735 research outputs found

    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

    Robot Autonomy for Surgery

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    Autonomous surgery involves having surgical tasks performed by a robot operating under its own will, with partial or no human involvement. There are several important advantages of automation in surgery, which include increasing precision of care due to sub-millimeter robot control, real-time utilization of biosignals for interventional care, improvements to surgical efficiency and execution, and computer-aided guidance under various medical imaging and sensing modalities. While these methods may displace some tasks of surgical teams and individual surgeons, they also present new capabilities in interventions that are too difficult or go beyond the skills of a human. In this chapter, we provide an overview of robot autonomy in commercial use and in research, and present some of the challenges faced in developing autonomous surgical robots

    Computer Assisted Orthopedic Surgery in TKA

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    From Concept to Market: Surgical Robot Development

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    Surgical robotics and supporting technologies have really become a prime example of modern applied information technology infiltrating our everyday lives. The development of these systems spans across four decades, and only the last few years brought the market value and saw the rising customer base imagined already by the early developers. This chapter guides through the historical development of the most important systems, and provide references and lessons learnt for current engineers facing similar challenges. A special emphasis is put on system validation, assessment and clearance, as the most commonly cited barrier hindering the wider deployment of a system

    A clinical review of robotic navigation in total knee arthroplasty: historical systems to modern design.

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    Robotic-assisted total knee arthroplasty (RA-TKA) has shown improved reproducibility and precision in mechanical alignment restoration, with improvement in early functional outcomes and 90-day episode of care cost savings compared to conventional TKA in some studies. However, its value is still to be determined.Current studies of RA-TKA systems are limited by short-term follow-up and significant heterogeneity of the available systems.In today\u27s paradigm shift towards an increased emphasis on quality of care while curtailing costs, providing value-based care is the primary goal for healthcare systems and clinicians. As robotic technology continues to develop, longer-term studies evaluating implant survivorship and complications will determine whether the initial capital is offset by improved outcomes.Future studies will have to determine the value of RA-TKA based on longer-term survivorships, patient-reported outcome measures, functional outcomes, and patient satisfaction measures

    The future of robotic surgery

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    © 2018 Royal College of Surgeons.For 20 years Intuitive Surgical’s da Vinci® system has held the monopoly in minimally invasive robotic surgery. Restrictive patenting, a well-developed marketing strategy and a high-quality product have protected the company’s leading market share.1 However, owing to the nuances of US patenting law, many of Intuitive Surgical’s earliest patents will be expiring in the next couple of years. With such a shift in backdrop, many of Intuitive Surgical’s competitors (from medical and industrial robotic backgrounds) have initiated robotic programmes – some of which are available for clinical use now. The next section of the review will focus on new and developing robotic systems in the field of minimally invasive surgery (Table 1), single-site surgery (Table 2), natural orifice transluminal endoscopic surgery (NOTES) and non-minimally invasive robotic systems (Table 3).Peer reviewedFinal Published versio

    Factors influencing wider acceptance of Computer Assisted Orthopaedic Surgery (CAOS) technologies for Total Joint Arthroplasty

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    Computer-assisted orthopaedic surgery (CAOS) promises to improve outcomes of joint arthroplasty through better alignment and orientation of implants, but take up has so far been modest. Following an overview of CAOS technologies covering image-guided surgery, image-free and robotic systems, several factors for lack of penetration are identified. These include poor validation of accuracy, lack of standardisation, inappropriate clinical outcomes measures for assessing and comparing technologies, unresolved debate about the effectiveness of minimally invasive surgery, and issues of medical device regulations, cost, autonomy of surgeons to choose equipment, ergonomics and training. The paper concludes that dialogue between surgeons and manufacturers is needed to develop standardised measurements and outcomes scoring systems that are more appropriate for technology comparisons, and encourages an increased awareness of user requirements

    Navigation with Local Sensors in Surgical Robotics

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    Recent Advancements in Augmented Reality for Robotic Applications: A Survey

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    Robots are expanding from industrial applications to daily life, in areas such as medical robotics, rehabilitative robotics, social robotics, and mobile/aerial robotics systems. In recent years, augmented reality (AR) has been integrated into many robotic applications, including medical, industrial, human–robot interactions, and collaboration scenarios. In this work, AR for both medical and industrial robot applications is reviewed and summarized. For medical robot applications, we investigated the integration of AR in (1) preoperative and surgical task planning; (2) image-guided robotic surgery; (3) surgical training and simulation; and (4) telesurgery. AR for industrial scenarios is reviewed in (1) human–robot interactions and collaborations; (2) path planning and task allocation; (3) training and simulation; and (4) teleoperation control/assistance. In addition, the limitations and challenges are discussed. Overall, this article serves as a valuable resource for working in the field of AR and robotic research, offering insights into the recent state of the art and prospects for improvement

    Intraoperative tissue classification methods in orthopedic and neurological surgeries: A systematic review

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    Accurate tissue differentiation during orthopedic and neurological surgeries is critical, given that such surgeries involve operations on or in the vicinity of vital neurovascular structures and erroneous surgical maneuvers can lead to surgical complications. By now, the number of emerging technologies tackling the problem of intraoperative tissue classification methods is increasing. Therefore, this systematic review paper intends to give a general overview of existing technologies. The review was done based on the PRISMA principle and two databases: PubMed and IEEE Xplore. The screening process resulted in 60 full-text papers. The general characteristics of the methodology from extracted papers included data processing pipeline, machine learning methods if applicable, types of tissues that can be identified with them, phantom used to conduct the experiment, and evaluation results. This paper can be useful in identifying the problems in the current status of the state-of-the-art intraoperative tissue classification methods and designing new enhanced techniques
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