Doctor of Philosophy

dissertationModeling the human hand's tendon system can bring better understanding to roboticists trying to create tendon based robotic hands and clinicians trying to identify new surgical solutions to hand tendon injuries. Accurate modeling of the hand's tendon system is complex due to the intricate nature of how tendons route and attach to each other and the skeleton system. These tendon complexities have restricted previous tendon models to single finger models with limited anatomical accuracy and no ability to depict fingertip contact force with external surfaces. This dissertation outlines the use of bond graph modeling to create and improve upon previous tendon models of the single finger. This bond graph tendon model of the single finger is the first model to incorporate many anatomical features, including tendon interconnections and anatomical stiffness, of the tendon system. A graphical user interface is presented to visually explore the relationship between tendon input and finger posture. The bond graph tendon model is validated using cadaver and in vivo experiments, along with the Anatomically Correct Testbed (ACT) Hand, which is a biologically inspired robotic hand that accurately mimics the bone structure, joints, and tendons of the human hand. Comparisons of the bond graph tendon model to in vivo data on finger joint coupling and fingertip pinch force, and cadaver data on the tendon system showed strong correlation in trends and magnitudes. A motion experiment, comparing the joint angle results of tendon excursions of the bond graph tendon model and the ACT Hand, and a force experiment, comparing the fingertip force generation of the two systems, were devised to validate the bond graph tendon model. The results of the motion experiments showed close agreement between the two systems (< 8 joint angle error), while the results of the force experiments showed a larger range correlation between the two systems (8-42% difference). The result of the validation experiments showed that the bond graph tendon model is able to accurately represent the tendon system of the finger. The model is also the first tendon model to allow for exploration of the effects of fingertip contact on the tendon system

The role of morphology of the thumb in anthropomorphic grasping : a review

The unique musculoskeletal structure of the human hand brings in wider dexterous capabilities to grasp and manipulate a repertoire of objects than the non-human primates. It has been widely accepted that the orientation and the position of the thumb plays an important role in this characteristic behavior. There have been numerous attempts to develop anthropomorphic robotic hands with varying levels of success. Nevertheless, manipulation ability in those hands is to be ameliorated even though they can grasp objects successfully. An appropriate model of the thumb is important to manipulate the objects against the fingers and to maintain the stability. Modeling these complex interactions about the mechanical axes of the joints and how to incorporate these joints in robotic thumbs is a challenging task. This article presents a review of the biomechanics of the human thumb and the robotic thumb designs to identify opportunities for future anthropomorphic robotic hands

A Linear Actuator/Spring Steel-Driven Glove for Assisting Individuals with Activities of Daily Living

Over three million people in the U.S. suffer from forearm and hand disabilities. This can result from aging, neurological disorders (e.g., stroke), chronic disease (e.g., arthritis), and injuries. Injuries to hands comprise one-third of all work-related injuries worldwide. This can lead to difficulties with activities of daily living (ADL), where one needs to grasp, lift, and release objects in the household. There is a rise in demand for assistive orthoses and gloves that can allow many people to regain their grasping/releasing ability and, thereby, their independence. The main contribution of this thesis is developing an assistive glove with the actuating mechanism comprised of linear actuators and strips of spring steel to enable bidirectional motion of users\u27 fingers during ADL. The target group of people to use this proposed actuation system was chosen to those who had only diminished hand grasping capabilities. There are already many different gloves in the market. Each one uses different methods of actuation and force transmission, as well as different control methods. These gloves were analyzed by looking at their actuation mechanisms, control systems, and the benefits and downfalls of each one. Vigorous testing was conducted to choose the most effective components for the actuating mechanism. Then, an assistive glove was fabricated which included a control system box that could be easily worn on the forearm of the user. Tests were conducted on the glove to test its effectiveness when the user’s hand was completely passive using four to six participants. Motion capture, force, and electromyography (EMG) data were collected and from those, range of finger motion, maximum grasping capabilities, maximum force generation, and muscle activity were analyzed. The glove was shown to actuate the fingers enough to grasp objects with different sizes ranging in diameter from 40mm to 80mm, with maximum possible weight able to be picked up being around 1000g for the larger sizes. The glove could generate 4N-5N to the index and middle fingers and 10N to the thumb. EMG analysis showed that using the glove to pick up heavy objects caused a decrease in muscle activity of up to 80%. From this analysis, it was shown that the glove has potential to assist with ADL and would provide greater independence for those with diminished hand grasping abilities

Achieving human-like dexterity in robotic hands : inspiration from human hand biomechanics and neuromuscular control

The human hand's unique biomechanical structure and neuromuscular control combine to produce amazing dexterous capabilities in a way that is still not fully understood. The Anatomically Correct Testbed (ACT) hand is a robotic system that is designed as a physical simulation of the human hand, and can help us examine and potentially uncover the roles of biomechanics and neural control in achieving dexterity. In this dissertation, I utilize the ACT hand and other robotic systems to explore the underlying sources of human hand dexterity, with the goal of understanding the fundamental differences between robotic and human hands in terms of (i) mechanical joint/tendon structure and (ii) control strategies. To begin, I develop comprehensive mechanical models that describe the musculoskeletal and tendon mechanics of the fingers and thumb of the human hand. Then, I work to isolate the contributions of biomechanical structure and neuromuscular control toward human dexterity. I have developed and implemented control strategies for achieving fine object manipulation first with the robotic hand of a space humanoid, Robonaut 2, and then with the ACT hand. I examined the unique control challenges, including uncontrollable joints and the requirement of accurate internal models, that arise due to the human hand's complex musculotendon structure and the potential advantages offered by the human hand's design, such as passive joint coupling to facilitate grasp shape adaptation and force production capabilities that are ideally suited for common manipulation tasks. Finally, inspired by the neuromuscular control strategies of the human hand, I have developed a novel hierarchical control strategy for the ACT hand and experimentally demonstrated improved grasp stability and manipulation capabilities compared to conventional robotic control laws. Through an in-depth exploration of human hand biomechanics and neuromuscular control, theoretical control analysis of robotic and human hands, and experimental demonstration of fine object manipulation, this work uncovers crucial insights into the sources of human hand dexterity that have the potential to drive innovative design and control strategies and bring robotic and prosthetic hands closer to human levels of dexterity.Mechanical Engineerin

Modeling & Analysis of Design Parameters for Portable Hand Orthoses to Assist Upper Motor Neuron Syndrome Impairments and Prototype Design

Wearable assistive robotics have the potential to address an unmet medical need of reducing disability in individuals with chronic hand impairments due to neurological trauma. Despite myriad prior works, few patients have seen the benefits of such devices. Following application experience with tendon-actuated soft robotic gloves and a collaborator\u27s orthosis with novel flat-spring actuators, we identified two common assumptions regarding hand orthosis design. The first was reliance on incomplete studies of grasping forces during activities of daily living as a basis for design criteria, leading to poor optimization. The second was a neglect of increases in muscle tone following neurological trauma, rendering most devices non-applicable to a large subset of the population. To address these gaps, we measured joint torques during activities of daily living with able-bodied subjects using dexterity representative of orthosis-aided motion. Next, we measured assistive torques needed to extend the fingers of individuals with increased flexor tone following TBI. Finally, we applied this knowledge to design a cable actuated orthosis for assisting finger extension, providing a basis for future work focused on an under-represented subgroup of patients

System Design of a Cheetah Robot Toward Ultra-high Speed

High-speed legged locomotion pushes the limits of the most challenging problems of design and development of the mechanism, also the control and the perception method. The cheetah is an existence proof of concept of what we imitate for high-speed running, and provides us lots of inspiration on design. In this paper, a new model of a cheetah-like robot is developed using anatomical analysis and design. Inspired by a biological neural mechanism, we propose a novel control method for controlling the muscles' flexion and extension, and simulations demonstrate good biological properties and leg's trajectory. Next, a cheetah robot prototype is designed and assembled with pneumatic muscles, a musculoskeletal structure, an antagonistic muscle arrangement and a J-type cushioning foot. Finally, experiments of the robot legs swing and kick ground tests demonstrate its natural manner and validate the design of the robot. In the future, we will test the bounding behaviour of a real legged system

A novel robotic platform to assist, train, and study head-neck movement

Moving the head-neck freely is an everyday task that a healthy person takes for granted. Such a simple movement, however, may be very challenging for individuals with neurological disorders such as amyotrophic lateral sclerosis. These individuals often do not have enough neck muscle strength to stabilize the head at the upright neutral or to move it in a controlled manner. Static braces are commonly prescribed to these patients. However, these braces often fix the head at a single configuration, which makes them uncomfortable to wear for an extended period of time. In this thesis, a robotic neck brace is developed. It accommodates three rotations and covers roughly 70% range of motion of the head-neck of a typical able-bodied adult. The hardware is lightweight (1.5 kilogram) and wearable, with a pair of pads and a soft band attached to the shoulders and the forehead, respectively. A parallel mechanism connecting the shoulder pads and the headband was designed to meet the empirical human movement data. This design choice is novel where the parasitic motion (translation of the head) was parameterized and optimized to address misalignment between the robot and the user's head. A user can control this neck brace to assist intended head-neck movement through input devices, including hand-held joysticks, keyboards, and eye-trackers. This provides a potential solution to remediate head drop. Additionally, this robotic brace is developed into a versatile platform to train and study head-neck movements. The robot was designed to be highly transparent to the user and features different force controllers. Therefore, it can be used to assess the free movement of the head-neck and mimic different interactions between a therapist and a patient. The modalities of this neck brace have been validated with different users. To the best of our knowledge, this robotic neck brace is the first in the literature to assist, train, and study head-neck movements