Individuals with functional blindness must often utilise assistive aids to enable them to complete tasks of daily living. One of these tasks, locomotion, poses considerable risk. The long white cane is often used to perform haptic exploration, but cannot detect obstacles that are not ground-based. Although devices have been developed to provide information above waist height, these do not provide auditory interfaces that are easy to learn. Development of such devices should adapt to the user, not require adaptation by the user. Can obstacle avoidance be achieved through direct perception? This research presents an auditory interface that has been designed with the user as the primary focus. An analysis of the tasks required has been taken into account resulting in an interface that audifies ultrasound. Audification provides intuitive information to the user to enable perceptive response to environmental obstacles. A device was developed that provides Doppler shift signals that are audible as a result of intentional aliasing. This system provides acoustic flow that is evident upon initiation of travel and has been shown to be effective in perceiving apertures and avoiding environmental obstacles. The orientation of receivers on this device was also examined, resulting in better distance perception and centreline accuracy when oriented outward as compared to forward. The design of this novel user interface for visually impaired individuals has also provided a tool that can be used to evaluate direct perception and acoustic flow in a manner that has never been studied before.

Individuals with functional blindness must often utilise assistive aids to enable them to complete tasks of daily living. One of these tasks, locomotion, poses considerable risk. The long white cane is often used to perform haptic exploration, but cannot detect obstacles that are not ground-based. Although devices have been developed to provide information above waist height, these do not provide auditory interfaces that are easy to learn. Development of such devices should adapt to the user, not require adaptation by the user. Can obstacle avoidance be achieved through direct perception? This research presents an auditory interface that has been designed with the user as the primary focus. An analysis of the tasks required has been taken into account resulting in an interface that audifies ultrasound. Audification provides intuitive information to the user to enable perceptive response to environmental obstacles. A device was developed that provides Doppler shift signals that are audible as a result of intentional aliasing. This system provides acoustic flow that is evident upon initiation of travel and has been shown to be effective in perceiving apertures and avoiding environmental obstacles. The orientation of receivers on this device was also examined, resulting in better distance perception and centreline accuracy when oriented outward as compared to forward. The design of this novel user interface for visually impaired individuals has also provided a tool that can be used to evaluate direct perception and acoustic flow in a manner that has never been studied before.

Due to the potential uses and advantages of 3D microelectromechanical systems (MEMS), research has been ongoing to advance the field. The intention of my reasearch is to explore different gripper designs and their interaction with corresponding components to establish a 3D microassembly system. In order to meet these goals, two grippers were designed using different mechanisms for grasping. At the same time, corresponding parts capable of being constructed into a 3D microstructure were designed to interact with the grippers. The microcomponents were fabricated using PolyMUMPS, a part of the Multi-User MEMS Processes (MUMPS), and experimentation was conducted with the goal of constructing a 3D microstructure. The results were partially successful in that both grippers were able to pick up corresonponding parts and bring them out of plane in order to make them stand up. However, a final 3D microstructure was unfortunately not achieved due to time constraints. This will be left to future researchers who continue the project. On the equpiment side a microassembly system was fully integrated using cameras for vision and motors with micro-resolution for movement. A computer program was used to control each part of the system. The cameras provided feedback from various views, allowing the operator to observe what was happening to the microcomponents. The grippers were attached to one of the motors and manipulated to pick up the parts. The final overall system proved sufficient for microassembly, but had some areas that could be improved upon.

The objective of this research is to build a prototype of a carbon nanotube (CNT)-based micro X-ray tube array, which can be used in a real-time cone-beam computed tomography (CT) scanner for cancer research. The X-ray tube array consists of an electron source, control grids, focusing electrodes, and an anode plate. All the experiments have been executed in an ultra high vacuum environment at a pressure of 10⁻⁷ Torr. A thin film consisting of multi-wall carbon nanotubes (MWNTs) was used as the electron source. A diode configuration was employed to test the field emission performance of the CNT thin film. The current density achieved was 1mA/cm² at 10V/µm. After the initial burn-in process, a relatively steady emission current was obtained for duration of 170 hours. The control grid was made of 25% opening space stainless steels mesh. Meshes with different wire diameters were tested in a triode structure, and some differences were observed. Multi-anode field emission tests and multi-tube electric field simulations were executed. Experiments and simulations have revealed crosstalk between pixels during field emission. Based on the above experiments and simulations, a signal pixel prototype has been fabricated and is being tested. Moreover, some potential optimizations that will be used in the second prototype are also discussed

Optical coherence tomography (OCT) is an innovative modern biomedical imaging technology that allows in-vivo, non-invasive imaging of biological tissues. At present, some of the major challenges in OCT include the need for fast data acquisition system for probing fast developing biochemical processes in biological tissue, for image processing algorithms to reduce speckle noise and to remove motion artefacts, and for dispersion compensation to improve axial resolution and image contrast. To address the need for fast data acquisition, a novel, high speed (47,000 A-scans/s), ultrahigh axial resolution (3.3μm) Fourier Domain Optical Coherence Tomography (FD-OCT) system in the 1060nm wavelength region has been built at the University of Waterloo. The system provides 3.3μm image resolution in biological tissue and maximum sensitivity of 110 dB. Retinal tomograms acquired in-vivo from a human volunteer and a rat animal model show clear visualization of all intra-retinal layers and increased penetration into the choroid. OCT is based on low-coherence light interferometry. Thus, image quality is dependent on the spatial and temporal coherence properties of the optical waves back-scattered from the imaged object. Due to the coherent nature of light, OCT images are contaminated with speckle noise. Two novel speckle noise reduction algorithms based on interval type II fuzzy sets has been developed to improve the quality of the OCT images. One algorithm is a combination of anisotropic diffusion and interval type II fuzzy system while the other algorithm is based on soft thresholding wavelet coefficients using interval type II fuzzy system. Application of these novel algorithms to Cameraman test image corrupted with speckle noise (variance=0.1) resulted in a root mean square error (RMSE) of 0.07 for both fuzzy anisotropic diffusion and fuzzy wavelet algorithms. This value is less compared to the results obtained for Wiener (RMSE=0.09), adaptive Lee (RMSE=0.09), and median (RMSE=0.12) filters. Applying the algorithms to optical coherence tomograms acquired in-vivo from a human finger-tip show reduction in the speckle noise and image SNR improvement of ~13dB for fuzzy anisotropic diffusion and ~11db for fuzzy wavelet. Comparison with the Wiener (SNR improvement of ~3dB), adaptive Lee (SNR improvement of ~5dB) and median (SNR improvement of ~5dB) filters, applied to the same images, demonstrates the better performance of the fuzzy type II algorithms in terms of image metrics improvement. Micrometer scale OCT image resolution is obtained via use of broad bandwidth light sources. However, the large spectral bandwidth of the imaging beam results in broadening of the OCT interferogram because of the dispersive properties of the imaged objects. This broadening causes deterioration of the axial resolution and as well as loss of contrast in OCT images. A novel even-order dispersion cancellation interferometry via a linear, classical interferometer has been developed which can be further expanded to dispersion canceled OCT.

A practical problem in computer graphics is that of representing a textured surface at arbitrary scales. I consider the underlying mathematical problem to be that of interpolating autoregressive random fields under arbitrary coordinate transformations. I examine the theoretical basis for the transformations that autoregressive parameters exhibit when the associated stationary random fields are scaled or rotated. The basic result is that the transform takes place in the continuous autocovariance domain, and that the spectral density and associated autoregressive parameters proceed directly from sampling the continuous autocovariance on a transformed grid. I show some real-world applications of these ideas, and explore how they allow us to interpolate into a random field. Along the way, I develop interesting ways to estimate simultaneous autoregressive parameters, to calculate the distorting effects of linear interpolation algorithms, and to interpolate random fields without altering their statistics.

The basal ganglia are a group of subcortical nuclei that contain about 100 million neurons in humans. Different modes of basal ganglia dysfunction lead to Parkinson's disease and Huntington's disease, which have debilitating motor and cognitive symptoms. However, despite intensive study, both the internal computational mechanisms of the basal ganglia, and their contribution to normal brain function, have been elusive. The goal of this thesis is to identify basic principles that underlie basal ganglia function, with a focus on signal representation, computation, dynamics, and plasticity. This process begins with a review of two current hypotheses of normal basal ganglia function, one being that they automatically select actions on the basis of past reinforcement, and the other that they compress cortical signals that tend to occur in conjunction with reinforcement. It is argued that a wide range of experimental data are consistent with these mechanisms operating in series, and that in this configuration, compression makes selection practical in natural environments. Although experimental work is outside the present scope, an experimental means of testing this proposal in the future is suggested. The remainder of the thesis builds on Eliasmith & Anderson's Neural Engineering Framework (NEF), which provides an integrated theoretical account of computation, representation, and dynamics in large neural circuits. The NEF provides considerable insight into basal ganglia function, but its explanatory power is potentially limited by two assumptions that the basal ganglia violate. First, like most large-network models, the NEF assumes that neurons integrate multiple synaptic inputs in a linear manner. However, synaptic integration in the basal ganglia is nonlinear in several respects. Three modes of nonlinearity are examined, including nonlinear interactions between dendritic branches, nonlinear integration within terminal branches, and nonlinear conductance-current relationships. The first mode is shown to affect neuron tuning. The other two modes are shown to enable alternative computational mechanisms that facilitate learning, and make computation more flexible, respectively. Secondly, while the NEF assumes that the feedforward dynamics of individual neurons are dominated by the dynamics of post-synaptic current, many basal ganglia neurons also exhibit prominent spike-generation dynamics, including adaptation, bursting, and hysterses. Of these, it is shown that the NEF theory of network dynamics applies fairly directly to certain cases of firing-rate adaptation. However, more complex dynamics, including nonlinear dynamics that are diverse across a population, can be described using the NEF equations for representation. In particular, a neuron's response can be characterized in terms of a more complex function that extends over both present and past inputs. It is therefore straightforward to apply NEF methods to interpret the effects of complex cell dynamics at the network level. The role of spike timing in basal ganglia function is also examined. Although the basal ganglia have been interpreted in the past to perform computations on the basis of mean firing rates (over windows of tens or hundreds of milliseconds) it has recently become clear that patterns of spikes on finer timescales are also functionally relevant. Past work has shown that precise spike times in sensory systems contain stimulus-related information, but there has been little study of how post-synaptic neurons might use this information. It is shown that essentially any neuron can use this information to perform flexible computations, and that these computations do not require spike timing that is very precise. As a consequence, irregular and highly-variable firing patterns can drive behaviour with which they have no detectable correlation. Most of the projection neurons in the basal ganglia are inhibitory, and the effect of one nucleus on another is classically interpreted as subtractive or divisive. Theoretically, very flexible computations can be performed within a projection if each presynaptic neuron can both excite and inhibit its targets, but this is hardly ever the case physiologically. However, it is shown here that equivalent computational flexibility is supported by inhibitory projections in the basal ganglia, as a simple consequence of inhibitory collaterals in the target nuclei. Finally, the relationship between population coding and synaptic plasticity is discussed. It is shown that Hebbian plasticity, in conjunction with lateral connections, determines both the dimension of the population code and the tuning of neuron responses within the coded space. These results permit a straightforward interpretation of the effects of synaptic plasticity on information processing at the network level. Together with the NEF, these new results provide a rich set of theoretical principles through which the dominant physiological factors that affect basal ganglia function can be more clearly understood.

Laparoscopic surgery provides major benefits to patients in terms of decreased pain and post-operative hospital stays, but also increases their risks of intra-operative injuries because of the reduction in feedback in the tactile and visual channels compared to open surgery. Although the limitations of laparoscopy have been studied, the specific role of force feedback in laparoscopic surgery performance is not well understood. The purpose of this thesis is to determine the effect of force feedback on the ability to accurately discriminate tissue compliance by comparing subjective tissue softness assessment, force output, and subjective force assessment, in conventional and laparoscopic setups. The experimental trials involved eleven participants providing evaluations for a range of compliant samples, and analyzed their force output as well as their subjective evaluation of force output. The results of this investigation show that the accuracy of compliance discrimination is worse when using indirect probing compared to direct probing, and that the force used in direct probing is lower than the indirect scenario. Further, the subjective assessment of force output in direct probing is not significantly different compared to indirect probing. Further research involving more replication, expert of laparoscopy, and a focus on grip force are recommended to better understand our awareness of the subjective force output.

VEMap (virtual emotion map) can be seen as an advanced application of virtual environment (VE) technology to aid with design activities in architecture and urban planning, which can assist designers to understand users’ opinions. The aim of this research and development work is to create a software application that allows designers to evaluate a user’s emotional response to virtual representations of architectural or urban planning environments. In this project, a galvanic skin response (GSR) test is adopted as an objective measurement for collecting skin conductance data representing emotional arousal. At the same time, the user’s self-reports are used as a form of subjective measurement for identifying emotional valence (i.e. positive, neutral, and negative). Finally, all of the information collected from both GSR readings (objective measurement) and self-reports (subjective measurement) are converted into coloured dots on the base map of the corresponding virtual environment (VE). According to the results of the VEmap evaluation and validation procedure, the beta-testing and evaluation of this project has been confirmed that VEmap may interpret users’ emotional changes as evoked by VE mostly. From a usability perspective, there is no obvious difficulty present for participants on all the controls. Moreover, according to participants’ comments, VEmap may increase users’ interests and promote their involvement if it is applied in architectural design and urban planning. However, gender might have influence on self-report part, and virtual reality usage or 3D game experiences might affect navigation in VE.

The graph model for conflict resolution (GMCR) provides a convenient and effective means to model and analyze a strategic conflict. Standard practice is to carry out a stability analysis of a graph model, and then to follow up with a post-stability analysis, two critical components of which are status quo analysis and coalition analysis. In stability analysis, an equilibrium is a state that is stable for all decision makers (DMs) under appropriate stability definitions or solution concepts. Status quo analysis aims to determine whether a particular equilibrium is reachable from a status quo (or an initial state) and, if so, how to reach it. A coalition is any subset of a set of DMs. The coalition stability analysis within the graph model is focused on the status quo states that are equilibria and assesses whether states that are stable from individual viewpoints may be unstable for coalitions. Stability analysis began within a simple preference structure which includes a relative preference relationship and an indifference relation. Subsequently, preference uncertainty and strength of preference were introduced into GMCR but not formally integrated. In this thesis, two new preference frameworks, hybrid preference and multiple-level preference, and an integrated algebraic approach are developed for GMCR. Hybrid preference extends existing preference structures to combine preference uncertainty and strength of preference into GMCR. A multiple-level preference framework expands GMCR to handle a more general and flexible structure than any existing system representing strength of preference. An integrated algebraic approach reveals a link among traditional stability analysis, status quo analysis, and coalition stability analysis by using matrix representation of the graph model for conflict resolution. To integrate the three existing preference structures into a hybrid system, a new preference framework is proposed for graph models using a quadruple relation to express strong or mild preference of one state or scenario over another, equal preference, and an uncertain preference. In addition, a multiple-level preference framework is introduced into the graph model methodology to handle multiple-level preference information, which lies between relative and cardinal preferences in information content. The existing structure with strength of preference takes into account that if a state is stable, it may be either strongly stable or weakly stable in the context of three levels of strength. However, the three-level structure is limited in its ability to depict the intensity of relative preference. In this research, four basic solution concepts consisting of Nash stability, general metarationality, symmetric metarationality, and sequential stability, are defined at each level of preference for the graph model with the extended multiple-level preference. The development of the two new preference frameworks expands the realm of applicability of the graph model and provides new insights into strategic conflicts so that more practical and complicated problems can be analyzed at greater depth. Because a graph model of a conflict consists of several interrelated graphs, it is natural to ask whether well-known results of Algebraic Graph Theory can help analyze a graph model. Analysis of a graph model involves searching paths in a graph but an important restriction of a graph model is that no DM can move twice in succession along any path. (If a DM can move consecutively, then this DM's graph is effectively transitive. Prohibiting consecutive moves thus allows for graph models with intransitive graphs, which are sometimes useful in practice.) Therefore, a graph model must be treated as an edge-weighted, colored multidigraph in which each arc represents a legal unilateral move and distinct colors refer to different DMs. The weight of an arc could represent some preference attribute. Tracing the evolution of a conflict in status quo analysis is converted to searching all colored paths from a status quo to a particular outcome in an edge-weighted, colored multidigraph. Generally, an adjacency matrix can determine a simple digraph and all state-by-state paths between any two vertices. However, if a graph model contains multiple arcs between the same two states controlled by different DMs, the adjacency matrix would be unable to track all aspects of conflict evolution from the status quo. To bridge the gap, a conversion function using the matrix representation is designed to transform the original problem of searching edge-weighted, colored paths in a colored multidigraph to a standard problem of finding paths in a simple digraph with no color constraints. As well, several unexpected and useful links among status quo analysis, stability analysis, and coalition analysis are revealed using the conversion function. The key input of stability analysis is the reachable list of a DM, or a coalition, by a legal move (in one step) or by a legal sequence of unilateral moves, from a status quo in 2-DM or $n$-DM ($n > 2$) models. A weighted reachability matrix for a DM or a coalition along weighted colored paths is designed to construct the reachable list using the aforementioned conversion function. The weight of each edge in a graph model is defined according to the preference structure, for example, simple preference, preference with uncertainty, or preference with strength. Furthermore, a graph model and the four basic graph model solution concepts are formulated explicitly using the weighted reachability matrix for the three preference structures. The explicit matrix representation for conflict resolution (MRCR) that facilitates stability calculations in both 2-DM and $n$-DM ($n > 2$) models for three existing preference structures. In addition, the weighted reachability matrix by a coalition is used to produce matrix representation of coalition stabilities in multiple-decision-maker conflicts for the three preference frameworks. Previously, solution concepts in the graph model were traditionally defined logically, in terms of the underlying graphs and preference relations. When status quo analysis algorithms were developed, this line of thinking was retained and pseudo-codes were developed following a similar logical structure. However, as was noted in the development of the decision support system (DSS) GMCR II, the nature of logical representations makes coding difficult. The DSS GMCR II, is available for basic stability analysis and status quo analysis within simple preference, but is difficult to modify or adapt to other preference structures. Compared with existing graphical or logical representation, matrix representation for conflict resolution (MRCR) is more effective and convenient for computer implementation and for adapting to new analysis techniques. Moreover, due to an inherent link between stability analysis and post-stability analysis presented, the proposed algebraic approach establishes an integrated paradigm of matrix representation for the graph model for conflict resolution.