Motor unit number estimation (MUNE) is an electrodiagnostic procedure used to estimate the number of MUs in a muscle. In this thesis, a new MUNE technique, called Automated MPS, has been developed to overcome the shortcomings of two current techniques, namely MPS and MUESA. This method can be summarized as follows. First, a muscle is stimulated with a train of constant intensity current pulses. Depending on various factors, one to three MUs activate probabilistically after each pulse, and several responses are collected. These collected responses should be divided into up to 2^n clusters, such that each cluster represents one possible combination of n Surface-detected Motor Unit Potentials (SMUPs). After clustering the collected responses, the average response of each cluster is calculated, the outliers are excluded, and similar groups are merged together. Then, depending on the number of response set groups, a decomposition technique is applied to the response clusters to obtain the $n$ constituent SMUPs. To estimate the number of MUs, the aforementioned process is repeated several times until enough SMUPs to calculate a reliable mean-SMUP are acquired. The number of MUs can then be determined by dividing the maximal compound muscle action potential (CMAP) size by the mean-SMUP size. The focus of this thesis was on using pattern recognition techniques to detect n SMUPs from a collected set of waveforms. Several experiments were performed using both simulated and real data to evaluate the ability of Automated MPS in finding the constituent SMUPs of a response set. Our experiments showed that performing Automated MPS needs less experience compared with MPS. Moreover, it can deal with more difficult situations and detect more accurate SMUPs compared with MUESA.

With the rapid growth in infrared sensor technology and its drastic cost reduction, the potential of application of these imaging technologies in computer vision systems has increased. One potential application for IR imaging is depth from stereo. Discerning depth from stereopsis is difficult because the quality of un-cooled sensors is not sufficient for generating dense depth maps. In this thesis, we investigate the production of sparse disparity maps from un-calibrated infrared stereo images and agree that a dense depth field may not be attained directly from IR stereo images, but perhaps a sparse depth field may be obtained that can be interpolated to produce a dense/semi-dense depth field. In our proposed technique, the sparse disparity map is produced by a robust features-based stereo matching method capable of dealing with the problems of infrared images, such as low resolution and high noise; initially, a set of stable features are extracted from stereo pairs using the phase congruency model, which contrary to the gradient-based feature detectors, provides features that are invariant to geometric transformations. Then, a set of Log-Gabor wavelet coefficients at different orientations and frequencies is used to analyze and describe the extracted features for matching. The resulted sparse disparity map is then refined by triangular and epipolar geometrical constraints. In densifying the sparse map, a watershed transformation is applied to divide the image into several segments, where the disparity inside each segment is assumed to vary smoothly. The surface of each segment is then reconstructed independently by fitting a spline to its known disparities; Experiments on a set of indoor and outdoor IR stereo pairs lend credibility to the robustness of our IR stereo matching and surface reconstruction techniques and hold promise for low-resolution stereo images which don’t have a large amount of texture and local details.

This thesis presents the theoretical derivations and the implementation of a contact dynamics modelling system based on compliant contact models. The system was designed to be used as a general-purpose modelling tool to support the task planning process space-based robot manipulator systems. This operational context imposes additional requirements on the contact dynamics modelling system beyond the usual ones of fidelity and accuracy. The system must not only be able to generate accurate and reliable simulation results, but it must do it in a reasonably short period of time, such that an operations engineer can investigate multiple scenarios within a few hours. The system is easy to interface with existing simulation facilities. All physical parameters of the contact model can be identified experimentally or can be obtained by other means through analysis or theoretical derivations based on the material properties. Similarly, the numerical parameters can be selected automatically or by using heuristic rules that give an indication of the range of values that would ensure that the simulations results are qualitatively correct. The contact dynamics modelling system is comprised of two contact models. On one hand, a point contact model is proposed to tackle simulations involving bodies with non-conformal surfaces. Since it is based on Hertz theory, the contacting surfaces must be smooth and without discontinuity, i.e., no corners or sharp edges. The point contact model includes normal damping and tangential friction and assumes the contact surface is very small, such that the contact force is assumed to be acting through a point. An expression to set the normal damping as a function of the effective coefficient of restitution is given. A new seven-parameter friction model is introduced. The friction model is based on a bristle friction model, and is adapted to the context of 3-dimensional frictional impact modelling with introduction of load-dependent bristle stiffness and damping terms, and with the expression of the bristle deformation in vectorial form. The model features a dwell-time stiction force dependency and is shown to be able to reproduce the dynamic nature of the friction phenomenon. A second contact model based on the Winkler elastic foundation model is then proposed to deal with a more general class of geometries. This so-called volumetric contact model is suitable for a broad range of contact geometries, as long as the contact surface can be approximated as being flat. A method to deal with objects where this latter approximation is not reasonable is also presented. The effect of the contact pressure distribution across the contact surface is accounted for in the form of the rolling resistance torque and spinning friction torque. It is shown that the contact forces and moments can be expressed in terms of the volumetric properties of the volume of interference between the two bodies, defined as the volume spanned by the intersection of the two undeformed geometries of the colliding bodies. The properties of interest are: the volume of the volume of interference, the position of its centroid, and its inertia tensor taken about the centroid. The analysis also introduces a new way of defining the contact normal; it is shown that the contact normal must correspond to one of the eigenvectors of the inertia tensor. The investigation also examines how the Coulomb friction is affected by the relative motion of the objects. The concept of average surface velocity is introduced. It accounts for both the relative translational and angular motions of the contacting surfaces. The average surface velocity is then used to find dimensionless factors that relate friction force and spinning torque caused by the Coulomb friction. These latter factors are labelled the Contensou factors. Also, the radius of gyration of the moment of inertia of the volume of interference about the contact normal was shown to correlate the spinning Coulomb friction torque to the translational Coulomb friction force. A volumetric version of the seven-parameter bristle friction model is then presented. The friction model includes both the tangential friction force and spinning friction torque. The Contensou factors are used to control the behaviour of the Coulomb friction. For both contact models, the equations are derived from first principles, and the behaviour of each contact model characteristic was studied and simulated. When available, the simulation results were compared with benchmark results from the literature. Experiments were performed to validate the point contact model using a six degrees-of-freedom manipulator holding a half-spherical payload, and coming into contact with a flat plate. Good correspondence between the simulated and experimental results was obtained.

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.