Development and validation of a computational multibody model of the elbow joint

Title from PDF of title page, viewed on March 25, 2014Thesis advisor: Trent M. GuessVitaIncludes bibliographical references (pages 71-78)Thesis (M. S.)--School of Computing and Engineering. University of Missouri--Kansas City, 2013Computational multibody models of the elbow joint can provide a powerful tool to study joint biomechanics, examine muscle and ligament function, soft tissue loading, and the effects of joint trauma. Such models can reduce the cost of expensive experimental testing and can predict some parameters that are difficult to investigate experimentally, such as forces within ligaments and contact forces between cartilage covered bones. These parameters can assist surgeons and other investigators to develop better treatments for elbow injuries and thereby increase patient care. Biomechanical computational models of the elbow exist in the literature, but these models are typically limited in their applicability by artificially constraining the joint (e.g. modeling the elbow as a hinge joint), prescribing specific kinematics, simplifying ligament characteristics or ignoring cartilage geometries. The purpose of this thesis was to develop anatomically correct subject specific computational multibody models of elbow joints and validate these models against experimental data. In these models, the joints were constrained by three-dimensional deformable contacts between articulating geometries, passive muscle loading, and multiple bundles of non-linear ligaments wrapped around the bones. In this approach, three-dimensional bone geometries for the model were constructed from volume images generated by computed tomography (CT) scans obtained from cadaver elbows. The ligaments and triceps tendon were modeled as spring-damper elements with non-linear stiffness. Articular cartilage was represented as uniform thickness solids covering the articulating bone surfaces. Finally, the model was validated by placing the cadaver elbows in a mechanical testing apparatus and comparing predicted kinematics and triceps tendon forces to experimentally measured values. A small improvement in predicted kinematics was observed compared to experimental values when the lateral ulnar collateral and annular ligament were wrapped around the bone. Some reductions of RMS error were also observed when a non-linear toe region was modeled in the ligament compared to models that had only a linear force-displacement relationship. None of these changes were statistically significant (ANOVA p-value was greater than 0.05)Abstract -- List of illustrations -- List of tables -- Acknowledgments -- Introduction -- Background -- Methods and materials -- Results -- Discussion -- Appendix -- Reference

Biomechanics

Biomechanics is a vast discipline within the field of Biomedical Engineering. It explores the underlying mechanics of how biological and physiological systems move. It encompasses important clinical applications to address questions related to medicine using engineering mechanics principles. Biomechanics includes interdisciplinary concepts from engineers, physicians, therapists, biologists, physicists, and mathematicians. Through their collaborative efforts, biomechanics research is ever changing and expanding, explaining new mechanisms and principles for dynamic human systems. Biomechanics is used to describe how the human body moves, walks, and breathes, in addition to how it responds to injury and rehabilitation. Advanced biomechanical modeling methods, such as inverse dynamics, finite element analysis, and musculoskeletal modeling are used to simulate and investigate human situations in regard to movement and injury. Biomechanical technologies are progressing to answer contemporary medical questions. The future of biomechanics is dependent on interdisciplinary research efforts and the education of tomorrow’s scientists

Development of an inverse musculoskeletal model of the wrist

The wrist is a complex mechanical system that plays a crucial role in many activities of daily living. Some pathologies that affect the wrist are mechanically instigated or propagated, like osteoarthritis, and can have significant effects on quality of life. The small size of the joint complex precludes some of the investigative techniques that are employed in investigating lower-limb pathology. One way to gain understanding of the biomechanics of the system is to create a computational model to perform investigations that cannot be carried out in vivo. The ambition is to apply an inverse musculoskeletal model of the wrist, previously developed at Imperial College London and implemented using a novel anatomical data set, to answer clinical questions by using biomechanical research to inform intervention. As a key input to the model is joint kinematics, the formation of the joint coordinate system (JCS) used to collect upper limb kinematics was a primary focus of this thesis. The recommendations for building the coordinate system commonly used, published by the International Society of Biomechanics (ISB), are difficult to implement in vivo as they depend on observations only feasible with cadavers. Likewise, the model uses the natural anatomical axes identified by calculating screw displacement axes of passive motions of a cadaveric wrist and thus the axes may differ from axes defined in vivo. Inconsistencies in the relative position and orientation of these axes in the literature raised the question of whether their in vitro definition would match the in vivo definition. A study was conducted to investigate the relative position and orientation of the natural axes of the wrist and to create an alternate joint coordinate system for the wrist using readily palpable anatomical landmarks of the hand and forearm. Participants performed flexion-extension (FE) and radial-ulnar deviation (RUD) motions with their dominant limb, both unrestricted and with a single-plane constraint, as well as pronation- supination (PS) and dart throwing motion. The muscle activities for the flexor digitorum superficialis, flexor carpi ulnaris, flexor carpi radialis, pronator teres, extensor digitorum communis, extensor carpi ulnaris, and extensor carpi radialis were recorded using surface electromyography (EMG). It was determined that defining the axes of the wrist with a prescribed motion pathway produces different results to unconstrained in vivo motion. The mean distance between the unconstrained FE and RUD axes, in the direction of the long axis of the forearm, was 2.5 ± 3.9mm and this was statistically different (p < 0.03) from that of the constrained axes (1.6 ± 4.0mm). The mean angular distance in the plane perpendicular to the long axis of the forearm was 53.2 ± 10.8◦. Again, this was statistically different (p < 0.001) from the constrained axes where the angular difference was 107.8 ± 17.7◦. The distance and angular difference between the constrained FE axis with the unconstrained RUD axis were similar to those documented in the literature. This suggests that the reason for the inconsistencies is that the motions were performed in different ways, rather than that they resulted from anatomical differences. Proposed alternate joint coordinate systems were compared to the ISB recommended system. Landmark palpation repeatability, axes direction repeatability, and amount of secondary rotation (e.g. rotation in RUD and PS axes during FE) were the metrics used to compare the systems. No difference was found between the ISB recommended JCS and those created as part of the study in any of the three metrics. This means that, for the given metrics, the proposed JCSs performed as well as the ISB recommended system and thus could be used instead, making the quantification of kinematics more feasible in a clinical setting. As a result, I recommend that an alternate JCS that uses the medial and lateral epicondyles, radial and ulnar styloids, the base of the third metacarpal, and the heads of the second and fifth metacarpal is used for in vivo clinical and research use. EMG signals were normalised by activity during maximal voluntary contraction (MVC) of the observed muscles. Nine tasks, selected from the literature, were performed and the task most likely to elicit MVC in each muscle was noted. The non-dominant limb was also investigated to determine whether dominance had an effect on the task most likely to elicit MVC. Dominance had limited effect with statistical differences being found only in the finger flexors and extensors (p < 0.031). Tasks most likely to elicit MVC were identified for each muscle. These results can be used to produce MVC protocols tailored to the muscles being investigated, can help check for crosstalk during electrode placement, and show that limb dominance needs to be considered when recording EMG for the finger muscles. The collected MVCs were used to normalise the EMG data that are presented in the thesis. It was found that the EMG pattern for each participant was statistically different from the others (p< 0.001) meaning that each individual employs a unique neuromuscular control algorithm for motions of the wrist. The primary differences were levels of co-contraction. This was consistent within the participants’ trials which suggests that there may be an anatomical reason for the level of co-contraction as this would be unique to each participant. The EMG data were also used to validate a musculoskeletal model of the wrist, previously developed at Imperial College, for in vivo applications. The kinematics for each participant were input into the model and the muscle forces were calculated. Simulated muscle activity was then calculated by normalising the muscle force by the maximum muscle force for each muscle. Five simulated muscle activities could be compared with the EMG data. The simulated muscle activity patterns matched the recorded EMG patterns both qualitatively and quantitatively, using statistical parameter mapping. No statistical difference was found between the recorded and simulated muscle activity. Thus the model is considered to be valid for predicting muscle activity during in vivo motion of the wrist. Though there was poor correlation between the model results and the EMG (r |0.65|), with the model producing the pattern with the smaller magnitude. It is hypothesised that this is again due to the lack of co-contraction, as agonist muscles would need to be more active to counter the forces generated by antagonists. Thus a JCS for the wrist that is employable in a clinical setting and performs as well as the ISB JCS has been identified; muscle activation patterns for the wrist have been identified; and the Imperial College London wrist model has been validated for in vivo use.Open Acces

A Biomechanical Investigation of Load Sharing at the Distal Forearm

Loading at the distal forearm has been previously examined under static loads, however there remains no consensus on how loading is affected by active wrist and forearm motion. This work examines load magnitudes and load sharing at the distal radius and ulna during of active wrist and forearm motion. Two instrumented implants were designed to measure in vitro loading in cadaveric specimen. The implants were evaluated and found reliable for use in further biomechanical studies. An in vitro study investigated the effect of joint angle and direction of joint motion on loads in the distal radius and ulna during active flexion-extension, radioulnar deviation and dart throw motion. Loads through the distal radius and ulna were significantly greater in extension and reverse dart throw motion than in flexion and forward dart throw motion. A subsequent study examined the effect of radial length changes, joint angle and direction of motion on distal radius and ulna loading during active forearm rotation. Load magnitudes through the distal radius were greater in supination than in pronation. Radial lengthening found to increase radial loading and decrease ulnar loading and radial shortening decreased distal radius loading and increased distal ulna loading throughout forearm rotation, in a quasilinear fashion. This work improves the understanding of forearm bone loading and will assist clinicians in the development of rehabilitation techniques, surgical protocols and implant designs

Measuring elbow kinematics in cricket bowling

In the sport of cricket the objective of the ‘no-ball’ law is to allow no performance advantage through elbow extension during ball delivery. Since the advent of high-speed video photography it has been revealed that some straightening occurs in bowlers who have actions that are traditionally considered in accordance with the law. Measuring the three-dimensional movement of the elbow is vital when assessing bowling legality in cricket. However, the elbow joint is a complex structure with a remarkable range of motion and tracking its movement through skin-based techniques can be highly erroneous due to the thick layer of skin overlying the joint. Within this work, a biomechanical model was mathematically developed and experimentally validated to assess bowling legality in cricket. The new model meets all of the specifications of a measurement method to be used in sports-related biomechanical studies for non-invasive measurement of joint kinematics at high speeds whilst allowing for the subject to move freely within a large volume. The model was compared with existing methods via a series of sensitivity analyses and was found to significantly improve repeatability compared to available elbow measurement techniques particularly in measuring subtle elbow rotations, such as elbow abduction and forearm pronation. In addition this model can be easily implemented within the existing experimental protocol for assessing bowling legality in cricket as proposed by the England and Wales Cricket Board and will be used in future clinical and sport-related studies

An Improved 2DOF Elastokinematic Surrogate Model for Continuous Motion Prediction and Visualisation of Forearm Pro-and Supination for Surgical Planning

Forearm rotation (pro-/supination) involves a non-trivial combination of rotation and translation of two bones, namely, radius and ulna, relatively to each other. Early works regarded this relative motion as a rotation about a fixed (skew) axis. However, this assumption turns out not to be exact. This thesis regards a spatial-loop surrogate mechanism involving two degrees of freedom with an elastic coupling for better forearm motion prediction. In addition, the influence of the bone morphology and position of elbow on kinematics are also considered. The model parameters are not measured directly from the anatomical components, but are fitted by reducing the errors between predicted and measured values in an optimization loop. For non-invasive measurement of bone position, magnetic resonance imaging (MRI) is employed. We present a method to self-calibrate the arm position in the MRI scanning tube and to fit the model parameters from a few, coarse MRI scans. Results show a good concordance between measurement and simulation. Moreover, the minimum distance changing between bones during forearm rotation is elucidated, which is not yet proved in anatomical and clinical literatures. The minimum distance is calculated by searching for the global shortest distance between bone contours on ulna and radius by a two-level selection and a following multidimensional Newton-Raphson algorithm. To this end, the methodology is extended from healthy bones to deformed arms and an angulated forearm model is developed. The 3D angulated bone geometry is obtained by manually separating the bone structure at the broken position, and the minimum distance and the range of motion of fractured forearms are analyzed. As shown for a single case validation, simulated results show very small deviations from anatomical data. Furthermore, the simulations discussed above are visualized using interactive interfaces, which facilitates the application of the model in clinical planning.Die Unterarmrotation beinhaltet eine nicht triviale Kombination einer Rotation und Translokation zweier Knochen, Radius und Ulna relativ zu einander. Frühere Arbeiten betrachteten diese relative Bewegung als eine Rotation um eine fixierte Achse. Allerdings scheint diese Annahme ungenau zu sein. Diese Arbeit betrachtet ein Spatial-Loop Surrogat Mechanismus unter Berücksichtigung von zwei Freiheitsgraden mit einer elastischen Gelenkverbindung für eine bessere Prognose der Unterarm-Bewegung. Zusätzlich wird der Einfluss der Knochenmorphologie und die Position des Ellenbogens auf die Kinematik berücksichtig. Die Modellparameter werden nicht direkt von den anatomischen Komponenten bestimmt, sondern unter Berücksichtigung der Abweichung von Annahme und Messung. Zur nicht invasiven Messung der Knochenposition wird die Methode der Magnetresonanztomographie (MRT) angewendet. Wir stellen hier eine Methode um die Arm-Position in das MRI Scan-Rohr selbst zu kalibrieren und die Modellparameter aus einige grobe MRT-Aufnahmen zu passen. Die simulierten Ergebnisse zeigen sehr kleine Abweichungen von anatomischen Daten. Eine minimale Änderung der Distanz zwischen den Knochen während der Unterarmrotation wird beleuchte, die bisher nicht in der anatomischen und klinischen Literatur beschrieben ist. Die Berechnung der minimalen Distanz erfolgt über die Ermittlung der gesamt kürzesten Distanz. Zu diesem Zweck wird die Methodik von gesunden Knochen auf deformiere Arme und ein angewinkeltes Unterarmmodel entwickelt. Die 3D gewinkelte Knochen-Geometrie ergibt sich aus der Knochenstruktur an der gebrochener Position manuell zu trennen, und darauf werden der Mindestabstand und der Bereich der Bewegung von dem gebrochenen Unterarm analysiert. Wie dies bei einer einzelnen Fall Validierung, zeigen die simulierten Ergebnisse sehr kleine Abweichungen von anatomischen Daten. Darüber hinaus werden die oben beschrieben Simulationen mit interaktiven Benutzeroberflächen visualisiert, welche die Anwendung des Modells in der klinischen Planung erleichtert

A Closed-Loop EMG-Assisted Shoulder Model

The human shoulder is a complex musculoskeletal system. Knowledge about its kinematics and dynamics can help improve associated treatments. However, to date direct measurements of these quantities can be only granted through invasive investigations or expensive imaging techniques. Musculoskeletal shoulder models provide useful predictions of shoulder kinematics and dynamics. Nevertheless, there remain significant gaps between the model predictions and behaviors of the real system. This thesis aims at extending an existing shoulder musculoskeletal model for patient-specific clinical applications. To this end, number of improvements are considered. The initial model only considered an outstretch arm. Therefore, the elbow and the muscles spanning it are added in the extended model. To this end, the bone morphologies of the ulna and the radius and muscles architectures are obtained from MRI scans. The elbow is modeled using two hinge joints replicating its flexion/extension and pronation/supination motions. The model is developed based on anthropometric data of a single subject. Given anthropometric variabilities among subjects, it cannot predict inter-individual differences. Therefore, scaling routines are developed to scale the model to a specific subject. The model's bone segment inertial properties, skeletal morphologies, and muscles architectures are scaled according to any specific subject. The effects of anthropometric parameters on glenohumeral (GH) joint reaction force predictions are evaluated. Humeral head translations (HHT) play a crucial role in the GH joint functions. Given that the model is developed based on inverse dynamics, it falls short of predicting the HHT. Therefore, a framework is developed allowing forward-dynamics simulation of the model with a six DOF GH joint. A deformable articular contact is included in the framework defining the GH joint contact force in terms of the joint rotations and translations. A videogrammetry systems is used for recording upper extremity motions. It measures trajectories of skin-fixed markers. However, it cannot practically track scapula motions and the GH joint center. Therefore, a method is developed estimating the GH joint center and consequently scapula motions. Multi-segment optimization is used to reconstruct the measured motions in terms of joints angles. A musculotendon model is a key component for muscle-driven applications of the model. A Hill-type musculotendon model is developed. However, the initial state of the Hill-type model is not provided. Therefore, singular perturbation analysis is used to propose a method providing an initial state for the developed Hill-type model. Given that the model is over-actuated, an optimal load-sharing is used to predict muscle forces. It overlooks antagonistic muscle co-contractions. However, muscle co-contractions play crucial roles in the GH joint stability. Therefore, the load-sharing is modified such that measured electromyography (EMG) data can be incorporated. It is hypothesized that inclusions of the measured EMG can improve model predictions of muscle co-contractions. The developed model provides predictions of joints angles, muscles forces, and GH joint force and translations that are in good agreements with in vivo studies. It could be populated with pre/post operative patients of total shoulder arthroplasty to answer clinical questions regarding treatments of GH joint osteoarthritis

Development of a feedback-controlled elbow simulator: design validation and clinical application

This work involves three topics that advance the functionality of an elbow simulator in the Orthopaedic Biomechanics Laboratory at Allegheny General Hospital. To draw clinically and scientifically meaningful conclusions from future cadaver studies conducted with the simulator, its design must be validated and the accuracy of the data collection methods demonstrated. The simulator was designed to offer physiologically-correct adjustable moment arms throughout the elbow's range of motion. To validate this, muscle moment arms were measured in three cadaver elbow specimens. Flexion-extension moment arms were measured at three different pronation/supination angles: fully pronated, fully supinated, and neutral. Pronation-supination moment arms for four elbow muscles were measured at three different flexion-extension angles: 30°, 60°, and 90°. The numeric results compared well with those previously reported. The biceps and pronator teres flexion-extension moment arms varied with pronation-supination position, and vice versa. This represents the first use of closed-loop feedback control in an elbow simulator, one of the first reports of both flexion-extension and pronation-supination moment arms in the same specimens, and demonstrates the adjustability of the moment arms that the elbow simulator can produce.Towards accurate motion analysis of the radial head, two areas were investigated. The first identified the phenomena of camera-switching, which occurs in motion analysis when data from one or more cameras is temporarily excluded from the computation of a marker's three-dimensional position. Tests with static markers showed that camera-switching could cause up to 3.7 mm of perceived movement. The second area of investigation set the stage for future studies with cadaver elbows. A protocol was developed to quantify both the travel of the native radial head, radial head implants, and the finite helical axis during pronation-supination movement. The tracking of implant motion employs a unique circle-fitting algorithm to determine the implant's center. A video-based motion analysis system was used to collect marker position coordinates actuated by a precision micrometer table. MATLAB code was designed and implemented to compute both the radial head position and finite helical axis from these data. Immediate future work will use these algorithms to evaluate radial head implants in comparison to the native radial head

Building a Bird: Musculoskeletal Modeling and Simulation of Wing-Assisted Incline Running during Avian Ontogeny

Flapping flight is the most power-demanding mode of locomotion, associated with a suite of anatomical specializations in extant adult birds. In contrast, many developing birds use their forelimbs to negotiate environments long before acquiring “flight adaptations,” recruiting their developing wings to continuously enhance leg performance and, in some cases, fly. How does anatomical development influence these locomotor behaviors? Isolating morphological contributions to wing performance is extremely challenging using purely empirical approaches. However, musculoskeletal modeling and simulation techniques can incorporate empirical data to explicitly examine the functional consequences of changing morphology by manipulating anatomical parameters individually and estimating their effects on locomotion. To assess how ontogenetic changes in anatomy affect locomotor capacity, we combined existing empirical data on muscle morphology, skeletal kinematics, and aerodynamic force production with advanced biomechanical modeling and simulation techniques to analyze the ontogeny of pectoral limb function in a precocial ground bird (Alectoris chukar). Simulations of wing-assisted incline running (WAIR) using these newly developed musculoskeletal models collectively suggest that immature birds have excess muscle capacity and are limited more by feather morphology, possibly because feathers grow more quickly and have a different style of growth than bones and muscles. These results provide critical information about the ontogeny and evolution of avian locomotion by (i) establishing how muscular and aerodynamic forces interface with the skeletal system to generate movement in morphing juvenile birds, and (ii) providing a benchmark to inform biomechanical modeling and simulation of other locomotor behaviors, both across extant species and among extinct theropod dinosaurs

Computer simulation of one-handed backhand groundstrokes in tennis

A subject-specific, torque-driven, 3D computer simulation model with eight segments was developed to investigate the effects of different variables belonging to the racket and player on the wrist and elbow loadings in one-handed tennis backhand groundstrokes. Wobbling masses were included to represent soft tissue movement. The string-bed was represented by nine-point masses connected to each other and the racket frame with elastic springs. There were twelve rotational degrees of freedom: three at the shoulder, two at the elbow, two at the wrist, three at the grip and two between the racket handle and racket head. Seven pairs of torque generators were used to control (via activation profiles) the joint angle changes in the model. An elite player was chosen to perform consistent and high standard backhand topspin strokes and a Vicon System was used to record the performances. [Continues.