New control strategies for neuroprosthetic systems

The availability of techniques to artificially excite paralyzed muscles opens enormous potential for restoring both upper and lower extremity movements with\ud neuroprostheses. Neuroprostheses must stimulate muscle, and control and regulate the artificial movements produced. Control methods to accomplish these tasks include feedforward (open-loop), feedback, and adaptive control. Feedforward control requires a great deal of information about the biomechanical behavior of the limb. For the upper extremity, an artificial motor program was developed to provide such movement program input to a neuroprosthesis. In lower extremity control, one group achieved their best results by attempting to meet naturally perceived gait objectives rather than to follow an exact joint angle trajectory. Adaptive feedforward control, as implemented in the cycleto-cycle controller, gave good compensation for the gradual decrease in performance observed with open-loop control. A neural network controller was able to control its system to customize stimulation parameters in order to generate a desired output trajectory in a given individual and to maintain tracking performance in the presence of muscle fatigue. The authors believe that practical FNS control systems must\ud exhibit many of these features of neurophysiological systems

Predictive Dynamic Simulation of Healthy Sit-to-Stand Movement

This thesis situates itself at the intersection of biomedical modelling and predictive simulation to synthesize healthy human sit-to-stand movement. While the importance of sit-to-stand to physical and social well-being is known, the reasons for why and how people come to perform sit-to-stand the way we do is largely unknown. This thesis establishes the determinants of sit-to-stand in healthy people so that future researchers may investigate the effects of compromised health on sit-to-stand and then explore means of intervening to preserve and restore this motion. Previous researchers have predicted how a person rises from seated. However aspects of their models, most commonly contact and muscle models, are biomechanically inconsistent and restrict their application. These researchers also have not validated their prediction results. To address these limitations and further the study of sit-to-stand prediction, the underlying themes of this thesis are in biomechanical modelling, predictive simulation, and validation. The goal of predicting sit-to-stand inspired the creation of three new models: a model of biomechanics, a model of motion, and performance criteria as a model of preference. First, the human is represented as three rigid links in the sagittal plane. As buttocks are kinetically important to sit-to-stand, a new constitutive model of buttocks is made from experimental force-deformation data. Ten muscles responsible for flexion and extension of the hips, knees, and ankles are defined in the model. Second, candidate sit-to-stand trajectories are described geometrically by a set of Bézier curves, for the first time. Third, with the assumption that healthy people naturally prioritize mechanical efficiency, disinclination to a motion is described as a cost function of joint torques, muscle stresses, and physical infeasibility including slipping and falling. This new dynamic optimization routine allows for motions of gradually increasing complexity, by adding control points to the Bézier curves, while the model's performance is improving. By comparing the predictive simulation results to normative sit-to-stand as described in the literature, for the first time, it is possible to say that the use of these models and optimal control strategy together has produced motions characteristic of healthy sit-to-stand. This work bridges the gap between predictive simulation results and experimental human results and in doing so establishes a benchmark in sit-to-stand prediction. In predicting healthy sit-to-stand, it makes a necessary step toward predicting pathological sit-to-stand, and then to predicting the results of intervention to inform medical design and planning

Humanoid Robots

For many years, the human being has been trying, in all ways, to recreate the complex mechanisms that form the human body. Such task is extremely complicated and the results are not totally satisfactory. However, with increasing technological advances based on theoretical and experimental researches, man gets, in a way, to copy or to imitate some systems of the human body. These researches not only intended to create humanoid robots, great part of them constituting autonomous systems, but also, in some way, to offer a higher knowledge of the systems that form the human body, objectifying possible applications in the technology of rehabilitation of human beings, gathering in a whole studies related not only to Robotics, but also to Biomechanics, Biomimmetics, Cybernetics, among other areas. This book presents a series of researches inspired by this ideal, carried through by various researchers worldwide, looking for to analyze and to discuss diverse subjects related to humanoid robots. The presented contributions explore aspects about robotic hands, learning, language, vision and locomotion

Comparison of lower body segment alignment of elite level hockey players to age-matched non-hockey players

Master's Project (M.A.) University of Alaska Fairbanks, 2015Lower body overuse and insidious onset injuries are thought to have an underlying biomechanical component which may be predisposing to injury. The purpose of this study was to compare lower body biomechanical characteristics for elite hockey players to matched controls. I hypothesize that elite hockey players have a greater degree of anterior pelvic tilt, greater varus knee angle, a higher foot arch and feet held in parallel more during gait than a matched non-skating population. Measures were taken of elite level, college aged, male hockey players and compared to cross country runners (ten subjects in each group) who served as controls for trunk angle, pelvic tilt angle, knee alignment, (varus/valgus angle), foot angle, arch index (arch height), hip, center of range of motion, hip external rotation, hip internal rotation, hip total range of motion (ROM), knee transverse plane ROM, and step width. The results obtained support the hypothesis for anterior pelvic tilt and foot angle during gait. Although knee angle was in the expected varus direction it was not significant and no differences were observed in the foot arch between the groups. All other measurements not directly related to the hypothesis were not significantly different with the exception of mean step width. The obtained results are important as recent literature describes a lower body posture of medial collapse into "dynamic valgus" as being predisposing to injury. Results show, on the spectrum from lower body varus to lower body valgus, hockey players are on the varus side of the spectrum in all attributes except arch height, which was similar in both populations. Since lower body alignment is thought to be coupled, this inconsistency appears contrary to the "medial collapse into dynamic valgus" model and may explain why foot orthotics and athletic shoes used as an injury intervention often fail

Real-time biped character stepping

PhD ThesisA rudimentary biped activity that is essential in interactive evirtual worlds, such as video-games and training simulations, is stepping. For example, stepping is fundamental in everyday terrestrial activities that include walking and balance recovery. Therefore an effective 3D stepping control algorithm that is computationally fast and easy to implement is extremely valuable and important to character animation research. This thesis focuses on generating real-time controllable stepping motions on-the-fly without key-framed data that are responsive and robust (e.g.,can remain upright and balanced under a variety of conditions, such as pushes and dynami- cally changing terrain). In our approach, we control the character’s direction and speed by means of varying the stepposition and duration. Our lightweight stepping model is used to create coordinated full-body motions, which produce directable steps to guide the character with specific goals (e.g., following a particular path while placing feet at viable locations). We also create protective steps in response to random disturbances (e.g., pushes). Whereby, the system automatically calculates where and when to place the foot to remedy the disruption. In conclusion, the inverted pendulum has a number of limitations that we address and resolve to produce an improved lightweight technique that provides better control and stability using approximate feature enhancements, for instance, ankle-torque and elongated-body

Building Parameterized Action Representations From Observation

Virtual worlds may be inhabited by intelligent agents who interact by performing various simple and complex actions. If the agents are human-like (embodied), their actions may be generated from motion capture or procedural animation. In this thesis, we introduce the CaPAR interactive system which combines both these approaches to generate agent-size neutral representations of actions within a framework called Parameterized Action Representation (PAR). Just as a person may learn a new complex physical task by observing another person doing it, our system observes a single trial of a human performing some complex task that involves interaction with self or other objects in the environment and automatically generates semantically rich information about the action. This information can be used to generate similar constrained motions for agents of different sizes. Human movement is captured by electromagnetic sensors. By computing motion zerocrossings and geometric spatial proximities, we isolate significant events, abstract both spatial and visual constraints from an agent\u27s action, and segment a given complex action into several simpler subactions. We analyze each independently and build individual PARs for them. Several PARs can be combined into one complex PAR representing the original activity. Within each motion segment, semantic and style information is extracted. The style information is used to generate the same constrained motion in other differently sized virtual agents by copying the end-effector velocity profile, by following a similar end-effector trajectory, or by scaling and mapping force interactions between the agent and an object. The semantic information is stored in a PAR. The extracted style and constraint information is stored in the corresponding agent and object models

Effects of Head Motion on Postural Stability in Participants with Chronic Motion Sensitivity

Background: Motion sensitivity, or motion sickness, is common among individuals in modern vehicular and visually stimulating environments; notably, people with normal vestibular function are susceptible to this condition. Motion-provoked dizziness often causes postural instability. Purposes: This study aimed to compare the effects of head motion on postural stability in healthy adults with and without chronic motion sensitivity (CMS) and to determine the effects of head motion direction (horizontal versus vertical) on postural stability. Methods: Sixty healthy adult males and females aged 20 to 40 years old were assigned to two groups, 30 participants with CMS and 30 participants without CMS. Pre-data collection, all participants were trained on specific parameters of cervical rotation, flexion, and extension. Then, postural stability measurements were taken during three conditions (static, horizontal, and vertical head movements) using the Bertec Balance Advantage Dynamic Computerized Dynamic Posturography (CDP). Results: There was a significant difference between the CMS and non-CMS groups in mean postural stability during head movement in both horizontal and vertical head motions (p = 0.005 and p = 0.024, respectively); however, no significant difference was shown in mean postural stability between horizontal and vertical head motions within each group (p = 0.297 in CMS group and p = 0.179 in non-CMS group). Conclusions: The results indicate that healthy young adults without CMS have better postural stability during head motion than those with CMS, and that head motion direction (horizontal versus vertical) does not influence postural stability within each study group

Synergy-Based Human Grasp Representations and Semi-Autonomous Control of Prosthetic Hands

Das sichere und stabile Greifen mit humanoiden Roboterhänden stellt eine große Herausforderung dar. Diese Dissertation befasst sich daher mit der Ableitung von Greifstrategien für Roboterhände aus der Beobachtung menschlichen Greifens. Dabei liegt der Fokus auf der Betrachtung des gesamten Greifvorgangs. Dieser umfasst zum einen die Hand- und Fingertrajektorien während des Greifprozesses und zum anderen die Kontaktpunkte sowie den Kraftverlauf zwischen Hand und Objekt vom ersten Kontakt bis zum statisch stabilen Griff. Es werden nichtlineare posturale Synergien und Kraftsynergien menschlicher Griffe vorgestellt, die die Generierung menschenähnlicher Griffposen und Griffkräfte erlauben. Weiterhin werden Synergieprimitive als adaptierbare Repräsentation menschlicher Greifbewegungen entwickelt. Die beschriebenen, vom Menschen gelernten Greifstrategien werden für die Steuerung robotischer Prothesenhände angewendet. Im Rahmen einer semi-autonomen Steuerung werden menschenähnliche Greifbewegungen situationsgerecht vorgeschlagen und vom Nutzenden der Prothese überwacht