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

Haptic Hand Exoskeleton for Precision Grasp Simulation

This paper outlines the design and the development of a novel robotic hand exoskeleton (HE) conceived for haptic interaction in the context of virtual reality (VR) and teleoperation (TO) applications. The device allows exerting controlled forces on fingertips of the index and thumb of the operator. The new exoskeleton features several design solutions adopted with the aim of optimizing force accuracy and resolution. The use of remote centers of motion mechanisms allows achieving a compact and lightweight design. An improved stiffness of the transmission and reduced requirements for the electromechanical actuators are obtained thanks to a novel principle for integrating speed reduction into torque transmission systems. A custom designed force sensor and integrated electronics are employed to further improve performances. The electromechanical design of the device and the experimental characterization are presented

Driving device for a hand movement without external force

People with disabilities have limitations in activities of daily life such as grasping a glass of water or moving an object. Orthotic products that improve or restore the functionality of the musculoskeletal system of a patient contribute to some extent to overcome the limitations described. So does the hand brace, used to treat musculoskeletal disorders caused by various diseases (rheumatic disorders, neurological, orthopedic and others). The paper simulates a novel exoskeleton helping to grasp any object. The novelty of this mechanism is that works without external energy, it works with a wrist movement that generates a kinetic movement and helps to grasp objects with an extra force. The orthosis facilitates the functionality, being comfortable and easy to be used by the patient. It is adaptable to hand size and finger length of the patient.Peer ReviewedPostprint (published version

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

Novel soft bending actuator based power augmentation hand exoskeleton controlled by human intention

This article presents the development of a soft material power augmentation wearable robot using novel bending soft artificial muscles. This soft exoskeleton was developed as a human hand power augmentation system for healthy or partially hand disabled individuals. The proposed prototype serves healthy manual workers by decreasing the muscular effort needed for grasping objects. Furthermore, it is a power augmentation wearable robot for partially hand disabled or post-stroke patients, supporting and augmenting the fingers’ grasping force with minimum muscular effort in most everyday activities. This wearable robot can fit any adult hand size without the need for any mechanical system changes or calibration. Novel bending soft actuators are developed to actuate this power augmentation device. The performance of these actuators has been experimentally assessed. A geometrical kinematic analysis and mathematical output force model have been developed for the novel actuators. The performance of this mathematical model has been proven experimentally with promising results. The control system of this exoskeleton is created by hybridization between cascaded position and force closed loop intelligent controllers. The cascaded position controller is designed for the bending actuators to follow the fingers in their bending movements. The force controller is developed to control the grasping force augmentation. The operation of the control system with the exoskeleton has been experimentally validated. EMG signals were monitored during the experiments to determine that the proposed exoskeleton system decreased the muscular efforts of the wearer

Hand-Tool-Tissue Interaction Forces in Neurosurgery for Haptic Rendering

Haptics provides sensory stimuli that represent the interaction with a virtual or telemanipulated object, and it is considered a valuable navigation and manipulation tool during tele-operated surgical procedures. Haptic feedback can be provided to the user via cutaneous information and kinesthetic feedback. Sensory subtraction removes the kinesthetic component of the haptic feedback, having only the cutaneous component provided to the user. Such a technique guarantees a stable haptic feedback loop, while it keeps the transparency of the tele-operation system high, which means that the system faithfully replicates and render back the user's directives. This work focuses on checking whether the interaction forces during a bench model neurosurgery operation can lie in the solely cutaneous perception of the human finger pads. If this assumption is found true, it would be possible to exploit sensory subtraction techniques for providing surgeons with feedback from neurosurgery. We measured the forces exerted to surgical tools by three neurosurgeons performing typical actions on a brain phantom, using contact force sensors, whilst the forces exerted by the tools to the phantom tissue were recorded using a load cell placed under the brain phantom box. The measured surgeon-tool contact forces were 0.01 - 3.49 N for the thumb and 0.01 - 6.6 N for index and middle finger, whereas the measured tool- tissue interaction forces were from six to eleven times smaller than the contact forces, i.e., 0.01 - 0.59 N. The measurements for the contact forces fit the range of the cutaneous sensitivity for the human finger pad, thus, we can say that, in a tele-operated robotic neurosurgery scenario, it would possible to render forces at the fingertip level by conveying haptic cues solely through the cutaneous channel of the surgeon's finger pads. This approach would allow high transparenc