tissue with a complex biomechanical structure. They are critical determinants of the kinematics as well as the stability of the knee joint. Several studies have been carried out to formulate tissue mechanical behavior, leading to the development of a wide spectrum of constitutive laws. In addition to developing analytical tools, extensive numerical studies have been conducted on menisci modeling. This study reviews the developments of the most widely used continuum models of the meniscus mechanical properties in conjunction with emerging analytical and numerical models used to study the meniscus. The review presents relevant approaches and assumptions used to develop the models and includes discussions regarding strengths, weaknesses, and discrepancies involved in the presented models. The study presents a comprehensive coverage of relevant publications included in Compendex, EMBASE, MEDLINE, PubMed, ScienceDirect, Springer, and Scopus databases. This review aims at opening novel avenues for improving menisci modeling within the framework of constitutive modeling through highlighting the needs for further research directed toward determining key factors in gaining insight into the biomechanics of menisci which is crucial for the elaborate design of meniscal replacements.

A novel micro-to-macro structural approach for mechanical characterization of adipose tissue extracellular matrix.

Mechanical characterization of adipose tissue micro-components is important for various biomedical applications such as tissue engineering and predicting adipose tissue response to forces involved in relevant medical intervention procedures (e.g. breast needle biopsy). For this characterization, we introduce a novel structural method for micromechanical modeling of the adipose tissue. The micromechanical model was developed using fluid-structure interaction (FSI) formulation. We utilized this model within an inverse problem framework to estimate the hyperelastic parameters of adipose tissue extracellular matrix (ECM). Using this framework, the ECM hyperelastic parameters were changed in the FSI model systematically using an optimization algorithm such that the mechanical response obtained from the FSI model matches the corresponding experimental response reported in previous studies. To account for adipocyte size variation, the hyperelastic parameters were determined for different adipocyte sizes in the FSI model. Results obtained in this investigation indicate that at various strains under quasi-static conditions, the stiffness of adipose tissue ECM is ~ (2-3) times higher than that of the adipose tissue. The results also indicate a very good fit between the FSI model responses and their experimental counterparts. This indicates the reliability of the proposed FSI model in capturing major elements of the adipose tissue micromechanics. As such, it is potentially useful in applications such as tissue engineering, estimating tissue deformation pertaining to medical intervention and cataloging the mechanical properties of adipose tissue under health and pathological conditions. It can also be utilized as a forward model for developing inversion algorithms designed to determine pathological adipose microstructural alterations.

Mechanical modeling and characterization of meniscus tissue using flat punch indentation and inverse finite element method.

In this paper, to characterize the mechanical properties of meniscus by considering its local microstructure, a novel nonlinear poroviscoelastic Finite Element (FE) model has been developed. To obtain the mechanical response of meniscus, indentation experiments were performed on bovine meniscus samples. The ramp-relaxation test scenario with different depths and preloads was designed to capture the mechanical characteristics of the tissue in different regions of the medial and lateral menisci. Thereafter, a FE simulation was performed considering experimental conditions. Constitutive parameters were optimized by solving a FE-based inverse problem using the heuristic Simulated Annealing (SA) optimization algorithm. These parameters were ranged according to previously reported data to improve the optimization procedure. Based on the results, the mechanical properties of meniscus were highly influenced by both superficial and main layers. At low indentation depths, a high percentage relaxation (p < 0.01) with a high relaxation rate (p < 0.05) was obtained, due to the poroelastic and viscoelastic nature of the superficial layer. Increasing both penetration depth and preload level involved the main layer response and caused alterations in hyperelastic and viscoelastic parameters of the tissue, such that for both layers, the shear modulus was increased (p < 0.01) while the rate and percentage of relaxation were decreased (p < 0.01). Results reflect that, shear modulus of the main layer in anterior region is higher than central and posterior sites in medial meniscus. In contrast, in lateral meniscus, posterior side is stiffer than central and anterior sides.

A new method for control of networked systems with an experimental verification.

This paper presents a variable selective control methodology for control of networked systems subject to transfer delay, packet-loss and packet-disordering. This approach is based upon the extension of the variable sampling period idea with a new packet based control methodology. In this way, corresponding to a range of expected time delays, a number of step-invariant discrete-time plant models are considered and based on them, a switching observer-based controller is designed by solving linear matrix inequalities (LMIs). A sufficient condition for closed-loop asymptotic stability is derived. Simulation and experimental investigations demonstrate the effectiveness of the proposed method in the real world.