An inertial motion capture framework for constructing body sensor networks

Motion capture is the process of measuring and subsequently reconstructing the movement of an animated object or being in virtual space. Virtual reconstructions of human motion play an important role in numerous application areas such as animation, medical science, ergonomics, etc. While optical motion capture systems are the industry standard, inertial body sensor networks are becoming viable alternatives due to portability, practicality and cost. This thesis presents an innovative inertial motion capture framework for constructing body sensor networks through software environments, smartphones and web technologies. The first component of the framework is a unique inertial motion capture software environment aimed at providing an improved experimentation environment, accompanied by programming scaffolding and a driver development kit, for users interested in studying or engineering body sensor networks. The software environment provides a bespoke 3D engine for kinematic motion visualisations and a set of tools for hardware integration. The software environment is used to develop the hardware behind a prototype motion capture suit focused on low-power consumption and hardware-centricity. Additional inertial measurement units, which are available commercially, are also integrated to demonstrate the functionality the software environment while providing the framework with additional sources for motion data. The smartphone is the most ubiquitous computing technology and its worldwide uptake has prompted many advances in wearable inertial sensing technologies. Smartphones contain gyroscopes, accelerometers and magnetometers, a combination of sensors that is commonly found in inertial measurement units. This thesis presents a mobile application that investigates whether the smartphone is capable of inertial motion capture by constructing a novel omnidirectional body sensor network. This thesis proposes a novel use for web technologies through the development of the Motion Cloud, a repository and gateway for inertial data. Web technologies have the potential to replace motion capture file formats with online repositories and to set a new standard for how motion data is stored. From a single inertial measurement unit to a more complex body sensor network, the proposed architecture is extendable and facilitates the integration of any inertial hardware configuration. The Motion Cloud’s data can be accessed through an application-programming interface or through a web portal that provides users with the functionality for visualising and exporting the motion data

The Design and Implementation of a Notional Machine for teaching Introductory Programming

Comprehension of both programming and programs is a difficult task for novices to master, with many university courses that feature a programming component demonstrating significant failure and drop out rates. Many theories exist that attempt to explain why this is the case. One such theory, originally postulated by du Boulay, is that students do not understand the properties of the machine; they do not understand what they are or how they are controlling them by writing code. This idea formed the development of the notional machine, which exists solely as an abstraction of the physical machine to aid with its understanding and comprehension. This work contributes a design for a new notional machine and a graphical notation for its representation. The notional machine is designed to work with object-oriented languages (in particular Java). It provides several novel contributions over pre-existing models -- while existing similar models are generally constrained to line by line operation, the notional machine presented here can scale effectively across many program sizes, from few objects and lines to many. In addition, it is able to be used in a variety of formats (in both electronic and unplugged form). It also melds together three traditionally separate diagrams that had to be understood simultaneously (the stack trace, class diagram and object heap.) Novis, an implemented version of the notional machine, is also presented and evaluated. It is able to create automatic and animated versions of notional machine diagrams, and has been integrated into BlueJ's main interface. Novis can present static notional machine diagrams at selected stages of program execution, or animate ongoing execution in real time. The evaluation of Novis is presented in two parts. It is first tested alongside a selection of methodically chosen textbook examples to ensure it can visualise a range of useful programs, and it then undergoes usability testing with a group of first year computer science students

Image and Evidence: The Study of Attention through the Combined Lenses of Neuroscience and Art

: Levy, EK 2012, ‘An artistic exploration of inattention blindness’, in Frontiers Hum Neurosci, vol. 5, ISSN=1662-5161.Full version unavailable due to 3rd party copyright restrictions.This study proposed that new insights about attention, including its phenomenon and pathology, would be provided by combining perspectives of the neurobiological discourse about attention with analyses of artworks that exploit the constraints of the attentional system. To advance the central argument that art offers a training ground for the attentional system, a wide range of contemporary art was analysed in light of specific tasks invoked. The kinds of cognitive tasks these works initiate with respect to the attentional system have been particularly critical to this research. Attention was explored within the context of transdisciplinary art practices, varied circumstances of viewing, new neuroscientific findings, and new approaches towards learning. Research for this dissertation required practical investigations in a gallery setting, and this original work was contextualised and correlated with pertinent neuroscientific approaches. It was also concluded that art can enhance public awareness of attention disorders and assist the public in discriminating between medical and social factors through questioning how norms of behaviour are defined and measured. This territory was examined through the comparative analysis of several diagnostic tests for attention deficit hyperactivity disorder (ADHD), through the adaptation of a methodology from economics involving patent citation in order to show market incentives, and through examples of data visualisation. The construction of an installation and collaborative animation allowed participants to experience first-hand the constraints on the attentional system, provoking awareness of our own “normal” physiological limitations. The embodied knowledge of images, emotion, and social context that are deeply embedded in art practices appeared to be capable of supplementing neuroscience’s understanding of attention and its disorders

NEUVis: Comparing Affective and Effective Visualisation

Data visualisations are useful for providing insight from complex scientific data. However, even with visualisation, scientific research is difficult for non-scientists to comprehend. When developed by designers in collaboration with scientists, data visualisation can be used to articulate scientific data in a way that non-experts can understand. Creating human-centred visualisations is a unique challenge, and there are no frameworks to support their design. In response, this thesis presents a practice-led study investigating design methods that can be used to develop Non-Expert User Visualisations (NEUVis), data visualisations for a general public, and the response that people have to different kinds of NEUVis. For this research, two groups of ten users participated in quantitative studies, informed by Yvonna Lincoln and Egon Guba’s method of Naturalistic Inquiry, which asked non-scientists to express their cognitive and emotional response to NEUVis using different media. The three different types of visualisations were infographics, 3D animations and an interactive installation. The installation used in the study, entitled 18S rDNA, was developed and evaluated as part of this research using John Zimmerman’s Research Through Design methodology. 18S rDNA embodies the knowledge and design methods that were developed for this research, and provided an opportunity for explication of the entire NEUVis design process. The research findings indicate that developing visualisations for the non-expert audience requires a new process, different to the way scientists visualise data. The result of this research describes how creative practitioners collaborate with primary researchers and presents a new human-centred design thinking model for NEUVis. This model includes two design tools. The first tool helps designers merge user needs with data they wish to visualise. The second tool helps designers take that merged information and begin an iterative, user-centred design process

Visualisation of Long in Time Dynamic Networks on Large Touch Displays

Any dataset containing information about relationships between entities can be modelled as a network. This network can be static, where the entities/relationships do not change over time, or dynamic, where the entities/relationships change over time. Network data that changes over time, dynamic network data, is a powerful resource when studying many important phenomena, across wide-ranging fields from travel networks to epidemiology.However, it is very difficult to analyse this data, especially if it covers a long period of time (e.g, one month) with respect to its temporal resolution (e.g. seconds). In this thesis, we address the problem of visualising long in time dynamic networks: networks that may not be particularly large in terms of the number of entities or relationships, but are long in terms of the length of time they cover when compared to their temporal resolution.We first introduce Dynamic Network Plaid, a system for the visualisation and analysis of long in time dynamic networks. We design and build for an 84" touch-screen vertically-mounted display as existing work reports positive results for the use of these in a visualisation context, and that they are useful for collaboration. The Plaid integrates multiple views and we prioritise the visualisation of interaction provenance. In this system we also introduce a novel method of time exploration called ‘interactive timeslicing’. This allows the selection and comparison of points that are far apart in time, a feature not offered by existing visualisation systems. The Plaid is validated through an expert user evaluation with three public health researchers.To confirm observations of the expert user evaluation, we then carry out a formal laboratory study with a large touch-screen display to verify our novel method of time navigation against existing animation and small multiples approaches. From this study, we find that interactive timeslicing outperforms animation and small multiples for complex tasks requiring a compari-son between multiple points that are far apart in time. We also find that small multiples is best suited to comparisons of multiple sequential points in time across a time interval.To generalise the results of this experiment, we later run a second formal laboratory study in the same format as the first, but this time using standard-sized displays with indirect mouse input. The second study reaffirms the results of the first, showing that our novel method of time navigation can facilitate the visual comparison of points that are distant in time in a way that existing approaches, small multiples and animation, cannot. The study demonstrates that our previous results generalise across display size and interaction type (touch vs mouse).In this thesis we introduce novel representations and time interaction techniques to improve the visualisation of long in time dynamic networks, and experimentally show that our novel method of time interaction outperforms other popular methods for some task types

Real-time and archival data visualisation techniques in city dashboards

City dashboards have become a common smart city technology, emerging as a key means of sharing and visualising urban data for the benefit of the public and city administrations. Operating as the front-end of many cities’ data stores, dashboards display and benchmark indicators relating to city operations, characteristics, and trends, displayed through interactive visual representations of spatial and temporal patterns. Many dashboards collect, archive, and present data collected in real-time, as well as more traditional time-sliced administrative data. In this paper, we evaluate the techniques that dashboards employ to present real-time data to dashboard users. Our analysis identifies two factors that shape and differentiate real-time visual analytic tools: the dynamic nature of the data, how they are refreshed, and how the realtimeness of the data is communicated to the user; and how the tool enables archival comparison. We assess dashboard design according to the strategies used to address specific challenges associated with each factor, specifically change blindness and temporal pattern detection. We conclude by proposing effective techniques for city dashboard design