A reconfigurable, tendon-based haptic interface for research into human-environment interactions

Human reaction to external stimuli can be investigated in a comprehensive way by using a versatile virtual-reality setup involving multiple display technologies. It is apparent that versatility remains a main challenge when human reactions are examined through the use of haptic interfaces as the interfaces must be able to cope with the entire range of diverse movements and forces/torques a human subject produces. To address the versatility challenge, we have developed a large-scale reconfigurable tendon-based haptic interface which can be adapted to a large variety of task dynamics and is integrated into a Cave Automatic Virtual Environment (CAVE). To prove the versatility of the haptic interface, two tasks, incorporating once the force and once the velocity extrema of a human subject's extremities, were implemented: a simulator with 3-DOF highly dynamic force feedback and a 3-DOF setup optimized to perform dynamic movements. In addition, a 6-DOF platform capable of lifting a human subject off the ground was realized. For these three applications, a position controller was implemented, adapted to each task, and tested. In the controller tests with highly different, task-specific trajectories, the three robot configurations fulfilled the demands on the application-specific accuracy which illustrates and confirms the versatility of the developed haptic interfac

Muscle Synergies Facilitate Computational Prediction of Subject-Specific Walking Motions.

Researchers have explored a variety of neurorehabilitation approaches to restore normal walking function following a stroke. However, there is currently no objective means for prescribing and implementing treatments that are likely to maximize recovery of walking function for any particular patient. As a first step toward optimizing neurorehabilitation effectiveness, this study develops and evaluates a patient-specific synergy-controlled neuromusculoskeletal simulation framework that can predict walking motions for an individual post-stroke. The main question we addressed was whether driving a subject-specific neuromusculoskeletal model with muscle synergy controls (5 per leg) facilitates generation of accurate walking predictions compared to a model driven by muscle activation controls (35 per leg) or joint torque controls (5 per leg). To explore this question, we developed a subject-specific neuromusculoskeletal model of a single high-functioning hemiparetic subject using instrumented treadmill walking data collected at the subject's self-selected speed of 0.5 m/s. The model included subject-specific representations of lower-body kinematic structure, foot-ground contact behavior, electromyography-driven muscle force generation, and neural control limitations and remaining capabilities. Using direct collocation optimal control and the subject-specific model, we evaluated the ability of the three control approaches to predict the subject's walking kinematics and kinetics at two speeds (0.5 and 0.8 m/s) for which experimental data were available from the subject. We also evaluated whether synergy controls could predict a physically realistic gait period at one speed (1.1 m/s) for which no experimental data were available. All three control approaches predicted the subject's walking kinematics and kinetics (including ground reaction forces) well for the model calibration speed of 0.5 m/s. However, only activation and synergy controls could predict the subject's walking kinematics and kinetics well for the faster non-calibration speed of 0.8 m/s, with synergy controls predicting the new gait period the most accurately. When used to predict how the subject would walk at 1.1 m/s, synergy controls predicted a gait period close to that estimated from the linear relationship between gait speed and stride length. These findings suggest that our neuromusculoskeletal simulation framework may be able to bridge the gap between patient-specific muscle synergy information and resulting functional capabilities and limitations

Biomechanics

Biomechanics is a vast discipline within the field of Biomedical Engineering. It explores the underlying mechanics of how biological and physiological systems move. It encompasses important clinical applications to address questions related to medicine using engineering mechanics principles. Biomechanics includes interdisciplinary concepts from engineers, physicians, therapists, biologists, physicists, and mathematicians. Through their collaborative efforts, biomechanics research is ever changing and expanding, explaining new mechanisms and principles for dynamic human systems. Biomechanics is used to describe how the human body moves, walks, and breathes, in addition to how it responds to injury and rehabilitation. Advanced biomechanical modeling methods, such as inverse dynamics, finite element analysis, and musculoskeletal modeling are used to simulate and investigate human situations in regard to movement and injury. Biomechanical technologies are progressing to answer contemporary medical questions. The future of biomechanics is dependent on interdisciplinary research efforts and the education of tomorrow’s scientists

Development of a neuromusculoskeletal computer model in a chondrodystrophic dog.

Intervertebral disc disease (IVDD) is a naturally occurring disease in dogs that produces a spontaneous injury to the spinal cord. IVDD is characterized by mineralization of the intervertebral disc nucleus pulposus, which reduces its load bearing capacity and results in high rates of intervertebral disc herniation (IVDH). IVDH is disproportionately present in Dachshunds compared to other breeds, affecting an estimated 1 in 5 Dachshunds during their lifetime (Levine, J. M. et al., 2011). Assessment of injury severity and recovery in animal models is generally performed using a point scale, where subjects are graded according to metrics such as pain perception, joint movement, and limb coordination (Basso et al., 1995; Levine, G. J. et al., 2009; Olby, N. J. et al., 2001). Although these methods provide a general view of recovery, they are unable to quantify metrics such as joint motion/torque and muscle activation/force produced during specific phases of gait. OpenSim is an open source software package that allows users to estimate joint kinematics/torques and muscle forces/activations in a musculoskeletal model, which can be scaled to a subject’s dimensions (Delp et al., 2007). Generic musculoskeletal models have been developed in the OpenSim platform for humans (Delp et al., 1990), cats (Keshner et al., 1997), and rats (Johnson et al., 2008), however to the author’s knowledge no model has been developed for dogs. April 12, 2016 The purpose of the proposed study was to develop a subject-specific neuromusculoskeletal computer model of a healthy dog using OpenSim software (Delp, Anderson et al. 2007) to deduce patterns of muscle activity during locomotion. The long- term goal of this study is to utilize the model to inform rehabilitation strategies to enhance recovery and function in dogs with SCI based upon an improved understanding of muscle activation patterns. Additionally, the ability to characterize muscle activation patterns will provide a tool for quantifying the efficacy of therapeutic interventions in a canine model that could allow for potential therapeutic advancement in both dogs and humans. The specific aims of this study were: 1. To characterize joint kinematics of healthy Dachshunds during walking gait. 2. To compare model-predicted joint kinematics to measured joint kinematics in healthy Dachshunds during walking gait. H1: Pelvic limb joint range of motion of the model-predicted kinematics will not be different from kinematics calculated from marker trajectory data. H2: Measured motion tracking marker trajectories will not be different from virtual model-predicted marker trajectories. 3. To quantify model sensitivity to changes in maximum muscle isometric force. H3: Varying maximum muscle isometric force will affect peak muscle activation. v April 12, 2016 To address these aims, a bilateral 3D model of the bony structures of the pelvis and pelvic limb (femur, tibia/fibula, phalanges, and metatarsals) and muscles was created using computed tomography (CT) imaging data. Parameters for the OpenSim model such as muscle origins and insertions, muscle cross-sectional area, and tendon slack length were obtained using computed tomography data or values from literature studies. Kinematic and kinetic data were incorporated in OpenSim to estimate joint kinematics and muscle activation patterns during locomotion. In this study a subject-specific canine pelvic limb neuromusculoskeletal OpenSim model was developed based upon anatomically accurate data, as well as parameters of dogs described in literature. This model included representation of bilateral pelvic limb boney segments and muscles. This model was used to predict kinematics, muscle activation patterns and muscle forces during simulated gait. Findings illustrated that the model provided a reasonable approximation of joint kinematics as compared to measured joint kinematics, based on correlation coefficients calculated between modeled and measured joint kinematics and motion tracking marker trajectory data. The extensor digitorum longus, tibialis cranialis, adductor, vastus lateralis/medialis, rectus femoris, and tensor fascia lata were primarily active during stance. The vastus lateralis/medialis, rectus femoris, tensor fascia lata, sartorius and gluteus medius were active during the first half of swing, while the adductor, semimembranosus, semitendinosus, and biceps femoris were active during the second half of swing. These activation patterns compare similarly with those found in the scientific literature, despite vi April 12, 2016 vii inherent differences in the comparison. This study illustrates the utility of an OpenSim model by demonstrating the ability to accurately model kinematic data, and predict muscle activation patterns during gait. Future work should involve further verification of modeled joint torques and muscle parameters, as well as describe small muscles not included in the current model

From standing posture to vertical jump - Experimental and model analysis of human movement

Dalla postura eretta al salto verticale - Analisi sperimentale e modellistica del movimento uman

serial and parallel robotics: energy saving systems and rehabilitation devices

This thesis focuses on the design and discussion of robotic devices and their applications. Robotics is the branch of technology that deals with the design, construction, operation, and application of robots as well as computer systems for their control, sensory feedback, and information processing [1]. Nowadays, robotics has been an unprecedented increase in applications of industry, military, health, domestic service, exploration, commerce, etc. Different applications require robots with different structures and different functions. Robotics normally includes serial and parallel structures. To have contribution to two kinds of structures, this thesis consisting of two sections is devoted to the design and development of serial and parallel robotic structures, focused on applications in the two different fields: industry and health

Design and implementation of a six-degree of freedom robotic platform for measuring the forces of flying objects

The purpose of this project was to research, design and build a six-degree of freedom platform that measures the forces of flying animal robotics. The platform had to have an embedded force sensing mechanism and should be able to move in response to forces detected and measured. The platform had to measure the forces in six different orthogonal axes. The course of action and focus of the thesis was to research, design, build and control the robotic platform and it was an individual project

Simulating a Flexible Robotic System based on Musculoskeletal Modeling

Humanoid robotics offers a unique research tool for understanding the human brain and body. The synthesis of human motion is a complex procedure that involves accurate reconstruction of movement sequences, modeling of musculoskeletal kinematics, dynamics and actuation, and characterization of reliable performance criteria. Many of these processes have much in common with the problems found in robotics research, with the recent advent of complex humanoid systems. This work presents the design and development of a new-generation bipedal robot. Its modeling and simulation has been realized by using an open-source software to create and analyze dynamic simulation of movement: OpenSim. Starting from a study by Fuben He, our model aims to be used as an innovative approach to the study of a such type of robot in which there are series elastic actuators represented by active and passive spring components in series with motors. It has provided of monoarticular and biarticular joint in a very similar manner to human musculoskeletal model. This thesis is only the starting point of a wide range of other possible future works: from the control structure completion and whole-body control application, to imitation learning and reinforcement learning for human locomotion, from motion test on at ground to motion test on rough ground, and obviously the transition from simulation to practice with a real elastic bipedal robot biologically-inspired that can move like a human bein

Optimal Design Methods for Increasing Power Performance of Multiactuator Robotic Limbs

abstract: In order for assistive mobile robots to operate in the same environment as humans, they must be able to navigate the same obstacles as humans do. Many elements are required to do this: a powerful controller which can understand the obstacle, and power-dense actuators which will be able to achieve the necessary limb accelerations and output energies. Rapid growth in information technology has made complex controllers, and the devices which run them considerably light and cheap. The energy density of batteries, motors, and engines has not grown nearly as fast. This is problematic because biological systems are more agile, and more efficient than robotic systems. This dissertation introduces design methods which may be used optimize a multiactuator robotic limb's natural dynamics in an effort to reduce energy waste. These energy savings decrease the robot's cost of transport, and the weight of the required fuel storage system. To achieve this, an optimal design method, which allows the specialization of robot geometry, is introduced. In addition to optimal geometry design, a gearing optimization is presented which selects a gear ratio which minimizes the electrical power at the motor while considering the constraints of the motor. Furthermore, an efficient algorithm for the optimization of parallel stiffness elements in the robot is introduced. In addition to the optimal design tools introduced, the KiTy SP robotic limb structure is also presented. Which is a novel hybrid parallel-serial actuation method. This novel leg structure has many desirable attributes such as: three dimensional end-effector positioning, low mobile mass, compact form-factor, and a large workspace. We also show that the KiTy SP structure outperforms the classical, biologically-inspired serial limb structure.Dissertation/ThesisDoctoral Dissertation Mechanical Engineering 201