Ahmet Erdemir

Lerner Research Institute, Cleveland, Ohio, United States

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Publications (35)80 Total impact

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    ABSTRACT: Therapeutic footwear is frequently prescribed in cases of rheumatoid arthritis and diabetes to relieve or redistribute high plantar pressures in the region of the metatarsal heads. Few guidelines exist as to how these interventions should be designed and what effect such interventions actually have on the plantar pressure distribution. Finite element analysis has the potential to assist in the design process by refining a given intervention or identifying an optimal intervention without having to actually build and test each condition. However, complete and detailed foot models based on medical image segmentation have proven time consuming to build and computationally expensive to solve, hindering their utility in practice. Therefore, the goal of the current work was to determine if a simplified patient-specific model could be used to assist in the design of foot orthoses to reduce the plantar pressure in the metatarsal head region. The approach is illustrated by a case study of a diabetic patient experiencing high pressures and pain over the fifth metatarsal head. The simple foot model was initially calibrated by adjusting the individual loads on the metatarsals to approximate measured peak plantar pressure distributions in the barefoot condition to within 3%. This loading was used in various shod conditions to identify an effective orthosis. Model results for metatarsal pads were considerably higher than measured values but predictions for uniform surfaces were generally within 16% of measured values. The approach enabled virtual prototyping of the orthoses, identifying the most favorable approach to redistribute the patient's plantar pressures.
    Journal of biomechanics. 07/2014;
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    ABSTRACT: Recent advances in computational modeling and simulation of human movement makes it possible to isolate and predict the potential contributions of a prosthetic device to the overall system performance. The Mauch S-N-S knee is one of the most widely used prosthetic knees in the market. The goal of this study is to develop dynamic models of the Mauch S-N-S knee for predictive simulation of a transfemoral amputee׳s gait under idealized conditions. Based on the functional description of the Mauch S-N-S prosthetic knee from the literature, a combined bench test and data fitting approach employing modified slow, normal, and fast gait patterns and nine combinations of stance and swing damping settings were performed. Two types of dynamic models, 2-phase and 4-phase models, of the Mauch S-N-S prosthetic knee were developed. The range of the coefficient of determination of the two dynamic models, when compared to the test data, was from 39.9 to 95%. Both dynamic models of this study can be utilized in musculoskeletal modeling studies, to better understand amputee gait and the contributions and interactions of various prosthetic leg components to the ambulatory performance.
    Journal of biomechanics. 06/2014;
  • Craig J Bennetts, Scott Sibole, Ahmet Erdemir
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    ABSTRACT: Finite element analysis provides a means of describing cellular mechanics in tissue, which can be useful in understanding and predicting physiological and pathological changes. Many prior studies have been limited to simulations of models containing single cells, which may not accurately describe the influence of mechanical interactions between cells. It is desirable to generate models that more accurately reflect the cellular organisation in tissue in order to evaluate the mechanical function of cells. However, as the model geometry becomes more complicated, manual model generation can become laborious. This can be prohibitive if a large number of distinct cell-scale models are required, for example, in multiscale modelling or probabilistic analysis. Therefore, a method was developed to automatically generate tissue-specific cellular models of arbitrary complexity, with minimal user intervention. This was achieved through a set of scripts, which are capable of generating both sample-specific models, with explicitly defined geometry, and tissue-specific models, with geometry derived implicitly from normal statistical distributions. Models are meshed with tetrahedral (TET) elements of variable size to sufficiently discretise model geometries at different spatial scales while reducing model complexity. The ability of TET meshes to appropriately simulate the biphasic mechanical response of a single-cell model is established against that of a corresponding hexahedral mesh for an illustrative use case. To further demonstrate the flexibility of this tool, an explicit model was developed from three-dimensional confocal laser scanning image data, and a set of models were generated from a statistical cellular distribution of the articular femoral cartilage. The tools presented herein are free and openly accessible to the community at large.
    Computer Methods in Biomechanics and Biomedical Engineering 04/2014; · 1.39 Impact Factor
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    ABSTRACT: In cartilage tissue engineering studies, the stimulatory effect of a constant magnitude of mechanical perturbation declines after the first two weeks of culture. Similarly, it is known that chondrocyte-agarose constructs should not be loaded within the first days after seeding, to prevent considerable cell death, suggesting a mechanical threshold. This study aims to establish a relationship between chondrocyte deformation and death, and to evaluate the protective effect of the pericellular matrix (PCM) that is formed in 3D cultures. Chondrocyte viability was monitored every hour for 24 hours after applying a strain range of 0% to 25% to agarose constructs containing chondrocytes, cultured for 1, 3, 5, 7 or 10 days. At these culture time points, PCM thickness and chondrocyte deformation were assessed by means of histology and assayed for biochemical contents. Inverse finite element simulations were used to evaluate the change of mechanical properties of the chondrocyte and PCM over the 10 day culture duration. Chondrocyte death was demonstrated to be dependent on both the magnitude and duration of straining. The highest cell death was observed at day 1 (43%), reducing over culture duration (15% at day 3, and 2.5% at day 10). Cell deformation at 25% compression decreased significantly over culture duration (aspect ratio of 2.24 ± 0.67 at day 1 and 1.45 ± 0.24 at day 3) and with increased matrix production. Inverse finite element simulations showed an increasing PCM Young's modulus of 45 KPa at day 3 to 162 KPa at day 10. The current results provide evidence for a mechanical threshold for chondrocyte death and for the protective effect of the PCM. As such, these insights may help in establishing mechanical loading protocols for cartilage tissue engineering studies.
    Tissue Engineering Part A 01/2014; · 4.64 Impact Factor
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    ABSTRACT: Anterior tears of the supraspinatus tendon are more likely to be clinically relevant than posterior tears of the supraspinatus. We hypothesized that anterior tears of the supraspinatus tendon involving the rotator cuff cable insertion are associated with greater tear gapping, decreased tendon stiffness, and increased regional tendon strain under physiologic loading conditions compared with equivalently sized tears of the rotator cuff crescent. Twelve human cadaveric shoulders were randomized to undergo simulation of equivalently sized supraspinatus tears of either the anterior rotator cuff cable (n = 6) or the adjacent rotator cuff crescent (n = 6). For each specimen, the supraspinatus tendon was cyclically loaded from 10 N to 180 N, and a custom three-dimensional optical system was used to track markers on the surface of the tendon. Tear gap distance, stiffness, and regional strains of the supraspinatus tendon were calculated. The tear gap distance of large cable tears (median gap distance, 5.2 mm) was significantly greater than that of large crescent tears (median gap distance, 1.3 mm) (p = 0.002), the stiffness of tendons with a small (p = 0.002) or large (p = 0.002) cable tear was significantly greater than that of tendons with equivalently sized crescent tears, and regional strains across the supraspinatus were significantly increased in magnitude and altered in distribution by tears involving the anterior insertion of the rotator cuff cable. These findings support our hypothesis that the rotator cuff cable, which is in the most anterior 8 to 12 mm of the supraspinatus tendon immediately posterior to the bicipital groove, is the primary load-bearing structure within the supraspinatus for force transmission to the proximal part of the humerus. Conversely, in the presence of an intact rotator cuff cable, the rotator cuff crescent insertion is relatively stress-shielded and plays a significantly lesser role in supraspinatus force transmission. Clinicians should consider early repair of rotator cuff cable tears, which may need surgical intervention to address their biomechanical pathology. In contrast, surgical treatment may be more safely delayed for rotator cuff crescent tears.
    The Journal of Bone and Joint Surgery 10/2013; 95(20):1817-24. · 3.23 Impact Factor
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    ABSTRACT: Understanding the mechanical behaviour of chondrocytes as a result of cartilage tissue mechanics has significant implications for both evaluation of mechanobiological function and to elaborate on damage mechanisms. A common procedure for prediction of chondrocyte mechanics (and of cell mechanics in general) relies on a computational post-processing approach where tissue-level deformations drive cell-level models. Potential loss of information in this numerical coupling approach may cause erroneous cellular-scale results, particularly during multiphysics analysis of cartilage. The goal of this study was to evaluate the capacity of first- and second-order data passing to predict chondrocyte mechanics by analysing cartilage deformations obtained for varying complexity of loading scenarios. A tissue-scale model with a sub-region incorporating representation of chondron size and distribution served as control. The post-processing approach first required solution of a homogeneous tissue-level model, results of which were used to drive a separate cell-level model (same characteristics as the sub-region of control model). The first-order data passing appeared to be adequate for simplified loading of the cartilage and for a subset of cell deformation metrics, for example, change in aspect ratio. The second-order data passing scheme was more accurate, particularly when asymmetric permeability of the tissue boundaries was considered. Yet, the method exhibited limitations for predictions of instantaneous metrics related to the fluid phase, for example, mass exchange rate. Nonetheless, employing higher order data exchange schemes may be necessary to understand the biphasic mechanics of cells under lifelike tissue loading states for the whole time history of the simulation.
    Computer Methods in Biomechanics and Biomedical Engineering 06/2013; · 1.39 Impact Factor
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    ABSTRACT: Accurate prediction of plantar shear stress and internal stress in the soft tissue layers of the foot using finite element models would provide valuable insight into the mechanical etiology of neuropathic foot ulcers. Accurate prediction of the internal stress distribution using finite element models requires that realistic descriptions of the material properties of the soft tissues are incorporated into the model. Our investigation focused on the creation of a novel three-dimensional (3D) finite element model of the forefoot with multiple soft tissue layers (skin, fat pad, and muscle) and the development of an inverse finite element procedure that would allow for the optimization of the nonlinear elastic coefficients used to define the material properties of the skin muscle and fat pad tissue layers of the forefoot based on a Ogden hyperelastic constitutive model. Optimization was achieved by comparing deformations predicted by finite element models to those measured during an experiment in which magnetic resonance imaging (MRI) images were acquired while the plantar surface forefoot was compressed. The optimization procedure was performed for both a model incorporating all three soft tissue layers and one in which all soft tissue layers were modeled as a single layer. The results indicated that the inclusion of multiple tissue layers affected the deformation and stresses predicted by the model. Sensitivity analysis performed on the optimized coefficients indicated that small changes in the coefficient values (±10%) can have rather large impacts on the predicted nominal strain (differences up to 14%) in a given tissue layer.
    Journal of Biomechanical Engineering 06/2013; 135(6):61001-12. · 1.52 Impact Factor
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    ABSTRACT: High plantar pressures have been associated with foot ulceration in people with diabetes, who can experience loss of protective sensation due to peripheral neuropathy. Therefore, characterization of elevated plantar pressure distributions can provide a means of identifying diabetic patients at potential risk of foot ulceration. Plantar pressure distribution classification can also be used to determine suitable preventive interventions, such as the provision of an appropriately designed insole. In the past, emphasis has primarily been placed on the identification of individual focal areas of elevated pressure. The goal of this study was to utilize k-means clustering analysis to identify typical regional peak plantar pressure distributions in a group of 819 diabetic feet. The number of clusters was varied from 2 to 10 to examine the effect on the differentiation and classification of regional peak plantar pressure distributions. As the number of groups increased, so too did the specificity of their pressure distributions: starting with overall low or overall high peak pressure groups and extending to clusters exhibiting several focal peak pressures in different regions of the foot. However, as the number of clusters increased, the ability to accurately classify a given regional peak plantar pressure distribution decreased. The balance between these opposing constraints can be adjusted when assessing patients with feet that are potentially "at risk" or while prescribing footwear to reduce high regional pressures. This analysis provides an understanding of the variability of the regional peak plantar pressure distributions seen within the diabetic population and serves as a guide for the preemptive assessment and prevention of diabetic foot ulcers.
    Journal of biomechanics 10/2012; · 2.66 Impact Factor
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    ABSTRACT: Articular cartilage experiences significant mechanical loads during daily activities. Healthy cartilage provides the capacity for load bearing and regulates the mechanobiological processes for tissue development, maintenance, and repair. Experimental studies at multiple scales have provided a fundamental understanding of macroscopic mechanical function, evaluation of the micromechanical environment of chondrocytes, and the foundations for mechanobiological response. In addition, computational models of cartilage have offered a concise description of experimental data at many spatial levels under healthy and diseased conditions, and have served to generate hypotheses for the mechanical and biological function. Further, modeling and simulation provides a platform for predictive risk assessment, management of dysfunction, as well as a means to relate multiple spatial scales. Simulation-based investigation of cartilage comes with many challenges including both the computational burden and often insufficient availability of data for model development and validation. This review outlines recent modeling and simulation approaches to understand cartilage function from a mechanical systems perspective, and illustrates pathways to associate mechanics with biological function. Computational representations at single scales are provided from the body down to the microstructure, along with attempts to explore multiscale mechanisms of load sharing that dictate the mechanical environment of the cartilage and chondrocytes.
    Annals of Biomedical Engineering 05/2012; 40(11):2456-74. · 3.23 Impact Factor
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    ABSTRACT: Quantification of plantar tissue behavior of the heel pad is essential in developing computational models for predictive analysis of preventive treatment options such as footwear for patients with diabetes. Simulation based studies in the past have generally adopted heel pad properties from the literature, in return using heel-specific geometry with material properties of a different heel. In exceptional cases, patient-specific material characterization was performed with simplified two-dimensional models, without further evaluation of a heel-specific response under different loading conditions. The aim of this study was to conduct an inverse finite element analysis of the heel in order to calculate heel-specific material properties in situ. Multidimensional experimental data available from a previous cadaver study by Erdemir et al. ("An Elaborate Data Set Characterizing the Mechanical Response of the Foot," ASME J. Biomech. Eng., 131(9), pp. 094502) was used for model development, optimization, and evaluation of material properties. A specimen-specific three-dimensional finite element representation was developed. Heel pad material properties were determined using inverse finite element analysis by fitting the model behavior to the experimental data. Compression dominant loading, applied using a spherical indenter, was used for optimization of the material properties. The optimized material properties were evaluated through simulations representative of a combined loading scenario (compression and anterior-posterior shear) with a spherical indenter and also of a compression dominant loading applied using an elevated platform. Optimized heel pad material coefficients were 0.001084 MPa (μ), 9.780 (α) (with an effective Poisson's ratio (ν) of 0.475), for a first-order nearly incompressible Ogden material model. The model predicted structural response of the heel pad was in good agreement for both the optimization (<1.05% maximum tool force, 0.9% maximum tool displacement) and validation cases (6.5% maximum tool force, 15% maximum tool displacement). The inverse analysis successfully predicted the material properties for the given specimen-specific heel pad using the experimental data for the specimen. The modeling framework and results can be used for accurate predictions of the three-dimensional interaction of the heel pad with its surroundings.
    Journal of Biomechanical Engineering 03/2012; 134(3):031002. · 1.52 Impact Factor
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    ABSTRACT: Simulation-based medicine and the development of complex computer models of biological structures is becoming ubiquitous for advancing biomedical engineering and clinical research. Finite element analysis (FEA) has been widely used in the last few decades to understand and predict biomechanical phenomena. Modeling and simulation approaches in biomechanics are highly interdisciplinary, involving novice and skilled developers in all areas of biomedical engineering and biology. While recent advances in model development and simulation platforms offer a wide range of tools to investigators, the decision making process during modeling and simulation has become more opaque. Hence, reliability of such models used for medical decision making and for driving multiscale analysis comes into question. Establishing guidelines for model development and dissemination is a daunting task, particularly with the complex and convoluted models used in FEA. Nonetheless, if better reporting can be established, researchers will have a better understanding of a model's value and the potential for reusability through sharing will be bolstered. Thus, the goal of this document is to identify resources and considerate reporting parameters for FEA studies in biomechanics. These entail various levels of reporting parameters for model identification, model structure, simulation structure, verification, validation, and availability. While we recognize that it may not be possible to provide and detail all of the reporting considerations presented, it is possible to establish a level of confidence with selective use of these parameters. More detailed reporting, however, can establish an explicit outline of the decision-making process in simulation-based analysis for enhanced reproducibility, reusability, and sharing.
    Journal of biomechanics 02/2012; 45(4):625-33. · 2.66 Impact Factor
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    Scott C Sibole, Ahmet Erdemir
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    ABSTRACT: Cells of the musculoskeletal system are known to respond to mechanical loading and chondrocytes within the cartilage are not an exception. However, understanding how joint level loads relate to cell level deformations, e.g. in the cartilage, is not a straightforward task. In this study, a multi-scale analysis pipeline was implemented to post-process the results of a macro-scale finite element (FE) tibiofemoral joint model to provide joint mechanics based displacement boundary conditions to micro-scale cellular FE models of the cartilage, for the purpose of characterizing chondrocyte deformations in relation to tibiofemoral joint loading. It was possible to identify the load distribution within the knee among its tissue structures and ultimately within the cartilage among its extracellular matrix, pericellular environment and resident chondrocytes. Various cellular deformation metrics (aspect ratio change, volumetric strain, cellular effective strain and maximum shear strain) were calculated. To illustrate further utility of this multi-scale modeling pipeline, two micro-scale cartilage constructs were considered: an idealized single cell at the centroid of a 100×100×100 μm block commonly used in past research studies, and an anatomically based (11 cell model of the same volume) representation of the middle zone of tibiofemoral cartilage. In both cases, chondrocytes experienced amplified deformations compared to those at the macro-scale, predicted by simulating one body weight compressive loading on the tibiofemoral joint. In the 11 cell case, all cells experienced less deformation than the single cell case, and also exhibited a larger variance in deformation compared to other cells residing in the same block. The coupling method proved to be highly scalable due to micro-scale model independence that allowed for exploitation of distributed memory computing architecture. The method's generalized nature also allows for substitution of any macro-scale and/or micro-scale model providing application for other multi-scale continuum mechanics problems.
    PLoS ONE 01/2012; 7(5):e37538. · 3.73 Impact Factor
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    ABSTRACT: Finite element analysis has been widely used in the field of foot and footwear biomechanics to determine plantar pressures as well as stresses and strains within soft tissue and footwear materials. When dealing with anatomical structures such as the foot, hexahedral mesh generation accounts for most of the model development time due to geometric complexities imposed by branching and embedded structures. Tetrahedral meshing, which can be more easily automated, has been the approach of choice to date in foot and footwear biomechanics. Here we use the nonlinear finite element program Abaqus (Simulia, Providence, RI) to examine the advantages and disadvantages of tetrahedral and hexahedral elements under compression and shear loading, material incompressibility, and frictional contact conditions, which are commonly seen in foot and footwear biomechanics. This study demonstrated that for a range of simulation conditions, hybrid hexahedral elements (Abaqus C3D8H) consistently performed well while hybrid linear tetrahedral elements (Abaqus C3D4H) performed poorly. On the other hand, enhanced quadratic tetrahedral elements with improved stress visualization (Abaqus C3D10I) performed as well as the hybrid hexahedral elements in terms of contact pressure and contact shear stress predictions. Although the enhanced quadratic tetrahedral element simulations were computationally expensive compared to hexahedral element simulations in both barefoot and footwear conditions, the enhanced quadratic tetrahedral element formulation seems to be very promising for foot and footwear applications as a result of decreased labor and expedited model development, all related to facilitated mesh generation.
    Journal of biomechanics 08/2011; 44(12):2337-43. · 2.66 Impact Factor
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    Jason P Halloran, Ahmet Erdemir
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    ABSTRACT: Simulation-based prediction of specimen-specific biomechanical behavior commonly requires inverse analysis using geometrically consistent finite element (FE) models. Optimization drives such analyses but previous studies have highlighted a large computational cost dictated by iterative use of nonlinear FE models. The goal of this study was to evaluate the performance of a local regression-based adaptive surrogate modeling approach to decrease computational cost for both global and local optimization approaches using an inverse FE application. Nonlinear elastic material parameters for patient-specific heel-pad tissue were found, both with and without the surrogate model. Surrogate prediction replaced a FE simulation using local regression of previous simulations when the corresponding error estimate was less than a given tolerance. Performance depended on optimization type and tolerance value. The surrogate reduced local optimization expense up to 68%, but achieved accurate results for only 1 of 20 initial conditions. Conversely, up to a tolerance value of 20 N(2), global optimization with the surrogate yielded consistent parameter predictions with a concurrent decrease in computational cost (up to 77%). However, the local optimization method without the surrogate, although sensitive to the initial conditions, was still on average seven times faster than the global approach. Our results help establish guidelines for setting acceptable tolerance values while using an adaptive surrogate model for inverse FE analysis. Most important, the study demonstrates the benefits of a surrogate modeling approach for intensive FE-based iterative analysis.
    Annals of Biomedical Engineering 05/2011; 39(9):2388-97. · 3.23 Impact Factor
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    ABSTRACT: Current computational methods for simulating locomotion have primarily used muscle-driven multibody dynamics, in which neuromuscular control is optimized. Such simulations generally represent joints and soft tissue as simple kinematic or elastic elements for computational efficiency. These assumptions limit application in studies such as ligament injury or osteoarthritis, where local tissue loading must be predicted. Conversely, tissue can be simulated using the finite element method with assumed or measured boundary conditions, but this does not represent the effects of whole body dynamics and neuromuscular control. Coupling the two domains would overcome these limitations and allow prediction of movement strategies guided by tissue stresses. Here we demonstrate this concept in a gait simulation where a musculoskeletal model is coupled to a finite element representation of the foot. Predictive simulations incorporated peak plantar tissue deformation into the objective of the movement optimization, as well as terms to track normative gait data and minimize fatigue. Two optimizations were performed, first without the strain minimization term and second with the term. Convergence to realistic gait patterns was achieved with the second optimization realizing a 44% reduction in peak tissue strain energy density. The study demonstrated that it is possible to alter computationally predicted neuromuscular control to minimize tissue strain while including desired kinematic and muscular behavior. Future work should include experimental validation before application of the methodology to patient care.
    Journal of biomechanics 10/2010; 43(14):2810-5. · 2.66 Impact Factor
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    ABSTRACT: Mechanical properties of the foot are responsible for its normal function and play a role in various clinical problems. Specifically, we are interested in quantification of foot mechanical properties to assist the development of computational models for movement analysis and detailed simulations of tissue deformation. Current available data are specific to a foot region and the loading scenarios are limited to a single direction. A data set that incorporates regional response, to quantify individual function of foot components, as well as the overall response, to illustrate their combined operation, does not exist. Furthermore, the combined three-dimensional loading scenarios while measuring the complete three-dimensional deformation response are lacking. When combined with an anatomical image data set, development of anatomically realistic and mechanically validated models becomes possible. Therefore, the goal of this study was to record and disseminate the mechanical response of a foot specimen, supported by imaging data. Robotic testing was conducted at the rear foot, forefoot, metatarsal heads, and the foot as a whole. Complex foot deformations were induced by single mode loading, e.g., compression, and combined loading, e.g., compression and shear. Small and large indenters were used for heel and metatarsal head loading, an elevated platform was utilized to isolate the rear foot and forefoot, and a full platform compressed the whole foot. Three-dimensional tool movements and reaction loads were recorded simultaneously. Computed tomography scans of the same specimen were collected for anatomical reconstruction a priori. The three-dimensional mechanical response of the specimen was nonlinear and viscoelastic. A low stiffness region was observed starting with contact between the tool and foot regions, increasing with loading. Loading and unloading responses portrayed hysteresis. Loading range ensured capturing the toe and linear regions of the load deformation curves for the dominant loading direction, with the rates approximating those of walking. A large data set was successfully obtained to characterize the overall and the regional mechanical responses of an intact foot specimen under single and combined loads. Medical imaging complemented the mechanical testing data to establish the potential relationship between the anatomical architecture and mechanical responses and to further develop foot models that are mechanically realistic and anatomically consistent. This combined data set has been documented and disseminated in the public domain to promote future development in foot biomechanics.
    Journal of Biomechanical Engineering 10/2009; 131(9):094502. · 1.52 Impact Factor
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    ABSTRACT: Biomechanics is broadly defined as the scientific discipline that investigates the effects of forces acting on and within biological structures. The realm of biomechanics includes the circulatory and respiratory systems, tissue mechanics and mechanotransduction, and the musculoskeletal system and motor control. As in many other biological phenomena, many spatial scales are crossed by biomechanics research: intracellular, multicellular, and extracellular matrices; and tissue, organ, and multiorgan systems. It is well established that the effect of forces at higher scales influence behavior at lower scales and that lower-scale properties influence higher-scale response. However, computational methods that incorporate these interactions in biomechanics are relatively rare. In general, computational models that include representation of multiple spatial or temporal scales are loosely defined as multiscale. The fact that multiscale modeling is not well defined lends the term to a variety of scenarios within the computational physiology community. In biomechanics, multiscale modeling may mean establishing a hierarchical link between the spatial and temporal scales, while the output of a larger-scale system is passed through a finely detailed representation at a lower scale (e.g., body-level movement simulations that provide net joint loading for tissue-level stress analysis). In reality, multiscale modeling may require more intricate representation of interactions among scales. A concurrent simulation strategy is inevitable to adequately represent nonlinear associations that have been known for decades [1].
    IEEE Engineering in Medicine and Biology Magazine 07/2009; · 2.73 Impact Factor
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    ABSTRACT: In this article, we describe some current multiscale modeling issues in computational biomechanics from the perspective of the musculoskeletal and respiratory systems and mechanotransduction. First, we outline the necessity of multiscale simulations in these biological systems. Then we summarize challenges inherent to multiscale biomechanics modeling, regardless of the subdiscipline, followed by computational challenges that are system-specific. We discuss some of the current tools that have been utilized to aid research in multiscale mechanics simulations, and the priorities to further the field of multiscale biomechanics computation.
    05/2009; 28(3).
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    ABSTRACT: Finite element (FE) modeling and multibody dynamics have traditionally been applied separately to the domains of tissue mechanics and musculoskeletal movements, respectively. Simultaneous simulation of both domains is needed when interactions between tissue and movement are of interest, but this has remained largely impractical due to the high computational cost. Here we present a method for the concurrent simulation of tissue and movement, in which state of the art methods are used in each domain, and communication occurs via a surrogate modeling system based on locally weighted regression. The surrogate model only performs FE simulations when regression from previous results is not within a user-specified tolerance. For proof of concept and to illustrate feasibility, the methods were demonstrated on an optimization of jumping movement using a planar musculoskeletal model coupled to a FE model of the foot. To test the relative accuracy of the surrogate model outputs against those of the FE model, a single forward dynamics simulation was performed with FE calls at every integration step and compared with a corresponding simulation with the surrogate model included. Neural excitations obtained from the jump height optimization were used for this purpose and root mean square (RMS) difference between surrogate and FE model outputs (ankle force and moment, peak contact pressure and peak von Mises stress) were calculated. Optimization of the jump height required 1800 iterations of the movement simulation, each requiring thousands of time steps. The surrogate modeling system only used the FE model in 5% of time steps, i.e., a 95% reduction in computation time. Errors introduced by the surrogate model were less than 1 mm in jump height and RMS errors of less than 2 N in ground reaction force, 0.25 Nm in ankle moment, and 10 kPa in peak tissue stress. Adaptive surrogate modeling based on local regression allows efficient concurrent simulations of tissue mechanics and musculoskeletal movement.
    Journal of Biomechanical Engineering 03/2009; 131(1):011014. · 1.52 Impact Factor
  • Marc Petre, Ahmet Erdemir, Peter R Cavanagh
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    ABSTRACT: It is well known that mechanical forces acting within the soft tissues of the foot can contribute to the formation of neuropathic ulcers in people with diabetes. Presently, only surface measurements of plantar pressure are used clinically to estimate risk status due to mechanical loading. It is currently not known how surface measurements relate to the three-dimensional (3-D) internal stress/strain state of the foot. This article describes the development of a foot-loading device that allows for the direct observation of the internal deformation of foot tissues under known forces. Ground reaction forces and plantar pressure distributions during normal walking were measured in ten healthy young adults. One instant in the gait cycle, when pressure under the metatarsal heads reached a peak, was extracted for simulation in an MR imager. T1-weighted 3-D gradient echo MRI sets were collected as the simulated walking ground reaction force was incrementally applied to the foot by the novel foot-loading device. The sub-metatarsal head soft-tissue thickness decreased rapidly at first and then reached a plateau. Peak plantar pressure measurements collected within the loading device (161+/-75kPa) were lower in magnitude and less focal than pressures measured during walking (492+/-91kPa). This finding implies that although the device successfully applied full peak walking ground reaction forces to the foot, they were not distributed in the same manner as during walking. Although not representative of gait, the data collected from this in vivo mechanical test are suitable for determination of foot tissue material properties or, when combined with finite element modeling, to examine the relationship between surface loading and internal stress.
    Journal of Biomechanics 02/2008; 41(2):470-4. · 2.72 Impact Factor

Publication Stats

521 Citations
80.00 Total Impact Points

Institutions

  • 2009–2014
    • Lerner Research Institute
      Cleveland, Ohio, United States
  • 2008
    • Cleveland Clinic
      Cleveland, Ohio, United States
  • 2006
    • Saint Louis University
      • Department of Biomedical Engineering
      Saint Louis, MI, United States
  • 2002–2004
    • Pennsylvania State University
      • Center for Locomotion Studies
      University Park, MD, United States