Design, Modeling and Control of a Magnetostriction-based Force Feedback System for Robot-assisted Cardiovascular Intervention Systems

Magnetorheological elastomers (MREs), as a class of smart materials, have a property called Magnetostriction means mechanical properties, including deformation of MREs, could be changed in response to an external magnetic field. Because of the controllable deformation, MRE is a suitable candidate for rendering the loss of haptic feedback in Robot-Assisted Cardiovascular (RCI) applications. In the recently-designed such force feedback systems, i.e. TorMag, the effect of matrix shear modulus and filler volume percentage was not studied comprehensively. Tormag also exposed limitations in force range. In the current study, a previously proposed and validated constitutive model of MREs was adopted. Then, twelve MREs with three silicon rubber matrices and four filler volume fractions were fabricated and characterized to improve the limitations mentioned above in Tormag. The average relative error between analytical force range and experiment was 10.2\%, while the maximum force range was 5.29 N (stiffest matrix and 40\% filler), and the minimum range was 1.06 N (softest matrix and 10\% filler). Increasing filler percentage from 10\% to 40\% increased the force feedback range up to 288\%. The state-space analysis of Tormag revealed that this system did not fully cover the required force range and zero force rendering. As an approach, structural optimization of the system is performed using the local and global optimization process. Next, a neural network (NN)-based model as the control framework was proposed and validated to obtain the necessary force for the desired input data. Then, a nearest neighbour search (NNS) method was added to the NN model to find the required magnetic field for a force-displacement profile as input. The proposed neural network accurately predicted the force-displacement behaviour of three types of MREs ($R^2=0.97$, mean-absolute-error=1.26 N). Also, the NN+ NNS model successfully obtained the required magnetic field (mean-absolute error=3.64 mT)

Bio-Inspired Soft Artificial Muscles for Robotic and Healthcare Applications

Soft robotics and soft artificial muscles have emerged as prolific research areas and have gained substantial traction over the last two decades. There is a large paradigm shift of research interests in soft artificial muscles for robotic and medical applications due to their soft, flexible and compliant characteristics compared to rigid actuators. Soft artificial muscles provide safe human-machine interaction, thus promoting their implementation in medical fields such as wearable assistive devices, haptic devices, soft surgical instruments and cardiac compression devices. Depending on the structure and material composition, soft artificial muscles can be controlled with various excitation sources, including electricity, magnetic fields, temperature and pressure. Pressure-driven artificial muscles are among the most popular soft actuators due to their fast response, high exertion force and energy efficiency. Although significant progress has been made, challenges remain for a new type of artificial muscle that is easy to manufacture, flexible, multifunctional and has a high length-to-diameter ratio. Inspired by human muscles, this thesis proposes a soft, scalable, flexible, multifunctional, responsive, and high aspect ratio hydraulic filament artificial muscle (HFAM) for robotic and medical applications. The HFAM consists of a silicone tube inserted inside a coil spring, which expands longitudinally when receiving positive hydraulic pressure. This simple fabrication method enables low-cost and mass production of a wide range of product sizes and materials. This thesis investigates the characteristics of the proposed HFAM and two implementations, as a wearable soft robotic glove to aid in grasping objects, and as a smart surgical suture for perforation closure. Multiple HFAMs are also combined by twisting and braiding techniques to enhance their performance. In addition, smart textiles are created from HFAMs using traditional knitting and weaving techniques for shape-programmable structures, shape-morphing soft robots and smart compression devices for massage therapy. Finally, a proof-of-concept robotic cardiac compression device is developed by arranging HFAMs in a special configuration to assist in heart failure treatment. Overall this fundamental work contributes to the development of soft artificial muscle technologies and paves the way for future comprehensive studies to develop HFAMs for specific medical and robotic requirements

Proceedings of the 2018 Canadian Society for Mechanical Engineering (CSME) International Congress

Published proceedings of the 2018 Canadian Society for Mechanical Engineering (CSME) International Congress, hosted by York University, 27-30 May 2018