Mark de Zee

Analysis of Musculoskeletal Systems in the AnyBody Modeling System

This paper reviews the simulation software the AnyBody Modeling System, which was originally developed by the authors. AnyBody is capable of analyzing the musculoskeletal system of humans or other creatures as rigid-body systems. The paper introduces the main features of the system; in particular, the inverse dynamic analysis that resolves the fundamental indeterminacy of the muscle configuration. In addition to the musculoskeletal system, a model can comprise external objects, loads, and motion specifications, thereby providing a complete set of the boundary conditions for a given task. The paper also describes the basic ideas of structured model development in AnyBody. 2006 Elsevier B.V. All rights reserved.

Anatomy and biomechanics of the back muscles in the lumbar spine with reference to biomechanical modeling.

Study Design. This article describes the development of a musculoskeletal model of the human lumbar spine with focus on back muscles. It includes data from literature in a structured form. Objective. To review the anatomy and biomechanics of the back muscles related to the lumbar spine with relevance for biomechanical modeling. Summary of Background Data. To reduce complexity, muscle units have been incorporated in an abridged manner, reducing their actions more or less to a single force equivalent. In early models of the lumbar spine, this may have been a necessary step to reduce complexity and, thereby, calculation time. The muscles of the spine are well described in the literature, but mainly qualitatively. Most of the literature provides a description of the structures without precise data of fiber length, muscle length, cross-sectional areas, moment arms, forces, etc. The predicted output of musculoskeletal models is very much dependent on the input parameters. The information needed to improve models consists of better approximations of the attachments to the vertebrae, and more precise data. Method. Review of literature. Results. The predicted output of musculoskeletal models is very much dependent on the input parameters. Moderate changes in the assumed muscle line-of-action (i.e., moment arm) could substantially alter the magnitudes of predicted muscle and spinal forces, while the choice of optimization formulation is less sensitive. Conclusions. Input parameters, moment arms, as well as physiologic cross-sectional areas have a profound effect on the predicted muscle forces. Therefore, it is important to choose the values for moment arm and physiologic cross-sectional area carefully because they are essential input parameters to biomechanical models.

On validation of multibody musculoskeletal models

We review the opportunities to validate multibody musculoskeletal models in view of the current transition of musculoskeletal modelling from a research topic to a practical simulation tool in product design, healthcare and other important applications. This transition creates a new need for justification that the models are adequate representations of the systems they simulate. The need for a consistent terminology and established standards is identified and knowledge from fields with a more progressed state-of-the-art in verification and validation is introduced. A number of practical steps for improvement of the validation of multibody musculoskeletal models are pointed out and directions for future research in the field are proposed. It is hoped that a more structured approach to model validation can help to improve the credibility of musculoskeletal models.

The variability and complexity of sitting postural control are associated with discomfort

The present investigation examined the variability of sitting postural movement in relation to the development of perceived discomfort by means of linear and nonlinear analysis. Nine male subjects participated in this study. Discomfort ratings, kinetic and kinematics data were recorded during prolonged sitting. Body part discomfort index, displacement of the center of pressure (COP) in anterior-posterior and medial-lateral directions as well as lumbar curvature were calculated. Mean, standard deviation and sample entropy values were extracted from COP and lumbar curvature signals. Standard deviation and sample entropy were used to assess the degree of variability and complexity of sitting. A correlation analysis was performed to determine the correlation of each parameter with discomfort. There were no correlations between discomfort and any of the mean values. On the contrary, the standard deviations of the COP displacement in both directions and lumbar curvature were positively correlated to discomfort, whereas sample entropies were negatively correlated. The present study suggests that the increase in degree of variability and the decrease in complexity of sitting postural control are interrelated with the increase in perceived discomfort. Finally, the present study underlined the importance of quantifying motor variability for understanding the biomechanics of seated posture.

Moment dependency of the series elastic stiffness in the human plantar flexors measured in vivo

The moment dependency of the series elastic stiffness (SES) in the human plantar flexors was investigated in vivo with the quick release method. At an ankle moment of 100 N m produced with either voluntary or electrical stimulation we found non-significantly different SES of 506+/-72 and 529+/-125 N m rad(-1), respectively. It has recently been proposed that the amount of series elastic tissue involved in plantar flexion changes with the moment level produced by the plantar flexors (Hof, J. Biomech 31 (1998) 793). However, our results indicate that the amount of series elastic tissue involved in plantar flexions remained constant with changing moment levels. We therefore propose that the series elastic component (SEC) in human plantar flexors act as one structure or rather one combination of anatomical structures which is engaged at all muscle activation levels, and that the mechanical properties (i.e. the stress-strain function) are determined by the combined tissue mechanical properties. Additionally, our results demonstrated that the SES in the human plantar flexors at moments levels up to about isometric maximum did not reach an asymptote where the stiffness is independent of moment, i.e. SEC of the plantar flexors is, during many daily activities, loaded for the greatest part in the non-linear part of the stress-strain function.

Missing links in pressure ulcer research—An interdisciplinary overview

This paper surveys the literature on the etiology of sitting-acquired deep tissue pressure ulcers from three different viewpoints. The first viewpoint is identification of risk factors related to seated posture. The second viewpoint focuses on the external factors that can cause necrosis to human cells, such as ischemia and compression. The third viewpoint focuses on computational models of the human buttocks to calculate where stress concentrations occur. Each viewpoint contributes to the understanding of pressure ulcer etiology, but in combination they cover the multiple scales from cell to organism, and the combined insight can provide important information toward a full understanding of the phenomenon. It is concluded that the following three questions must be answered by future research. 1) Does compressive stress alone explain cell death, or is it necessary to consider the full three-dimensional strain tensor in the tissues? 2) How does the change in posture-induced load applied on the human buttocks change the stress distribution in the deep muscle tissue? 3) Is it possible to optimize the seated posture in a computational model to reduce the deeper tissue loads?

Scaling of musculoskeletal models from static and dynamic trials

Subject-specific scaling of cadaver-based musculoskeletal models is important for accurate musculoskeletal analysis within multiple areas such as ergonomics, orthopaedics and occupational health. We present two procedures to scale ‘generic’ musculoskeletal models to match segment lengths and joint parameters to a specific subject and compare the results to a simpler approach based on linear, segment-wise scaling. By incorporating data from functional and standing reference trials, the new scaling approaches reduce the model sensitivity to assumed model marker positions. For validation, we applied all three scaling methods to an inverse dynamics-based musculoskeletal model and compared predicted knee joint contact forces to those measured with an instrumented prosthesis during gait. Additionally, a Monte Carlo study was used to investigate the sensitivity of the knee joint contact force to random adjustments of the assumed model marker positions (+/− one marker diameter). The model based on linear scaling showed the highest variation in the knee joint contact force of 1.44 body weight (BW) around contra-lateral heel strike, and a variation in root mean square deviation (RMSD) of 0.36 BW. The proposed methods reduced the variation to 1.0 BW (RMSD 0.26 BW) for the anatomical landmark based method and 0.47 BW (RMSD 0.06 BW) for the functional based method. Variation in model predictions due to uncertainty in marker positions is a trait of all marker-based musculoskeletal modelling approaches. The presented methods solve part of this problem and rely less on manual identification of anatomical landmarks in the model. The work represents a step towards a more consistent methodology in musculoskeletal modelling.

Evaluation of a geometry-based knee joint compared to a planar knee joint

Today neuromuscular simulations are used in several fields, such as diagnostics and planing of surgery, to get a deeper understanding of the musculoskeletal system. During the last year, new models and datasets have been presented which can provide us with more in-depth simulations and results. The same kind of development has occurred in the field of studying the human knee joint using complex three dimensional finite element models and simulations. In the field of musculoskeletal simulations, no such knee joints can be used. Instead the most common knee joint description is an idealized knee joint with limited accuracy or a planar knee joint which only describes the knee motion in a plane. In this paper, a new knee joint based on both equations and geometry is introduced and compared to a common clinical planar knee joint. The two kinematical models are analyzed using a gait motion, and are evaluated using the muscle activation and joint reaction forces which are compared to in-vivo measured forces. We show that we are able to predict the lateral, anterior and longitudinal moments, and that we are able to predict better knee and hip joint reaction forces.

Estimation of Ground Reaction Forces and Moments During Gait Using Only Inertial Motion Capture

Ground reaction forces and moments (GRF&M) are important measures used as input in biomechanical analysis to estimate joint kinetics, which often are used to infer information for many musculoskeletal diseases. Their assessment is conventionally achieved using laboratory-based equipment that cannot be applied in daily life monitoring. In this study, we propose a method to predict GRF&M during walking, using exclusively kinematic information from fully-ambulatory inertial motion capture (IMC). From the equations of motion, we derive the total external forces and moments. Then, we solve the indeterminacy problem during double stance using a distribution algorithm based on a smooth transition assumption. The agreement between the IMC-predicted and reference GRF&M was categorized over normal walking speed as excellent for the vertical (ρ = 0.992, rRMSE = 5.3%), anterior (ρ = 0.965, rRMSE = 9.4%) and sagittal (ρ = 0.933, rRMSE = 12.4%) GRF&M components and as strong for the lateral (ρ = 0.862, rRMSE = 13.1%), frontal (ρ = 0.710, rRMSE = 29.6%), and transverse GRF&M (ρ = 0.826, rRMSE = 18.2%). Sensitivity analysis was performed on the effect of the cut-off frequency used in the filtering of the input kinematics, as well as the threshold velocities for the gait event detection algorithm. This study was the first to use only inertial motion capture to estimate 3D GRF&M during gait, providing comparable accuracy with optical motion capture prediction. This approach enables applications that require estimation of the kinetics during walking outside the gait laboratory.

Prediction of the articular eminence shape in a patient with unilateral hypoplasia of the right mandibular ramus before and after distraction osteogenesis—A simulation study

The aim of this work was to predict the shape of the articular eminence in a patient with unilateral hypoplasia of the right mandibular ramus before and after distraction osteogenesis (DO). Using a patient-specific musculoskeletal model of the mandible the hypothesis that the observed differences in this patient in the left and right articular eminence inclinations were consistent with minimisation of joint loads was tested. Moreover, a prediction was made of the final shape of the articular eminence after DO when the expected remodelling has reached a steady state. The individual muscle forces and the average TMJ loading were computed for each combination of articular eminence angles both before and after DO. This exhaustive parameter study provides a full overview of average TMJ loading depending on the angles of the articular eminences. Before DO the parameter study resulted in different articular eminence inclinations between left and right sides consistent with patient data obtained from CT scans, indicating that in this patient the articular eminence shapes result from minimisation of joint loads. The simulation model predicts development of almost equal articular eminence shapes after DO. The same tendency was observed in cone beam CT scans (NewTom) of the patient taken 6.5 years after surgery.