474 research outputs found

    Prevalence of haptic feedback in robot-mediated surgery : a systematic review of literature

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    © 2017 Springer-Verlag. This is a post-peer-review, pre-copyedit version of an article published in Journal of Robotic Surgery. The final authenticated version is available online at: https://doi.org/10.1007/s11701-017-0763-4With the successful uptake and inclusion of robotic systems in minimally invasive surgery and with the increasing application of robotic surgery (RS) in numerous surgical specialities worldwide, there is now a need to develop and enhance the technology further. One such improvement is the implementation and amalgamation of haptic feedback technology into RS which will permit the operating surgeon on the console to receive haptic information on the type of tissue being operated on. The main advantage of using this is to allow the operating surgeon to feel and control the amount of force applied to different tissues during surgery thus minimising the risk of tissue damage due to both the direct and indirect effects of excessive tissue force or tension being applied during RS. We performed a two-rater systematic review to identify the latest developments and potential avenues of improving technology in the application and implementation of haptic feedback technology to the operating surgeon on the console during RS. This review provides a summary of technological enhancements in RS, considering different stages of work, from proof of concept to cadaver tissue testing, surgery in animals, and finally real implementation in surgical practice. We identify that at the time of this review, while there is a unanimous agreement regarding need for haptic and tactile feedback, there are no solutions or products available that address this need. There is a scope and need for new developments in haptic augmentation for robot-mediated surgery with the aim of improving patient care and robotic surgical technology further.Peer reviewe

    A Review of Virtual Reality Based Training Simulators for Orthopaedic Surgery

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    This review presents current virtual reality based training simulators for hip, knee and other orthopaedic surgery, including elective and trauma surgical procedures. There have not been any reviews focussing on hip and knee orthopaedic simulators. A comparison of existing simulator features is provided to identify what is missing and what is required to improve upon current simulators. In total 11 total hip replacement pre-operative planning tools were analysed, plus 9 hip trauma fracture training simulators. Additionally 9 knee arthroscopy simulators and 8 other orthopaedic simulators were included for comparison. The findings are that for orthopaedic surgery simulators in general, there is increasing use of patient-specific virtual models which reduce the learning curve. Modelling is also being used for patient-specific implant design and manufacture. Simulators are being increasingly validated for assessment as well as training. There are very few training simulators available for hip replacement, yet more advanced virtual reality is being used for other procedures such as hip trauma and drilling. Training simulators for hip replacement and orthopaedic surgery in general lag behind other surgical procedures for which virtual reality has become more common. Further developments are required to bring hip replacement training simulation up to date with other procedures. This suggests there is a gap in the market for a new high fidelity hip replacement and resurfacing training simulator

    A review of virtual reality based training simulators for orthopaedic surgery

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    This is the author accepted manuscript. The final version is available from Elsevier via the DOI in this recordThis review presents current virtual reality based training simulators for hip, knee and other orthopaedic surgery, including elective and trauma surgical procedures. There have not been any reviews focussing on hip and knee orthopaedic simulators. A comparison of existing simulator features is provided to identify what is missing and what is required to improve upon current simulators. In total 11 hip replacements pre-operative planning tools were analysed, plus 9 hip trauma fracture training simulators. Additionally 9 knee arthroscopy simulators and 8 other orthopaedic simulators were included for comparison. The findings are that for orthopaedic surgery simulators in general, there is increasing use of patient-specific virtual models which reduce the learning curve. Modelling is also being used for patient-specific implant design and manufacture. Simulators are being increasingly validated for assessment as well as training. There are very few training simulators available for hip replacement, yet more advanced virtual reality is being used for other procedures such as hip trauma and drilling. Training simulators for hip replacement and orthopaedic surgery in general lag behind other surgical procedures for which virtual reality has become more common. Further developments are required to bring hip replacement training simulation up to date with other procedures. This suggests there is a gap in the market for a new high fidelity hip replacement and resurfacing training simulator.Wessex Academic Health Science Network (Wessex AHSN) Innovation and Wealth Creation Accelerator Fund 2014/15Bournemouth Universit

    Patient-specific simulation for autonomous surgery

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    An Autonomous Robotic Surgical System (ARSS) has to interact with the complex anatomical environment, which is deforming and whose properties are often uncertain. Within this context, an ARSS can benefit from the availability of patient-specific simulation of the anatomy. For example, simulation can provide a safe and controlled environment for the design, test and validation of the autonomous capabilities. Moreover, it can be used to generate large amounts of patient-specific data that can be exploited to learn models and/or tasks. The aim of this Thesis is to investigate the different ways in which simulation can support an ARSS and to propose solutions to favor its employability in robotic surgery. We first address all the phases needed to create such a simulation, from model choice in the pre-operative phase based on the available knowledge to its intra-operative update to compensate for inaccurate parametrization. We propose to rely on deep neural networks trained with synthetic data both to generate a patient-specific model and to design a strategy to update model parametrization starting directly from intra-operative sensor data. Afterwards, we test how simulation can assist the ARSS, both for task learning and during task execution. We show that simulation can be used to efficiently train approaches that require multiple interactions with the environment, compensating for the riskiness to acquire data from real surgical robotic systems. Finally, we propose a modular framework for autonomous surgery that includes deliberative functions to handle real anatomical environments with uncertain parameters. The integration of a personalized simulation proves fundamental both for optimal task planning and to enhance and monitor real execution. The contributions presented in this Thesis have the potential to introduce significant step changes in the development and actual performance of autonomous robotic surgical systems, making them closer to applicability to real clinical conditions

    Robots and tools for remodeling bone

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    The field of robotic surgery has progressed from small teams of researchers repurposing industrial robots, to a competitive and highly innovative subsection of the medical device industry. Surgical robots allow surgeons to perform tasks with greater ease, accuracy, or safety, and fall under one of four levels of autonomy; active, semi-active, passive, and remote manipulator. The increased accuracy afforded by surgical robots has allowed for cementless hip arthroplasty, improved postoperative alignment following knee arthroplasty, and reduced duration of intraoperative fluoroscopy among other benefits. Cutting of bone has historically used tools such as hand saws and drills, with other elaborate cutting tools now used routinely to remodel bone. Improvements in cutting accuracy and additional options for safety and monitoring during surgery give robotic surgeries some advantages over conventional techniques. This article aims to provide an overview of current robots and tools with a common target tissue of bone, proposes a new process for defining the level of autonomy for a surgical robot, and examines future directions in robotic surgery

    Shared control for natural motion and safety in hands-on robotic surgery

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    Hands-on robotic surgery is where the surgeon controls the tool's motion by applying forces and torques to the robot holding the tool, allowing the robot-environment interaction to be felt though the tool itself. To further improve results, shared control strategies are used to combine the strengths of the surgeon with those of the robot. One such strategy is active constraints, which prevent motion into regions deemed unsafe or unnecessary. While research in active constraints on rigid anatomy has been well-established, limited work on dynamic active constraints (DACs) for deformable soft tissue has been performed, particularly on strategies which handle multiple sensing modalities. In addition, attaching the tool to the robot imposes the end effector dynamics onto the surgeon, reducing dexterity and increasing fatigue. Current control policies on these systems only compensate for gravity, ignoring other dynamic effects. This thesis presents several research contributions to shared control in hands-on robotic surgery, which create a more natural motion for the surgeon and expand the usage of DACs to point clouds. A novel null-space based optimization technique has been developed which minimizes the end effector friction, mass, and inertia of redundant robots, creating a more natural motion, one which is closer to the feeling of the tool unattached to the robot. By operating in the null-space, the surgeon is left in full control of the procedure. A novel DACs approach has also been developed, which operates on point clouds. This allows its application to various sensing technologies, such as 3D cameras or CT scans and, therefore, various surgeries. Experimental validation in point-to-point motion trials and a virtual reality ultrasound scenario demonstrate a reduction in work when maneuvering the tool and improvements in accuracy and speed when performing virtual ultrasound scans. Overall, the results suggest that these techniques could increase the ease of use for the surgeon and improve patient safety.Open Acces

    Concept and Design of a Hand-held Mobile Robot System for Craniotomy

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    This work demonstrates a highly intuitive robot for Surgical Craniotomy Procedures. Utilising a wheeled hand-held robot, to navigate the Craniotomy Drill over a patient\u27s skull, the system does not remove the surgeons from the procedure, but supports them during this critical phase of the operation

    Intraoperative Planning and Execution of Arbitrary Orthopedic Interventions Using Handheld Robotics and Augmented Reality

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    The focus of this work is a generic, intraoperative and image-free planning and execution application for arbitrary orthopedic interventions using a novel handheld robotic device and optical see-through glasses (AR). This medical CAD application enables the surgeon to intraoperatively plan the intervention directly on the patient’s bone. The glasses and all the other instruments are accurately calibrated using new techniques. Several interventions show the effectiveness of this approach

    The Effect of Robotic Technology on Perioperative Outcomes in Total Knee Arthroplasty

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    Introduction Robotic technology has recently regained momentum in total knee arthroplasty (TKA) but the effects of this technology on accuracy of implant positioning, intraoperative soft tissue injury and postoperative functional rehabilitation remain unknown. The objectives of this research thesis were to compare a comprehensive range of radiological objectives and perioperative outcomes in conventional jig-based TKA versus robotic-arm assisted TKA, and use optical motion capture technology to quantify the effects of anterior cruciate ligament (ACL) and posterior cruciate ligament (PCL) resection on knee biomechanics. Methods A series of prospective cohort studies were undertaken in patients with established knee osteoarthritis undergoing primary conventional jig-based TKA versus robotic-arm assisted TKA. Predefined radiological and perioperative study outcomes were recorded by independent observers. Optical motion capture technology during robotic TKA was used to quantify the effects of ACL and PCL resection on knee biomechanics. Results Robotic-arm assisted TKA was associated with improved accuracy of implant positioning, reduced periarticular soft tissue injury, decreased bone trauma, improved postoperative functional rehabilitation, and reduced early systemic inflammatory response compared to conventional jig-based TKA. The Macroscopic Soft Tissue Injury (MASTI) classification system was developed and validated for grading intraoperative periarticular soft tissue injury and bone trauma during TKA. ACL resection created flexion-extension mismatch by increasing the extension gap more than the flexion gap, whilst PCL resection increased the flexion gap proportionally more than the extension gap and created mediolateral laxity in knee flexion but not in extension. Conclusion Robotic-arm assisted TKA was associated with increased accuracy of implant positioning, reduced iatrogenic soft tissue injury, and improved functional rehabilitation compared to conventional jig-based TKA. ACL and PCL resections created unique changes in knee biomechanics that affected flexion-extension gaps and mediolateral soft tissue tension during TKA. On the basis of this thesis, further clinical trials have been established to determine the long-term clinical significance of these findings
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