Upper and Lower Limb Movement Kinematics in Aging

Fragile X-associated tremor/ataxia syndrome (FXTAS) is a neurodegenerative disorder associated with a premutation cytosine-guanine-guanine (CGG) trinucleotide repeat expansion of the FMR1 gene. FXTAS is estimated to be the most common single-gene form of ataxia in the aging population. Gait ataxia and intention tremor are the primary behavioral symptoms of FXTAS, though clinical evaluation of these symptoms often is subjective, contributing to difficulties in reliably differentiating individuals with FXTAS and asymptomatic premutation carriers. This study aimed to clarify the extent to which quantitative measures of gait and upper limb kinematics may serve as biobehavioral markers of FXTAS degeneration. Nineteen premutation carriers (aged 46-77 years), including 9 with possible, probable, or definite FXTAS and 16 sex- and IQ-matched healthy controls, completed tests of non-constrained walking and reaching while both standing (static reaching) and walking (dynamic reaching) to quantify gait and upper limb control, respectively. For the non-constrained walking task, participants wore reflective markers and walked at their preferred speed on a walkway. During the static reaching task, participants reached and lifted boxes of different sizes while standing. During the dynamic reaching task, participants walked to reach and lift the boxes. Movement kinematics were examined in relation to clinical ratings of neuromotor impairments and CGG repeat length. During non-constrained walking, individuals with FXTAS showed decreased stride lengths and stride velocities, increased percentages of double support time, and increased variabilities of cadence and center of mass relative to both asymptomatic premutation carriers and controls. While individuals with FXTAS did not show any static reaching differences relative to the other two groups, they showed multiple differences during dynamic reaching trials, including reduced maximum reaching velocity, prolonged acceleration time, and jerkier movement of the shoulder, elbow, and hand. Gait differences during non-constrained walking were associated with more severe clinically rated posture and gait symptoms. Reduced maximum reaching velocity and increased jerkiness during dynamic reaching were each related to more severe clinically rated kinetic dysfunction and overall neuromotor symptoms in FMR1 premutation carriers. Our findings suggest kinematic alterations consistent with gait ataxia and upper limb bradykinesia are each selectively present in individuals with FXTAS, but not asymptomatic aging premutation carriers. Consistent with neuropathological and magnetic resonance imaging (MRI) studies of FXTAS, these findings implicate cerebellar and basal ganglia degeneration associated with neuromotor decline. Our results showing associations between quantitative kinematic differences in FXTAS and clinical ratings suggest that objective assessments of gait and reaching behaviors may serve as critical and reliable targets for detecting FXTAS risk and monitoring progression

A Hierarchical Architecture for Flexible Human-Robot Collaboration

This thesis is devoted to design a software architecture for Human- Robot Collaboration (HRC), to enhance the robots\u2019 abilities for working alongside humans. We propose FlexHRC, a hierarchical and flexible human-robot cooperation architecture specifically designed to provide collaborative robots with an extended degree of autonomy when supporting human operators in tasks with high-variability. Along with FlexHRC, we have introduced novel techniques appropriate for three interleaved levels, namely perception, representation, and action, each one aimed at addressing specific traits of humanrobot cooperation tasks. The Industry 4.0 paradigm emphasizes the crucial benefits that collaborative robots could bring to the whole production process. In this context, a yet unreached enabling technology is the design of robots able to deal at all levels with humans\u2019 intrinsic variability, which is not only a necessary element to a comfortable working experience for humans but also a precious capability for efficiently dealing with unexpected events. Moreover, a flexible assembly of semi-finished products is one of the expected features of next-generation shop-floor lines. Currently, such flexibility is placed on the shoulders of human operators, who are responsible for product variability, and therefore they are subject to potentially high stress levels and cognitive load when dealing with complex operations. At the same time, operations in the shop-floor are still very structured and well-defined. Collaborative robots have been designed to allow for a transition of such burden from human operators to robots that are flexible enough to support them in high-variability tasks while they unfold. As mentioned before, FlexHRC architecture encompasses three perception, action, and representation levels. The perception level relies on wearable sensors for human action recognition and point cloud data for perceiving the object in the scene. The action level embraces four components, the robot execution manager for decoupling action planning from robot motion planning and mapping the symbolic actions to the robot controller command interface, a task Priority framework to control the robot, a differential equation solver to simulate and evaluate the robot behaviour on-the-fly, and finally a random-based method for the robot path planning. The representation level depends on AND/OR graphs for the representation of and the reasoning upon human-robot cooperation models online, a task manager to plan, adapt, and make decision for the robot behaviors, and a knowledge base in order to store the cooperation and workspace information. We evaluated the FlexHRC functionalities according to the application desired objectives. This evaluation is accompanied with several experiments, namely collaborative screwing task, coordinated transportation of the objects in cluttered environment, collaborative table assembly task, and object positioning tasks. The main contributions of this work are: (i) design and implementation of FlexHRC which enables the functional requirements necessary for the shop-floor assembly application such as task and team level flexibility, scalability, adaptability, and safety just a few to name, (ii) development of the task representation, which integrates a hierarchical AND/OR graph whose online behaviour is formally specified using First Order Logic, (iii) an in-the-loop simulation-based decision making process for the operations of collaborative robots coping with the variability of human operator actions, (iv) the robot adaptation to the human on-the-fly decisions and actions via human action recognition, and (v) the predictable robot behavior to the human user thanks to the task priority based control frame, the introduced path planner, and the natural and intuitive communication of the robot with the human

The Dynamics of Ethical Decision-Making in Business Settings: Some Implications for the Teaching of Ethics in Business Education

This study investigated ethical decision-making in the context of business settings and the teaching of ethics in business education. Over the past century or so, there has been a general acceptance of the need to teach business ethics in business education. However, close scrutiny shows that it has been patchy, and where it has been taught it is often only as an elective. Nevertheless, ethics is important in the business world and unethical behaviour can exact severe punishment. This suggests it should be taught, but that raises questions of how, and on what theoretical basis? For the past half-century, Kohlberg’s developmental theory of moral development has provided the main model in business education, but in the last decade criticisms have come from the social-intuitionist approach and from dynamic systems theory (DST). A dynamic systems approach was used as the main theoretical framework for this study. The adoption of this approach impacted the research methodology of this study and the interpretation of the data. In terms of method, whereas Kohlbergian and similar cognitivist approaches used hypothetical dilemmas in conducting research, this study employed five scenarios that attempt to mirror real-life ethical dilemmas that arise within a business context. Each scenario contained an ethical dilemma, but it was up to the participant to identify it. In terms of the analysis of data, whereas previous approaches applied supposition-laden scoring schemes based on assumed stabilities (e.g., stages and levels) in development, this study attempted to identify emerging and shifting patterns of decision-making in different contexts. Research was undertaken with 16 MBA students enrolled in a business school in a university in Sydney. The findings of this study appear to provide important clues about ethical decision-making, which could be used in future to design alternative pedagogies and teaching materials, when teaching business ethics in the context of business education

The Dynamics of Ethical Decision-Making in Business Settings: Some Implications for the Teaching of Ethics in Business Education

This study investigated ethical decision-making in the context of business settings and the teaching of ethics in business education. Over the past century or so, there has been a general acceptance of the need to teach business ethics in business education. However, close scrutiny shows that it has been patchy, and where it has been taught it is often only as an elective. Nevertheless, ethics is important in the business world and unethical behaviour can exact severe punishment. This suggests it should be taught, but that raises questions of how, and on what theoretical basis? For the past half-century, Kohlberg’s developmental theory of moral development has provided the main model in business education, but in the last decade criticisms have come from the social-intuitionist approach and from dynamic systems theory (DST). A dynamic systems approach was used as the main theoretical framework for this study. The adoption of this approach impacted the research methodology of this study and the interpretation of the data. In terms of method, whereas Kohlbergian and similar cognitivist approaches used hypothetical dilemmas in conducting research, this study employed five scenarios that attempt to mirror real-life ethical dilemmas that arise within a business context. Each scenario contained an ethical dilemma, but it was up to the participant to identify it. In terms of the analysis of data, whereas previous approaches applied supposition-laden scoring schemes based on assumed stabilities (e.g., stages and levels) in development, this study attempted to identify emerging and shifting patterns of decision-making in different contexts. Research was undertaken with 16 MBA students enrolled in a business school in a university in Sydney. The findings of this study appear to provide important clues about ethical decision-making, which could be used in future to design alternative pedagogies and teaching materials, when teaching business ethics in the context of business education

System Qualities Ontology, Tradespace and Affordability (SQOTA) Project – Phase 4

This task was proposed and established as a result of a pair of 2012 workshops sponsored by the DoD Engineered Resilient Systems technology priority area and by the SERC. The workshops focused on how best to strengthen DoD’s capabilities in dealing with its systems’ non-functional requirements, often also called system qualities, properties, levels of service, and –ilities. The term –ilities was often used during the workshops, and became the title of the resulting SERC research task: “ilities Tradespace and Affordability Project (iTAP).” As the project progressed, the term “ilities” often became a source of confusion, as in “Do your results include considerations of safety, security, resilience, etc., which don’t have “ility” in their names?” Also, as our ontology, methods, processes, and tools became of interest across the DoD and across international and standards communities, we found that the term “System Qualities” was most often used. As a result, we are changing the name of the project to “System Qualities Ontology, Tradespace, and Affordability (SQOTA).” Some of this year’s university reports still refer to the project as “iTAP.”This material is based upon work supported, in whole or in part, by the U.S. Department of Defense through the Office of the Assistant of Defense for Research and Engineering (ASD(R&E)) under Contract HQ0034-13-D-0004.This material is based upon work supported, in whole or in part, by the U.S. Department of Defense through the Office of the Assistant of Defense for Research and Engineering (ASD(R&E)) under Contract HQ0034-13-D-0004

Patterned Plantar Stimulation During Gait

It is well established that the soles of the feet are involved and aid in balance control. However, it is not well understood the exact role that the feet play in gait control. During walking, the center of pressure (CoP) takes a predictable and repeated path along the plantar surfaces, going from heel to toe. This CoP has been established to be vital for postural control during standing, the plantar surfaces may perform a similar role during walking by perceiving this CoP path. Most studies use vibro-tactile stimulation on the plantar surfaces during the entire gait cycle, including the swing phase. However, no studies have investigated the effects of different patterns of sequential stimulation on the plantar surfaces during the stance phase of gait. Therefore, the following chapters describe a method of testing this effect, and demonstrating how such patterned plantar stimulation alters gait in healthy young adults. This method of testing was developed such that plantar stimulation would activate specifically during the stance phase of the gait cycle, and activate in a gait-like or an abnormal sequence. We then hypothesized that stimulation in an abnormal sequence would result in gait and balance deficits when compared to stimulation that followed the natural sequence during walking. Additionally, that walking on an inclined surface would increase the effects of the tactile stimulation sequences on such measures when compared with no stimulation. We tested a total of nine healthy adults and found very minimal effects from the stimulation in any pattern. This demonstrates that healthy adults have the ability to adjust and reweigh sensory information from the plantar surfaces such that gait and balance outcomes show minimal or no deficits when foot-sole tactile sensory sequences are manipulated during slow walking. Additionally, that the perception of the CoP movement may be predominately supplied by slow adapting fibers that are not typically sensitive to vibrations. This work gives indication to the flexibility and adaptability of a healthy motor control system and demonstrates a method of testing such a system with an online stimulation control software

Travel behaviour dynamics: a mobility biography study towards change

Travel demand management (TDM) strategies continue to receive attention in recent years as a means of managing congestion in cities and promoting more sustainable transport systems. Most TDM measures focus on effecting travel behaviour change amongst commuters. Clearly such measures are likely to have the greatest impact when targeted at commuters most receptive to changing their travel behaviour at the right time. The study of commuters in order to understand their travel behaviour patterns, when they are most open to change and what causes them to change, is therefore imperative in drawing up effective TDM strategies. Also important is identifying the period within which commuters are deliberating and seeking information in order to change their mode of transport. Many studies have been conducted, in various contexts, to understand the dynamics of travel behaviour change. Some studies have argued travel behaviour to be rational, thus, an individual engage in active deliberation whenever there is a mode use choice decision problem. These studies suggest variability in travel patterns. Other studies have argued travel behaviour to be habitual in nature and characterised by non-deliberative repetition travel decisions. They argued that deliberate reappraisal of travel choices generally occur when triggered by 'key life course events’ or 'life shocks’. Such habitual behaviour suggests fairly stable travel patterns in a city’s transport network. The process through which the individual goes through in making a mode use change decision when triggered by 'key life course events’ however remain largely unexplored. This study, through the use of a qualitative mobility biography survey, firstly investigated the proposition that commuters in Cape Town engage for long periods of time in non-deliberative habitual mode choice behaviour while exhibiting considerable levels of intra-personal variability. These nondeliberative habitual mode use choice behaviours were posited to change when infrequent key life course events or incidents induce deliberation. Average duration between mode use changes among commuters was found to be about six years, confirming the habitual nature of mode use choice - especially among private vehicle users. Variations were, however, found in other attributes of travel choices such as departure time and route choice. Changes in mode use were observed to be in all directions, with the net change over the long-term being from public to private transport - an indication of 'asymmetric churn’. Key life course events found to cause mode use changes included changes in employment, changes in residential location and car ownership. The study then investigated the process a commuter goes through in making mode use changes when experiencing one of these three major life course events. The time when commuters start to deliberate on mode use change and seek information was investigated. Commuters were found to start deliberating on mode use changes and seek information about thirty and twenty-five days before the life course event occurs respectively and stopped about a day after. Information sought after during deliberation included; operational cost, comfort, travel time, convenience of mode use and safety. Commuters, however thought more about what they would gain by changing mode rather than what they would lose. The study concludes by recommending travel demand management strategies to be targeted at commuters that are about to experience a life course event and not after, as it may be too late. Information aimed at changing mode use choices from private to public transport should lay emphasis on what commuters would gain by changing to public transport rather than what they would lose. Information such as travel cost, travel time, convenience, safety, environmental and health impacts may be included in the design of information packs

Analyzing complex data using domain constraints

Data-driven research approaches are becoming increasingly popular in a growing number of scientific disciplines. While a data-driven research approach can yield superior results, generating the required data can be very costly. This frequently leads to small and complex data sets, in which it is impossible to rely on volume alone to compensate for all shortcomings of the data. To counter this problem, other reliable sources of information must be incorporated. In this work, domain knowledge, as a particularly reliable type of additional information, is used to inform data-driven analysis methods. This domain knowledge is represented as constraints on the possible solutions, which the presented methods can use to inform their analysis. It focusses on spatial constraints as a particularly common type of constraint, but the proposed techniques are general enough to be applied to other types of constraints. In this thesis, new methods using domain constraints for data-driven science applications are discussed. These methods have applications in feature evaluation, route database repair, and Gaussian Mixture modeling of spatial data. The first application focuses on feature evaluation. The presented method receives two representations of the same data: one as the intended target and the other for investigation. It calculates a score indicating how much the two representations agree. A presented application uses this technique to compare a reference attribute set with different subsets to determine the importance and relevance of individual attributes. A second technique analyzes route data for constraint compliance. The presented framework allows the user to specify constraints and possible actions to modify the data. The presented method then uses these inputs to generate a version of the data, which agrees with the constraints, while otherwise reducing the impact of the modifications as much as possible. Two extensions of this schema are presented: an extension to continuously valued costs, which are minimized, and an extension to constraints involving more than one moving object. Another addressed application area is modeling of multivariate measurement data, which was measured at spatially distributed locations. The spatial information recorded with the data can be used as the basis for constraints. This thesis presents multiple approaches to building a model of this kind of data while complying with spatial constraints. The first approach is an interactive tool, which allows domain scientists to generate a model of the data, which complies with their knowledge about the data. The second is a Monte Carlo approach, which generates a large number of possible models, tests them for compliance with the constraints, and returns the best one. The final two approaches are based on the EM algorithm and use different ways of incorporating the information into their models. At the end of the thesis, two applications of the models, which have been generated in the previous chapter, are presented. The first is prediction of the origin of samples and the other is the visual representation of the extracted models on a map. These tools can be used by domain scientists to augment their tried and tested tools. The developed techniques are applied to a real-world data set collected in the archaeobiological research project FOR 1670 (Transalpine mobility and cultural transfer) of the German Science Foundation. The data set contains isotope ratio measurements of samples, which were discovered at archaeological sites in the Alps region of central Europe. Using the presented data analysis methods, the data is analyzed to answer relevant domain questions. In a first application, the attributes of the measurements are analyzed for their relative importance and their ability to predict the spatial location of samples. Another presented application is the reconstruction of potential migration routes between the investigated sites. Then spatial models are built using the presented modeling approaches. Univariate outliers are determined and used to predict locations based on the generated models. These are cross-referenced with the recorded origins. Finally, maps of the isotope distribution in the investigated regions are presented. The described methods and demonstrated analyses show that domain knowledge can be used to formulate constraints that inform the data analysis process to yield valid models from relatively small data sets and support domain scientists in their analyses.Datengetriebene Forschungsansätze werden für eine wachsende Anzahl von wissenschaftlichen Disziplinen immer wichtiger. Obwohl ein datengetriebener Forschungsansatz bessere Ergebnisse erzielen kann, kann es sehr teuer sein die notwendigen Daten zu gewinnen. Dies hat häufig zur Folge, dass kleine und komplexe Datensätze entstehen, bei denen es nicht möglich ist sich auf die Menge der Datenpunkte zu verlassen um Probleme bei der Analyse auszugleichen. Um diesem Problem zu begegnen müssen andere Informationsquellen verwendet werden. Fachwissen als eine besonders zuverlässige Quelle solcher Informationen kann herangezogen werden, um die datengetriebenen Analysemethoden zu unterstützen. Dieses Fachwissen wird ausgedrückt als Constraints (Nebenbedingungen) der möglichen Lösungen, die die vorgestellten Methoden benutzen können um ihre Analyse zu steuern. Der Fokus liegt dabei auf räumlichen Constraints als eine besonders häufige Art von Constraints, aber die vorgeschlagenen Methoden sind allgemein genug um auf andere Arte von Constraints angewendet zu werden. Es werden neue Methoden diskutiert, die Fachwissen für datengetriebene wissenschaftliche Anwendungen verwenden. Diese Methoden haben Anwendungen auf Feature-Evaluation, die Reparatur von Bewegungsdatenbanken und auf Gaussian-Mixture-Modelle von räumlichen Daten. Die erste Anwendung betrifft Feature-Evaluation. Die vorgestellte Methode erhält zwei Repräsentationen der selben Daten: eine als Zielrepräsentation und eine zur Untersuchung. Sie berechnet einen Wert, der aussagt, wie einig sich die beiden Repräsentationen sind. Eine vorgestellte Anwendung benutzt diese Technik um eine Referenzmenge von Attributen mit verschiedenen Untermengen zu vergleichen, um die Wichtigkeit und Relevanz einzelner Attribute zu bestimmen. Eine zweite Technik analysiert die Einhaltung von Constraints in Bewegungsdaten. Das präsentierte Framework erlaubt dem Benutzer Constraints zu definieren und mögliche Aktionen zur Veränderung der Daten anzuwenden. Die präsentierte Methode benutzt diese Eingaben dann um eine neue Variante der Daten zu erstellen, die die Constraints erfüllt ohne die Datenbank mehr als notwendig zu verändern. Zwei Erweiterungen dieser Grundidee werden vorgestellt: eine Erweiterung auf stetige Kostenfunktionen, die minimiert werden, und eine Erweiterung auf Bedingungen, die mehr als ein bewegliches Objekt betreffen. Ein weiteres behandeltes Anwendungsgebiet ist die Modellierung von multivariaten Messungen, die an räumlich verteilten Orten gemessen wurden. Die räumliche Information, die zusammen mit diesen Daten erhoben wurde, kann als Grundlage genutzt werden um Constraints zu formulieren. Mehrere Ansätze zum Erstellen von Modellen auf dieser Art von Daten werden vorgestellt, die räumliche Constraints einhalten. Der erste dieser Ansätze ist ein interaktives Werkzeug, das Fachwissenschaftlern dabei hilft, Modelle der Daten zu erstellen, die mit ihrem Wissen über die Daten übereinstimmen. Der zweite ist eine Monte-Carlo-Simulation, die eine große Menge möglicher Modelle erstellt, testet ob sie mit den Constraints übereinstimmen und das beste Modell zurückgeben. Zwei letzte Ansätze basieren auf dem EM-Algorithmus und benutzen verschiedene Arten diese Information in das Modell zu integrieren. Am Ende werden zwei Anwendungen der gerade vorgestellten Modelle vorgestellt. Die erste ist die Vorhersage der Herkunft von Proben und die andere ist die grafische Darstellung der erstellten Modelle auf einer Karte. Diese Werkzeuge können von Fachwissenschaftlern benutzt werden um ihre bewährten Methoden zu unterstützen. Die entwickelten Methoden werden auf einen realen Datensatz angewendet, der von dem archäo-biologischen Forschungsprojekt FOR 1670 (Transalpine Mobilität und Kulturtransfer der Deutschen Forschungsgemeinschaft erhoben worden ist. Der Datensatz enthält Messungen von Isotopenverhältnissen von Proben, die in archäologischen Fundstellen in den zentraleuropäischen Alpen gefunden wurden. Die präsentierten Datenanalyse-Methoden werden verwendet um diese Daten zu analysieren und relevante Forschungsfragen zu klären. In einer ersten Anwendung werden die Attribute der Messungen analysiert um ihre relative Wichtigkeit und ihre Fähigkeit zu bewerten, die räumliche Herkunft der Proben vorherzusagen. Eine weitere vorgestellte Anwendung ist die Wiederherstellung von möglichen Migrationsrouten zwischen den untersuchten Fundstellen. Danach werden räumliche Modelle der Daten unter Verwendung der vorgestellten Methoden erstellt. Univariate Outlier werden bestimmt und ihre möglich Herkunft basierend auf der erstellten Karte wird bestimmt. Die vorhergesagte Herkunft wird mit der tatsächlichen Fundstelle verglichen. Zuletzt werden Karten der Isotopenverteilung der untersuchten Region vorgestellt. Die beschriebenen Methoden und vorgestellten Analysen zeigen, dass Fachwissen verwendet werden kann um Constraints zu formulieren, die den Datenanalyseprozess unterstützen, um gültige Modelle aus relativ kleinen Datensätzen zu erstellen und Fachwissenschaftler bei ihren Analysen zu unterstützen

Hideous Progeny, Dreaming Robots, and the Limits of the Human

This project is an in-depth exploration and synthesis of three different works: novels Frankenstein by Mary Shelley and Do Androids Dream of Electric Sheep by Philip K. Dick, and the movie Bladerunner by Ridley Scott. I will be approaching each story as a separate entity unto themselves yet tie them together through the common lens of a need to explore what it means to be human, the treatment of those that fall outside of the norm, and how that leads to villainous representation. While the negative portrayal of disabled bodies has positively progressed since Frankenstein, this problem continues to endure within both art and society. Art is merely one facet of a larger problem but by close reading novels and film I hope to gain a better understanding at the the ways in which the disabled body is vilified as well as what it will take to move beyond and into a place of acceptance. By applying theoretical perspectives from aesthetic theory, posthumanism, and disability studies, I argue how evolving perceptions of the body impact our definitions of the villainous