Characterizing full-body reach duration across task and viewpoint modalities

The full-body control of virtual characters is a promising technique for application fields such as Virtual Prototyping. However it is important to assess to what extent the user full-body behavior is modified when immersed in a virtual environment. In the present study we have measured reach durations for two types of task (controlling a simple rigid shape vs. a virtual character) and two types of viewpoint (1st person vs. 3rd person). The paper first describes the architecture of the motion capture approach retained for the on-line full-body reach experiment. We then present reach measurement results performed in a non-virtual environment. They show that the target height parameter leads to reach duration variation of ∓25% around the average duration for the highest and lowest targets. This characteristic is highly accentuated in the virtual world as analyzed in the discussion section. In particular, the discrepancy observed for the first person viewpoint modality suggests to adopt a third person viewpoint when controling the posture of a virtual character in a virtual environment

A biomechanics-based articulation model for medical applications

Computer Graphics came into the medical world especially after the arrival of 3D medical imaging. Computer Graphics techniques are already integrated in the diagnosis procedure by means of the visual tridimensional analysis of computer tomography, magnetic resonance and even ultrasound data. The representations they provide, nevertheless, are static pictures of the patients' body, lacking in functional information. We believe that the next step in computer assisted diagnosis and surgery planning depends on the development of functional 3D models of human body. It is in this context that we propose a model of articulations based on biomechanics. Such model is able to simulate the joint functionality in order to allow for a number of medical applications. It was developed focusing on the following requirements: it must be at the same time simple enough to be implemented on computer, and realistic enough to allow for medical applications; it must be visual in order for applications to be able to explore the joint in a 3D simulation environment. Then, we propose to combine kinematical motion for the parts that can be considered as rigid, such as bones, and physical simulation of the soft tissues. We also deal with the interaction between the different elements of the joint, and for that we propose a specific contact management model. Our kinematical skeleton is based on anatomy. Special considerations have been taken to include anatomical features like axis displacements, range of motion control, and joints coupling. Once a 3D model of the skeleton is built, it can be simulated by data coming from motion capture or can be specified by a specialist, a clinician for instance. Our deformation model is an extension of the classical mass-spring systems. A spherical volume is considered around mass points, and mechanical properties of real materials can be used to parameterize the model. Viscoelasticity, anisotropy and non-linearity of the tissues are simulated. We particularly proposed a method to configure the mass-spring matrix such that the objects behave according to a predefined Young's modulus. A contact management model is also proposed to deal with the geometric interactions between the elements inside the joint. After having tested several approaches, we proposed a new method for collision detection which measures in constant time the signed distance to the closest point for each point of two meshes subject to collide. We also proposed a method for collision response which acts directly on the surfaces geometry, in a way that the physical behavior relies on the propagation of reaction forces produced inside the tissue. Finally, we proposed a 3D model of a joint combining the three elements: anatomical skeleton motion, biomechanical soft tissues deformation, and contact management. On the top of that we built a virtual hip joint and implemented a set of medical applications prototypes. Such applications allow for assessment of stress distribution on the articular surfaces, range of motion estimation based on ligament constraint, ligament elasticity estimation from clinically measured range of motion, and pre- and post-operative evaluation of stress distribution. Although our model provides physicians with a number of useful variables for diagnosis and surgery planning, it should be improved for effective clinical use. Validation has been done partially. However, a global clinical validation is necessary. Patient specific data are still difficult to obtain, especially individualized mechanical properties of tissues. The characterization of material properties in our soft tissues model can also be improved by including control over the shear modulus

COMBINING MUSCULOSKELETAL MODELING AND FEM IN DIABETIC FOOT PREVENTION

Recently the development of Patient-specific models (PSMs) tailored to patient-specific data, has gained more and more attention in clinical applications. PSMs could represent a solution to the growing awareness of personalized medicine which allow the realization of more effective rehabilitation treatments designed on the subject capabilities. PSMs have the potential of improving diagnosis and optimizing clinical treatments by predicting and comparing the outcomes of different approaches of intervention. Furthermore they can provide information that cannot be directly measured, such as muscle forces or internal stresses and strains of the bones. Given the considerable amount of diseases affecting motor ability, PSMs of the lower limbs have been broadly addressed in literature. Two techniques are mostly used in this area: musculoskeletal (MS) modeling and finite element (FE) analysis. (MS) models represent a valuable tool, as they can provide important information about the unique anatomical and functional characteristics of different subjects, through the computation of human internal variables, such as muscle activations and forces and joint contact forces. The flexibility and adaptability of FE analysis makes it a perfect solution to model biological geometries and materials and to simulate complicated boundary and loading conditions. Accurate and descriptive FE models would serve as an excellent tool for scientific and medical research. Furthermore they could be used in clinical settings if combined with medical imaging, in order to improve patient care. Several 3-dimensional (3D) foot FE models were recently developed to analyze the biomechanical behavior of the human foot and ankle complex that is commonly studied with experimental techniques like stereophotogrammetry, force and plantar pressure plates. In this context, many gait analysis protocols have been proposed to assess the 3D kinetics, kinematics and plantar pressure distribution. This evaluation has shown to be useful in characterizing the foot biomechanics in different pathologies like the diabetic foot. Diabetic foot is an invalidating complication of diabetes mellitus, a chronic disease frequently encountered in the aging population. It is characterize by the development of ulcers which can lead to amputation. Models for simulations of deformations and stresses in the diabetic plantar pad are required to predict high risk areas on the plantar surface and can be used to investigate the performance of different insoles design for optimal pressure relief. This work represents a first effort towards the definition of a more complete PSM which combining both a MS model and a FE model, can increase the understanding of the diabetic foot pathology. To achieve this objective, several limitations and issues have been addressed. As first, MS models of diabetic and control subjects were developed using OpenSim, to estimate muscle forces. The objective was to evaluate whether the diabetic population exhibit lower limb muscle strength deficits compared to the healthy one. Subjects routine gait analysis was performed and lower limb joints kinematics, kinetics, time and space parameters estimated by means of a modified version of the IORgait protocol. 3D lower limb joints kinematics and kinetics was also calculated with OpenSim. Both methodologies were able to highlight differences in joint kinematics and kinetics between the two populations. Furthermore MS models showed significant differences in healthy muscle forces with respect to the diabetic ones, in some of the muscles. This knowledge can help the planning of specific training in order to improve gait speed, balance, muscle strength and joint mobility. After the use of MS models proved to be applicable in the diabetic population, the next step was to combine them with foot FE models. This was done in two phases. At first the impact of applying the foot joints contact forces (JCFs) obtained from MS models as boundary condition on the foot FE models was verified. Subject specific geometries from MRI were used for the development of the foot FE models while the experimental plantar pressures acquired during gait were used in the validation process. A better agreement was found between experimentally measured and simulated plantar pressure obtained with JCFs than with the experimentally measured ground reaction forces as boundary conditions. Afterwards the use of muscles forces as boundary condition in the FE simulations was evaluated. Subject-specific integrated and synchronized kinematic-kinetic data acquired during gait analysis were used for the development of the MS models and for the computation of the muscle forces. Muscle insertions were then located in the MRI and correspondent connectors were created in the FE model. FE subject-specific simulations were subsequently run with Abaqus by conducting a quasi-static analysis on 4 gait cycle phases and adopting 2 conditions: one including the muscle forces and one without. Once again the validation of the FE simulations was done by means of a comparison between simulated and experimentally measured plantar pressures. Results showed a marked improvement in the estimation of the peak pressure for the model that included the muscles. Finally, an attempt towards the definition of a parametric foot finite element model was done. In fact, despite the recent developments, patient-specific models are not yet successfully applied in a clinical setting. One of the challenges is the time required for mesh creation, which is difficult to automate. The development of parametric models by means of the Principle Component Analysis (PCA) can represent an appealing solution. In this study PCA was applied to the feet of a small cohort of diabetic and healthy subjects in order to evaluate the possibility of developing parametric foot models and to use them to identify variations and similarities between the two populations. The limitations of the use of models have also been analyzed. Their adoption is indeed limited by the lack of verification and validation standards. Even using subjects’ MRI or CT data for the development of FEM together with experimentally acquired motion analysis data for the boundary and loading conditions, the subject specifity is still not reached for what regards all the material properties. Furthermore it should be considered that everything relies on algorithm and models that would never be perfectly representing the reality. Overall, the work presented in this thesis represents an extended evaluation of the possible uses of modeling techniques in the diabetic foot prevention, by considering all the limitations introduced as well as the potential benefits of their use in a clinical context. The research is organized in six chapters: Chapter 1 - provides a background on the modeling techniques, both FE modeling and MS modeling. Furthermore it also describes the gait analysis, its instrumentation and some of the protocols used in the evaluation of the biomechanics of the lower limbs; Chapter 2 - gives a detailed overview of the biomechanics of the foot. It particularly focuses on the diabetes and the diabetic foot; Chapter 3 - introduces the application of MSs for the diabetic foot prevention after a brief background on the techniques usually chosen for the evaluation of the motor impairments caused by the disease. Aim, material and methods, results and discussion are presented. The complete work flow is described, and the chapter ends with a discussion on new key findings and limitations. Chapter 4 – reports the work done to combine the use of musculoskeletal models with foot FEMs. At first the impact of applying the foot joints contact forces obtained from MS models as boundary condition on the foot FEMs is verified. Then the use of muscles forces (again obtained from MS models) as boundary condition in the FE simulations is evaluated. For both studies a brief background is presented together with the methods applied, the results obtained and a discussion of novelties and drawbacks. Chapter 5 – explores the possibility of defining a parametric foot FEM applying the Principle Component Analysis (PCA) on the feet of a small cohort of diabetic and healthy subjects. A background on the importance of patient specific models is presented followed by material and methods, results and discussion of what obtained with this study. Chapter 6 - summarizes the results and the novelty of the thesis, delineating the conclusions and the future research paths

Development and Characterization of Velocity Workspaces for the Human Knee.

The knee joint is the most complex joint in the human body. A complete understanding of the physical behavior of the joint is essential for the prevention of injury and efficient treatment of infirmities of the knee. A kinematic model of the human knee including bone surfaces and four major ligaments was studied using techniques pioneered in robotic workspace analysis. The objective of this work was to develop and test methods for determining displacement and velocity workspaces for the model and investigate these workspaces. Data were collected from several sources using magnetic resonance imaging (MRI) and computed tomography (CT). Geometric data, including surface representations and ligament lengths and insertions, were extracted from the images to construct the kinematic model. Fixed orientation displacement workspaces for the tibia relative to the femur were computed using ANSI C programs and visualized using commercial personal computer graphics packages. Interpreting the constraints at a point on the fixed orientation displacement workspace, a corresponding velocity workspace was computed based on extended screw theory, implemented using MATLAB(TM), and visually interpreted by depicting basis elements. With the available data and immediate application of the displacement workspace analysis to clinical settings, fixed orientation displacement workspaces were found to hold the most promise. Significant findings of the velocity workspace analysis include the characterization of the velocity workspaces depending on the interaction of the underlying two-systems of the constraint set, an indication of the contributions from passive constraints to force closure of the joint, computational means to find potentially harmful motions within the model, and realistic motions predicted from solely geometric constraints. Geometric algebra was also investigated as an alternative method of representing the underlying mathematics of the computations with promising results. Recommendations for improving and continuing the research may be divided into three areas: the evolution of the knee model to allow a representation for cartilage and the menisci to be used in the workspace analysis, the integration of kinematic data with the workspace analysis, and the development of in vivo data collection methods to foster validation of the techniques outlined in this dissertation

Medical Robotics

The first generation of surgical robots are already being installed in a number of operating rooms around the world. Robotics is being introduced to medicine because it allows for unprecedented control and precision of surgical instruments in minimally invasive procedures. So far, robots have been used to position an endoscope, perform gallbladder surgery and correct gastroesophogeal reflux and heartburn. The ultimate goal of the robotic surgery field is to design a robot that can be used to perform closed-chest, beating-heart surgery. The use of robotics in surgery will expand over the next decades without any doubt. Minimally Invasive Surgery (MIS) is a revolutionary approach in surgery. In MIS, the operation is performed with instruments and viewing equipment inserted into the body through small incisions created by the surgeon, in contrast to open surgery with large incisions. This minimizes surgical trauma and damage to healthy tissue, resulting in shorter patient recovery time. The aim of this book is to provide an overview of the state-of-art, to present new ideas, original results and practical experiences in this expanding area. Nevertheless, many chapters in the book concern advanced research on this growing area. The book provides critical analysis of clinical trials, assessment of the benefits and risks of the application of these technologies. This book is certainly a small sample of the research activity on Medical Robotics going on around the globe as you read it, but it surely covers a good deal of what has been done in the field recently, and as such it works as a valuable source for researchers interested in the involved subjects, whether they are currently “medical roboticists” or not

Towards the application of multi-DOF EMG-driven neuromusculoskeletal modeling in clinical practice: methodological aspects

New methods able to assess the individual ability of patients to generate motion and adaptation strategies are increasingly required for clinical applications aiming at recovering motor functions. Indeed, more effective rehabilitation treatments are designed to be personalized on the subject capabilities. In this context, neuromusculoskeletal (NMS) models represent a valuable tool, as they can provide important information about the unique anatomical, neurological, and functional characteristics of different subjects, through the computation of human internal variables, such as muscle activations, muscle forces, joint contact forces and moments. A first possible approach is to estimate these values using optimization-based NMS models. However, these models require to make assumptions on how the muscles contribute to the observed movement. More promising are instead NMS models driven by electromyographic signals (EMG), which use experimentally recorded signals that can be considered a direct representation of the subject motor intentions. This allows to account for the actual differences in an individual neuromuscular control system, without making any preliminary assumptions. Therefore these models have the potentialities to provide the level of personalization that is essential for applications in the clinical field. Although EMG-driven NMS models have been investigated in the literature, even for clinical purposes, they are mostly limited to one degree of freedom (DOF), and consider only the muscles spanning that DOF. Additionally, despite the promising results, they are still not introduced in the clinical practice; the main reason possibly being their complexity, that makes them not usable in clinical context, where standard and reliable procedures are required. The importance of EMG-driven NMS modeling for clinical applications would be even higher with the availability of multi-DOF models, as impairments usually compromise multiple joints. Nevertheless, even if a first multi-DOF EMG-driven NMS model for the lower limbs has been recently introduced in literature, its even greater complexity makes more difficult an analysis of its applicability in the clinical field. This work represents a first effort towards a critical analysis of multi-DOF EMG-driven NMS models to evaluate their possible use in clinical practice. To achieve this objective, several issues and limitations have been addressed. In the specific, the attention has been focused on two aspects: (i) making the methodology usable, to foster its adoption by multiple laboratories and research groups, and to facilitate sensitivity analyses required to assess its accuracy; (ii) highlighting the effects of some methodological aspects related to data acquisition and processing, and evaluating their impact on the accuracy of estimated parameters and muscle forces. This analysis is even more important for multi-DOF EMG-driven NMS model as it is still not present in the literature. To accomplish the first goal, a software tool (MOtoNMS) has been developed and it is freely available for the research community. It is a complete, flexible, and user-friendly tool that allows to automatically process experimental motion data from different laboratories in a transparent and repeatable way, for their subsequent use with neuromusculoskeletal modeling software. MOtoNMS generalizes data processing methods across laboratories, and simplifies and speeds up the demanding data elaboration workflow. This simplification represents an indispensable step towards an actual translation of NMS methods in clinical practice. The second part of the work has been, instead, dedicated to analyze the impact on model parameters and muscle forces prediction of different techniques for EMG data collection and processing that are feasible for clinical settings, in particular concentrating on EMGs normalization. Indeed, moving EMG-driven NMS modeling towards clinical applications that deal with multiple DOFs requires to carefully consider subject's motor limitations due to his/her mobility impairments. This results in a rethinking about the methodologies for data acquisition and processing. Therefore, the impact of using only data from walking trials on both calibration of model parameters and computing the maximum EMG values needed for the normalization step, has been assessed with two case studies. Moreover, a protocol for the collection of maximum voluntary contractions has been proposed. This protocol is suitable for multiple DOFs applications involving patients with reduced motor ability and it requires only low-cost and easy to acquire tools to make it applicable in any laboratory. The research proposed in this thesis provides tools to simplify the use of multi-DOF EMG-driven neuromusculoskeletal models and proposes analyses and procedures to evaluate the accuracy and reliability of the obtained results with the aim of pursuing clinical applications

12 Chapters on Nuclear Medicine

The development of nuclear medicine as a medical specialty has resulted in the large-scale application of its effective imaging methods in everyday practice as a primary method of diagnosis. The introduction of positron-emitting tracers (PET) has represented another fundamental leap forward in the ability of nuclear medicine to exert a profound impact on patient management, while the ability to produce radioisotopes of different elements initiated a variety of tracer studies in biology and medicine, facilitating enhanced interactions of nuclear medicine specialists and specialists in other disciplines. At present, nuclear medicine is an essential part of diagnosis of many diseases, particularly in cardiologic, nephrologic and oncologic applications and it is well-established in its therapeutic approaches, notably in the treatment of thyroid cancers. Data from official sources of different countries confirm that more than 10-15 percent of expenditures on clinical imaging studies are spent on nuclear medicine procedures