Clinical decisions based on gait data obtained by optoelectronic motion capturing require profound knowledge about the repeatability of the used measurement systems and methods. The purpose of this study was to evaluate the effects of inconsistent anthropometric measurements on joint kinematics calculated with the Plug-in Gait model. Therefore, a sensitivity study was conducted to ascertain how joint kinematics output is affected to different anthropometric data input. One previously examined gait session of a healthy male subject and his anthropometric data that were assessed by two experienced examiners served as a basis for this analytical evaluation. This sensitivity study yielded a maximum difference in joint kinematics by the two sets of anthropometrics of up to 1.2°. In conclusion, this study has shown that the reliability of subjects’ anthropometrics assessed by experienced examiners has no considerable effects on joint kinematics.

I use temporal lidar and radar to reveal fault rupture kinematics and to test a method of mapping earthquake-induced structural damage. Using pre- and post-event data, these applications of remote technology offer unique perspectives of earthquake effects. Lidar point clouds can produce high resolution, three-dimensional terrain maps, so subtle landscape shifts can be discerned through temporal analysis, providing detailed imagery of co-seismic ground displacement and faulting. All-weather radar systems record back-scattered signal amplitude and phase. Pre- and post-event comparisons of phase can illuminate co-seismic structural damage using an oblique look angle, most sensitive to changes in building heights. Extracted information from these geodetic methods may be used to inform decisions on future earthquake modeling and emergency response. In the first major section of this thesis, I calculate co-seismic 3D ground deformation produced by the Papatea fault using differential lidar. I demonstrate that this fault - a key element within the 2016 Mw 7.8 Kaikoura earthquake - has a distinctly non-planar geometry, far exceeded typical co-seismic slip-to-length ratios, and defied Andersonian mechanics by slipping vertically at steep angles. Its surface deformation is poorly reproduced by elastic dislocation models, suggesting the Papatea fault did not release stored strain energy as typically assumed, perhaps explaining its seismic quiescence in back-projections. Instead, it slipped in response to neighboring fault movements, creating a localized space problem, accounting for its anelastic deformation field. Thus, modeling complex, multiple-fault earthquakes as slip on planar faults embedded in an elastic medium may not always be appropriate. For the second major part of this thesis, I compare mean values of interferometric synthetic aperture radar (InSAR) coherence change across four case studies of earthquake-induced building damage. These include the 2016 Amatrice earthquake, the 2017 Puebla-Morelos earthquake, the 2017 Sarpol-e-Zahab earthquake, and the 2018 Anchorage earthquake. I examine the influences of environmental and urban characteristics on co-seismic coherence change using Sentinel-1 imagery and compare the outcomes of various damage levels. I do not find consistent values of mean coherence change to distinguish levels of damage across the case studies, indicating coherence change values vary with location, environment, and damage pattern. However, this method of damage mapping shows potential as a useful tool in earthquake emergency response, capable of quickly identifying localized areas of high damage in areas with low snow and vegetation cover. Given the large spatial coverage and relatively quick, low-cost acquisition of SAR imagery, this method could provide damage estimates for unsafe or remote regions or for areas unable to self-report damage. / Graduate

Brain-machine interfaces (BMIs) are the only currently viable means of communication for many individuals suffering from locked-in syndrome (LIS) – profound paralysis that results in severely limited or total loss of voluntary motor control. By inferring user intent from task-modulated neurological signals and then translating those intentions into actions, BMIs can enable LIS patients increased autonomy. Significant effort has been devoted to developing BMIs over the last three decades, but only recently have the combined advances in hardware, software, and methodology provided a setting to realize the translation of this research from the lab into practical, real-world applications. Non-invasive methods, such as those based on the electroencephalogram (EEG), offer the only feasible solution for practical use at the moment, but suffer from limited communication rates and susceptibility to environmental noise. Maximization of the efficacy of each decoded intention, therefore, is critical. This thesis addresses the challenge of implementing a BMI intended for practical use with a focus on an autonomous assistive robot application. First an adaptive EEG- based BMI strategy is developed that relies upon code-modulated visual evoked potentials (c-VEPs) to infer user intent. As voluntary gaze control is typically not available to LIS patients, c-VEP decoding methods under both gaze-dependent and gaze- independent scenarios are explored. Adaptive decoding strategies in both offline and online task conditions are evaluated, and a novel approach to assess ongoing online BMI performance is introduced. Next, an adaptive neural network-based system for assistive robot control is presented that employs exploratory learning to achieve the coordinated motor planning needed to navigate toward, reach for, and grasp distant objects. Exploratory learning, or “learning by doing,” is an unsupervised method in which the robot is able to build an internal model for motor planning and coordination based on real-time sensory inputs received during exploration. Finally, a software platform intended for practical BMI application use is developed and evaluated. Using online c-VEP methods, users control a simple 2D cursor control game, a basic augmentative and alternative communication tool, and an assistive robot, both manually and via high-level goal-oriented commands.

Aim: The intention of this study was to examine whether different brands and models of skating boots differently affect the kinetic and kinematic properties of a landing impact from a jump. The differences were tested between new figure skating boots Graf Edmonton, new Edea Concerto and old used Graf Edmonton. Method: Subjects simulated a figure skating jump landing by landing from a counter movement jump off boxes of two different heights onto artificial ice in the Biomechanics and Motor Control (BMC) laboratory. During these jumps the subjects wore figure skating boots of different age and types. Landing impacts were examined by Qualisys motion capture system, Kistler force plate and Pedar-X in-shoe force and pressure measuring system. Each subject acted as his own control for comparison of kinetic and kinematic variables between the skates. Statistical comparison was carried out in SPSS. Results: The research results indicate that the kinetic and kinematic properties of a landing impact significantly (P≤0.05) differed depending on the tested skates. Significant differences were found between new Graf Edmonton and old used Graf Edmonton, between new Graf Edmonton and new Edea Concerto as well as between old used Graf Edmonton and new Edea Concerto. Conclusions: The first research hypothesis was accepted, indicating that reduced vertical ground reaction force (VGRF) acted in new Edea Concerto compared to new and old, used Graf Edmonton boots. The second research hypothesis was rejected since the VGRF acting during the landing impact in old, used Graf Edmonton was greater compared to new Edea Concerto and there was no significant difference compared to new Graf Edmonton boots. The differences between the figure skating boots found in this research are suggested to be caused by different construction designs and materials used in the skates. / <p>Kursen Projektarbete.</p>

abstract: Falls are the leading cause of fatal and non-fatal injuries in the older adult population with more than 27,000 fall related deaths reported every year[1]. Adults suffering from lower extremity arthritis have more than twice the likelihood of experiencing multiple falls resulting in increased fall-related injuries compared to healthy adults. People with lower extremity end-stage osteoarthritis(KOA), experience a number of fall risk factors such as knee instability, poor mobility, and knee pain/stiffness. At end-stage knee OA, the space between the bones in the joint of the knee is significantly reduced, resulting in bone to bone frictional wearing causing bone deformation. In addition, an impaired stepping response during a postural perturbation is seen in people with OA related knee instability. The most common treatment for end-stage knee osteoarthritis is a surgical procedure called, total knee replacement (TKR). It is known that TKR significantly reduces pain, knee stiffness, and restores musculoskeletal functions such as range of motion. Despite studies concluding that knee OA increases fall-risk, it remains unknown if standard treatments, such as TKR, can effectively decrease fall-risk. Analyzing the compensatory step response during a fall is a significant indicator of whether a fall or a recovery will occur in the event of a postural disturbance and is key to determining fall risk among people. Studies have shown reduced trunk stability and step length, as well as increased trunk velocities, correspond to an impaired compensatory step. This study looks at these populations to determine whether TKR significantly enhances compensatory stepping response by analyzing trunk velocities and flexions among other kinematic/kinetic variable analysis during treadmill induced perturbations and clinical assessments. / Dissertation/Thesis / Masters Thesis Biomedical Engineering 2019

Most of work on motion of mobile robots is to generate plans for avoiding obstacles or perform some meaningful and useful actions. In modern robot theatres and entertainment robots the motions of the robot are scripted and thus the performance or behavior of the robot is always the same. In this work we want to propose a new approach to robot motion generation. We want our robot to behave more like real people. People do not move in mechanical way like robots. When a human is supposed to execute some motion, these motions are similar to one another but always slightly or not so slightly different. We want to reproduce this property based on the introduced by us new concept of probabilistic regular expression, a method to describe sets of interrelated similar actions instead of single actions. Our goal is not only to create motions for humanoid robots that will look more naturally and less mechanically, but also to program robots that will combine basic movements from certain library in many different and partially random ways. While the basic motions were created ahead of time, their combinations are specified in our new language. Although now our method is only for motions and does not take inputs from sensors into account, in future the language can be extended to input/output sequences, thus the robot will be able to adapt the motion in different ways, to some sets of sequences of input stimuli. The inputs will come from sensors, possibly attached to limbs of controlling humans from whom the patterns of motion will be acquired.

Cette thèse présente une approche de modélisation inspirée par la robotique pour l'étude des changements conformationnels des protéines. Cette approche est basée sur une représentation mécanistique des protéines permettant l'application de méthodes efficaces provenant du domaine de la robotique. Elle fournit également une méthode appropriée pour le traitement « gros-grains » des protéines sans perte de détail au niveau atomique. L'approche présentée dans cette thèse est appliquée à deux types de problèmes de simulation moléculaire. Dans le premier, cette approche est utilisée pour améliorer l'échantillonnage de l'espace conformationnel des protéines. Plus précisément, cette approche de modélisation est utilisée pour implémenter des classes de mouvements pour l'échantillonnage, aussi bien connues que nouvelles, ainsi qu'une stratégie d'échantillonnage mixte, dans le contexte de la méthode de Monte Carlo. Les résultats des simulations effectuées sur des protéines ayant des topologies différentes montrent que cette stratégie améliore l'échantillonnage, sans toutefois nécessiter de ressources de calcul supplémentaires. Dans le deuxième type de problèmes abordés ici, l'approche de modélisation mécanistique est utilisée pour implémenter une méthode inspirée par la robotique et appliquée à la simulation de mouvements de grande amplitude dans les protéines. Cette méthode est basée sur la combinaison de l'algorithme RRT (Rapidly-exploring Random Tree) avec l'analyse en modes normaux, qui permet une exploration efficace des espaces de dimension élevée tels les espaces conformationnels des protéines. Les résultats de simulations effectuées sur un ensemble de protéines montrent l'efficacité de la méthode proposée pour l'étude des transitions conformationnelles / Proteins are biological macromolecules that play essential roles in living organisms. Un- derstanding the relationship between protein structure, dynamics and function is indis- pensable for advances in fields such as biology, pharmacology and biotechnology. Study- ing this relationship requires a combination of experimental and computational methods, whose development is the object of very active interdisciplinary research. In such a context, this thesis presents a robotics-inspired modeling approach for studying confor- mational changes in proteins. This approach is based on a mechanistic representation of proteins that enables the application of efficient methods originating from the field of robotics. It also provides an accurate method for coarse-grained treatment of proteins without loosing full-atom details.The presented approach is applied in this thesis to two different molecular simulation problems. First, the approach is used to enhance sampling of the conformational space of proteins using the Monte Carlo method. The modeling approach is used to implement new and known Monte Carlo trial move classes as well as a mixed sampling strategy. Results of simulations performed on proteins with different topologies show that this strategy enhances sampling without demanding higher computational resources. In the second problem tackled in this thesis, the mechanistic modeling approach is used to implement a robotics-inspired method for simulating large amplitude motions in proteins. This method is based on the combination of the Rapidly-exploring Random Tree (RRT) algorithm with Normal Mode Analysis (NMA), which allows efficient exploration of the high dimensional conformational spaces of proteins. Results of simulations performed on ten different proteins of different sizes and topologies show the effectiveness of the proposed method for studying conformational transitions

Indiana University-Purdue University Indianapolis (IUPUI) / Khakpour, Zahra M.S.M.E., Purdue University, May 2017. Multibody Dynamics Model of A Full Human Body For Simulating Walking, Major Professor: Hazim El-Mounayri. Bipedal robotics is a relatively new research area which is concerned with creating walking robots which have mobility and agility characteristics approaching those of humans. Also, in general, simulation of bipedal walking is important in many other applications such as: design and testing of orthopedic implants; testing human walking rehabilitation strategies and devices; design of equipment and facilities for human/robot use/interaction; design of sports equipment; and improving sports performance & reducing injury. One of the main technical challenges in that bipedal robotics area is developing a walking control strategy which results in a stable and balanced upright walking gait of the robot on level as well as non-level (sloped/rough) terrains. In this thesis the following aspects of the walking control strategy are developed and tested in a high-fidelity multibody dynamics model of a humanoid body model: 1. Kinematic design of a walking gait using cubic Hermite splines to specify the motion of the center of the foot. 2. Inverse kinematics to compute the legs joint angles necessary to generate the walking gait. 3. Inverse dynamics using rotary actuators at the joints with PD (Proportional-Derivative) controllers to control the motion of the leg links. The thee-dimensional multibody dynamics model is built using the DIS (Dynamic Interactions Simulator) code. It consists of 42 rigid bodies representing the legs, hip, spine, ribs, neck, arms, and head. The bodies are connected using 42 revolute joints with a rotational actuator along with a PD controller at each joint. A penalty normal contact force model along with a polygonal contact surface representing the bottom of each foot is used to model contact between the foot and the terrain. Friction is modeled using an asperity-based friction model which approximates Coulomb friction using a variable anchor-point spring in parallel with a velocity dependent friction law. In this thesis, it is assumed in the model that a balance controller already exists to ensure that the walking motion is balanced (i.e. that the robot does not tip over). A multi-body dynamic model of the full human body is developed and the controllers are designed to simulate the walking motion. This includes the design of the geometric model, development of the control system in kinematics approach, and the simulation setup.

Title: Measurement and analysis of postural stability and movement patterns of persons after transfemoral amputation. Objectives: The aim of this work is to understand the compensatory mechanisms arising after femoral amputation and to find out what effect the lenght of amputation has on movement patterns in humans after transfemoral amputation and exarticulation in the knee joint. Methods: In my work I used the method of analysis and method of comparison. For the analysis of postural stability, I used standard tools: force plates (Kistler 9286A) and motion recording system (Kistler 9286A). To compare kinematic one-dimensional data, I used the technique of statistical parametric mapping, which is a generalization of classical statistical tests from scalar to one-dimensional data. 8 probands with transfemoral amputation participated in the study. Three successful attempts were recorded, at three speeds with the contact of a residual and amputated limb. The movement of the pelvis in the horizontal, sagittal, transverse planes and the time spent on a residual limb were analyzed. Results: We found that the length of amputation significantly effects postural stability and movement patterns. It was found that the shorter the amputation stump, the less stable the gait, with greater deviations in the...

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