This study investigated the importance of binocular vision to foot placement accuracy when stepping onto a floor-based target during gait initiation. Starting from stationary, participants placed alternate feet onto targets sequentially positioned along a straight travel path with the added constraint that the initial target (target 1) could move in the medio-lateral (M-L) direction. Repeated trials when target 1 remained stationary or moved laterally at the instant of lead-limb toe-off (TO) or 200 ms after TO (early swing) were undertaken under binocular and monocular viewing. Catch trials when target 1 shifted medially were also undertaken. Foot-reach kinematics, foot trajectory corrections and foot placement accuracy for the step onto target 1 were determined via 3D motion analyses. Peak foot-reach velocity and initial foot-reach duration were unaffected by vision condition but terminal foot-reach duration was prolonged under monocular conditions (p = 0.002). Foot trajectory alteration onsets were unaffected by vision condition, but onsets occurred sooner when the target shifted in early swing compared to at TO (p = 0.033). M-L foot placement accuracy decreased (p = 0.025) and variability increased (p = 0.05) under monocular conditions, particularly when stepping onto the moving target. There was no difference between vision conditions in A-P foot placement accuracy. Results indicate that monocular vision provides sufficient information to determine stepping distance and correctly transport the foot towards the target but binocular vision is required to attain a precise M-L foot placement; particularly so when stepping onto a moving target. These findings are in agreement with those found in the reaching and grasping literature, indicating that binocular vision is important for end-point precision. / The Health Foundation, UK. Grant (3991/3322)

Notre motivation est de comprendre la locomotion humaine pour un meilleur contrôle des systèmes virtuels (robots et mannequins). La locomotion humaine a été étudiée depuis longtemps dans des domaines différents. Nous considérons la locomotion comme le déplacement d’un repère attaché au corps humain (direction et orientation) au lieu de la trajectoire articulaire du corps complet. Notre approche est basée sur le fondement calculatoire de la locomotion humaine. Le but est de trouver un modèle qui explique la forme de la locomotion humaine dans l’espace. Pour ce faire, nous étudions tout d’abord le comportement des trajectoires au sol pendant la locomotion intentionnelle. Quand un humain marche, il met un pied devant l’autre et par conséquence, l’orientation du corps suit la direction tangente de la trajectoire. C’est ce qu’on appelle l’hypothèse de comportement nonholonome. Cependant, dans le cas d’un pas de côté, l’orientation du corps n’est plus semblable à la direction de trajectoire, et l’hypothèse n’est plus valable. Le comportement de la locomotion devient holonome. Le but de la thèse est de distinguer ces deux comportements et de les exploiter en neuroscience, robotique et animation graphique. La première partie de la thèse présente une étude qui permet de déterminer des configurations de comportement holonome par un protocole expérimental et par une fonction qui segmente les comportements nonholonomes et holonomes d’une trajectoire. Dans la deuxième partie, nous établissons un modèle unifiant comportements nonholonomes et holonomes. Ce modèle combine trois vitesses générant la locomotion humaine : tangentielle, angulaire et latérale. Par une approche de commande optimale inverse nous proposons une fonction multi-objectifs qui optimise des trajectoires calculées pour les rendre proches des trajectoires humaines naturelles. La dernière partie est l’application qui utilise les deux comportements pour synthétiser des locomotions humaines dans un environnement d’animation graphique. Chaque locomotion est caractérisée par trois vitesses et est donc considérée comme un point dans l’espace de commande 3D (de trois vitesses). Nous avons collecté une librairie qui contient des locomotions de vitesses différentes – des points dans l’espace 3D. Ces points sont structurés en un nuage de tétraèdres. Quand une vitesse désirée est donnée, elle est projetée dans l’espace 3D et on trouve le tétraèdre qui la contient. La nouvelle animation est interpolée par quatre locomotions correspondant aux quatre sommets du tétraèdre. On expose plusieurs scénarios d’animations sur un personnage virtuel. / Our motivation is to understand human locomotion to better control locomotion of virtual systems (robots and mannequins). Human locomotion has been studied so far in different disciplines. We consider locomotion as the level of a body frame (in direction and orientation) instead of the complexity of many kinematic joints systems as other approaches. Our approach concentrates on the computational foundation of human locomotion. The ultimate goal is to find a model that explains the shape of human locomotion in space. To do that, we first base on the behavior of trajectories on the ground during intentional locomotion. When human walk, they put one foot in front of the other and consequently, the direction of motion is deduced by the body orientation. That’s what we called the nonholonomic behavior hypothesis. However, in the case of a sideward step, the body orientation is not coupled to the tangential direction of the trajectory, and the hypothesis is no longer validated. The behavior of locomotion becomes holonomic. The aim of this thesis is to distinguish these two behaviors and to exploit them in neuroscience, robotics and computer animation. The first part of the thesis is to determine the configurations of the holonomic behavior by an experimental protocol and an original analytical tool segmenting the nonholonomic and holonomic behaviors of any trajectory. In the second part, we present a model unifying nonholonomic and holonomic behaviors. This model combines three velocities generating human locomotion: forward, angular and lateral. The experimental data in the first part are used in an inverse optimal control approach to find a multi-objective function which produces calculated trajectories as those of natural human locomotion. The last part is the application that uses the two behaviors to synthesize human locomotion in computer animation. Each locomotion is characterized by three velocities and is therefore considered as a point in 3D control space (of three speeds). We collected a library that contains locomotions at different velocities - points in 3D space. These points are structured in a tetrahedra cloud. When a desired speed is given, it is projected into the 3D space and we find the corresponding tetrahedron that contains it. The new animation is interpolated by four locomotions corresponding to four vertices of the selected tetrahedron. We exhibit several animation scenarios on a virtual character.

Thesis (M.S.)--University of Texas at El Paso, 2009. / Title from title screen. Vita. CD-ROM. Includes bibliographical references. Also available online.

No description available.

No description available.

No description available.

Effective movement is central to survival and it is essential for all animals to react in response to changes around them. In many animals the rhythmic signals that drive locomotion are generated intrinsically by small networks of neurons in the nervous system which can be switched on and off. In this thesis I use a very simple animal, in which the behaviours and neuronal networks have been well characterised experimentally, to explore the salient features of such networks. Two days after hatching, tadpoles of the frog Xenopus laevis respond to a brief touch to the head by starting to swim. The swimming rhythm is driven by a small population of electrically coupled brainstem neurons (called dINs) on each side of the tadpole. These neurons also receive synaptic input following head skin stimulation. I build biophysical computational models of these neurons based on experimental data in order to address questions about the effects of electrical coupling, synaptic feedback excitation and initiation pathways. My aim is better understanding of how swimming activity is initiated and sustained in the tadpole. I find that the electrical coupling between the dINs causes their firing properties to be modulated. This allows two experimental observations to be reconciled: that a dIN only fires a single action potential in response to step current injections but the population fires like pacemakers during swimming. I build on this hypothesis and show that long-lasting, excitatory feedback within the population of dINs allows rhythmic pacemaker activity to be sustained in one side of the nervous system. This activity can be switched on and off at short latency in response to biologically realistic synaptic input. I further investigate models of synaptic input from a defined swim initiation pathway and show that electrical coupling causes a population of dINs to be recruited to fire either as a group or not at all. This allows the animal to convert continuously varying sensory stimuli into a discrete decision. Finally I find that it is difficult to reliably start swimming-like activity in the tadpole model using simple, short-latency, symmetrical initiation pathways but that by using more complex, asymmetrical, neuronal-pathways to each side of the body, consistent with experimental observations, the initiation of swimming is more robust. Throughout this work, I make testable predictions about the population of brainstem neurons and also describe where more experimental data is needed. In order to manage the parameters and simulations, I present prototype libraries to build and manage these biophysical model networks.

This thesis addresses modeling and simulation of the human lower extremities in order to track walking motion and estimate walking distance. The lower extremities are modeled as an articulated object, which consists of rigid bars connected to each other by joints. This model is tested by using both synthetic and real data. The synthetic data is created based on the main principles of biomechanics. The real data is obtained from the MARG sensors and is processed by the Factored Quaternion algorithm. Next, it is implemented in a simulation program written in Matlab. The program utilizes a mathematical model that represents the human gait-cycle and is based on the theory of forward kinematics as well as on the theory of manipulator kinematics. The simulation program is able to track the motion of the limbs that represent the lower extremities and estimate the traveled distance. Extensive laboratory tests verified the validity of the configuration.

Long projections from the brainstem to the lumbar cord activate locomotion. Using in vitro neonatal rats our laboratory showed that relay (propriospinal - PS) neurons also contribute to transmission of the locomotor signal. This thesis examines whether locomotor-related PS neurons exist in adult mammals, which has important clinical implications. The brainstem of adult decerebrate rats was stimulated to elicit stepping. The following manipulations were performed: 1) suppression of synaptic transmission to PS neurons, 2) lesioning of direct bulbospinal projections to lumbar segments, and 3) neurochemical excitation of PS neurons. In addition, in the absence of brainstem stimulation, the ability of neurochemically excited PS neurons to induce stepping was examined. Brainstem-evoked locomotion was suppressed by synaptic blockade, enhanced by PS neuron excitation, persists after lesioning of long-direct projections, and hindlimb stepping was elicited by PS neuron excitation alone. The findings support the existence of a locomotor-related PS system in adult mammals. / October 2016

Mémoire numérisé par la Direction des bibliothèques de l'Université de Montréal.