51 research outputs found

    R&D ALLIANCE PARTNER ATTRIBUTES AND INNOVATION PERFORMANCE: A FUZZY SET QUALITATIVE COMPARATIVE ANALYSIS

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    Because R&D alliances are important means for fostering firm innovation performance, research has investigated their key drivers. However, multiple configurations of R&D alliance drivers may lead to firm innovation performance. Drawing upon the knowledge-based view of alliances, we investigate configurations of R&D alliance factors leading to high innovation performance in allied firms by focusing on partner attributes (i.e., technological relatedness, competitive overlap, experience, relative size). Then, using a fuzzy set qualitative comparative analysis, we dissect the configurations of these factors in 27 R&D alliances formed by 54 telecom firms worldwide. We find that good R&D alliance partners are technologically related competitors with no experience in forming R&D alliances. Alternatively, competitors can achieve high innovation performance when they have experience in doing R&D alliances and are not technologically related. Drawing on these findings, we submit a set of propositions with relevant implications for the knowledge-based view of alliances and coopetition research

    Preliminary analysis of force-torque measurements for robot-assisted fracture surgery

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    © 2015 IEEE. Our group at Bristol Robotics Laboratory has been working on a new robotic system for fracture surgery that has been previously reported [1]. The robotic system is being developed for distal femur fractures and features a robot that manipulates the small fracture fragments through small percutaneous incisions and a robot that re-aligns the long bones. The robots controller design relies on accurate and bounded force and position parameters for which we require real surgical data. This paper reports preliminary findings of forces and torques applied during bone and soft tissue manipulation in typical orthopaedic surgery procedures. Using customised orthopaedic surgical tools we have collected data from a range of orthopaedic surgical procedures at Bristol Royal Infirmary, UK. Maximum forces and torques encountered during fracture manipulation which involved proximal femur and soft tissue distraction around it and reduction of neck of femur fractures have been recorded and further analysed in conjunction with accompanying image recordings. Using this data we are establishing a set of technical requirements for creating safe and dynamically stable minimally invasive robot-assisted fracture surgery (RAFS) systems

    Editorial: Translational research in medical robotics—challenges and opportunities

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    In the last few decades, emerging medical technologies and the growing number of commercial robotic platforms have supported diagnosis and treatment of both acute and chronic diseases of the human body, improving the clinical outcome, reducing trauma, shortening the patient recovery time, and increasing postoperative survival rates (Troccaz et al., 2019). Medical robots–including surgical robots, rehabilitation and assistive robots, and hospital automation robots–with improved safety, efficacy and reduced costs, robotic platforms will soon approach a tipping point, moving beyond early adopters to become part of the mainstream clinical practice, defining the future of smart hospitals and home-based patient care. Surgical robots promise to enhance minimally invasive surgery with precise instrument control, intuitive hand-eye coordination, and superior dexterity within tight spaces (Dupont et al., 2021). Rehabilitation robotics facilitates robot-assisted therapy and automated recovery training (Xue et al., 2021). Assistive robots aid individuals with physical limitations, either enhancing or compensating for functions, promoting independence, and lessening the burden on caregivers (Trainum et al., 2023). Additionally, robotic systems can automate hospital operations, spanning service robots aiding clinicians to robots in labs for high-throughput testing (Kwon et al., 2022). These technologies aim to revolutionize healthcare, offering improved patient care and operational efficiency

    Image-Guided Surgical Robotic System for Percutaneous Reduction of Joint Fractures

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    Complex joint fractures often require an open surgical procedure, which is associated with extensive soft tissue damages and longer hospitalization and rehabilitation time. Percutaneous techniques can potentially mitigate these risks but their application to joint fractures is limited by the current sub-optimal 2D intra-operative imaging (fluoroscopy) and by the high forces involved in the fragment manipulation (due to the presence of soft tissue, e.g., muscles) which might result in fracture malreduction. Integration of robotic assistance and 3D image guidance can potentially overcome these issues. The authors propose an image-guided surgical robotic system for the percutaneous treatment of knee joint fractures, i.e., the robot-assisted fracture surgery (RAFS) system. It allows simultaneous manipulation of two bone fragments, safer robot-bone fixation system, and a traction performing robotic manipulator. This system has led to a novel clinical workflow and has been tested both in laboratory and in clinically relevant cadaveric trials. The RAFS system was tested on 9 cadaver specimens and was able to reduce 7 out of 9 distal femur fractures (T- and Y-shape 33-C1) with acceptable accuracy (≈1 mm, ≈5°), demonstrating its applicability to fix knee joint fractures. This study paved the way to develop novel technologies for percutaneous treatment of complex fractures including hip, ankle, and shoulder, thus representing a step toward minimally-invasive fracture surgeries

    End-to-End Real-time Catheter Segmentation with Optical Flow-Guided Warping during Endovascular Intervention

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    Accurate real-time catheter segmentation is an important pre-requisite for robot-assisted endovascular intervention. Most of the existing learning-based methods for catheter segmentation and tracking are only trained on small-scale datasets or synthetic data due to the difficulties of ground-truth annotation. Furthermore, the temporal continuity in intraoperative imaging sequences is not fully utilised. In this paper, we present FW-Net, an end-to-end and real-time deep learning framework for endovascular intervention. The proposed FW-Net has three modules: a segmentation network with encoder-decoder architecture, a flow network to extract optical flow information, and a novel flow-guided warping function to learn the frame-to-frame temporal continuity. We show that by effectively learning temporal continuity, the network can successfully segment and track the catheters in real-time sequences using only raw ground-truth for training. Detailed validation results confirm that our FW-Net outperforms state-of-the-art techniques while achieving real-time performance.Comment: ICRA 202

    Vision-based real-time position control of a semi-automated system for robot-assisted joint fracture surgery

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    Purpose: Joint fracture surgery quality can be improved by robotic system with high-accuracy and high-repeatability fracture fragment manipulation. A new real-time vision-based system for fragment manipulation during robot-assisted fracture surgery was developed and tested. Methods: The control strategy was accomplished by merging fast open-loop control with vision-based control. This two-phase process is designed to eliminate the open-loop positioning errors by closing the control loop using visual feedback provided by an optical tracking system. Evaluation of the control system accuracy was performed using robot positioning trials, and fracture reduction accuracy was tested in trials on ex vivo porcine model.Results: The system resulted in high fracture reduction reliability with a reduction accuracy of 0.09mm (translations) and of (Formula presented.) (rotations), maximum observed errors in the order of 0.12mm (translations) and of (Formula presented.) (rotations), and a reduction repeatability of 0.02mm and (Formula presented.). Conclusions: The proposed vision-based system was shown to be effective and suitable for real joint fracture surgical procedures, contributing a potential improvement of their quality

    Intra-operative fiducial-based CT/fluoroscope image registration framework for image-guided robot-assisted joint fracture surgery

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    Purpose Joint fractures must be accurately reduced minimising soft tissue damages to avoid negative surgical outcomes. To this regard, we have developed the RAFS surgical system, which allows the percutaneous reduction of intra-articular fractures and provides intra-operative real-time 3D image guidance to the surgeon. Earlier experiments showed the effectiveness of the RAFS system on phantoms, but also key issues which precluded its use in a clinical application. This work proposes a redesign of the RAFS’s navigation system overcoming the earlier version’s issues, aiming to move the RAFS system into a surgical environment. Methods The navigation system is improved through an image registration framework allowing the intra-operative registration between pre-operative CT images and intra-operative fluoroscopic images of a fractured bone using a custom-made fiducial marker. The objective of the registration is to estimate the relative pose between a bone fragment and an orthopaedic manipulation pin inserted into it intra-operatively. The actual pose of the bone fragment can be updated in real time using an optical tracker, enabling the image guidance. Results Experiments on phantom and cadavers demonstrated the accuracy and reliability of the registration framework, showing a reduction accuracy (sTRE) of about 0.88 ±0.2mm (phantom) and 1.15±0.8mm (cadavers). Four distal femur fractures were successfully reduced in cadaveric specimens using the improved navigation system and the RAFS system following the new clinical workflow (reduction error 1.2±0.3mm, 2±1∘). Conclusion Experiments showed the feasibility of the image registration framework. It was successfully integrated into the navigation system, allowing the use of the RAFS system in a realistic surgical application

    Responsible innovation across borders: tensions, paradoxes and possibilities

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    In March 2014 a group of early career researchers and academics from São Paulo state and from the UK met at the University of Campinas to participate in a workshop on ‘Responsible Innovation and the Governance of Socially Controversial Technologies’. In this Perspective we describe key reflections and observations from the workshop discussions, paying particular attention to the discourse of responsible innovation from a cross-cultural perspective. We describe a number of important tensions, paradoxes and opportunities that emerged over the three days of the workshop

    Navigation system for robot-assisted intra-articular lower-limb fracture surgery

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    Purpose In the surgical treatment for lower-leg intra-articular fractures, the fragments have to be positioned and aligned to reconstruct the fractured bone as precisely as possible, to allow the joint to function correctly again. Standard procedures use 2D radiographs to estimate the desired reduction position of bone fragments. However, optimal correction in a 3D space requires 3D imaging. This paper introduces a new navigation system that uses pre-operative planning based on 3D CT data and intra-operative 3D guidance to virtually reduce lower-limb intra-articular fractures. Physical reduction in the fractures is then performed by our robotic system based on the virtual reduction. Methods 3D models of bone fragments are segmented from CT scan. Fragments are pre-operatively visualized on the screen and virtually manipulated by the surgeon through a dedicated GUI to achieve the virtual reduction in the fracture. Intra-operatively, the actual position of the bone fragments is provided by an optical tracker enabling real-time 3D guidance. The motion commands for the robot connected to the bone fragment are generated, and the fracture physically reduced based on the surgeon’s virtual reduction. To test the system, four femur models were fractured to obtain four different distal femur fracture types. Each one of them was subsequently reduced 20 times by a surgeon using our system. Results The navigation system allowed an orthopaedic surgeon to virtually reduce the fracture with a maximum residual positioning error of 0.95±0.3mm (translational) and 1.4∘±0.5∘ (rotational). Correspondent physical reductions resulted in an accuracy of 1.03 ± 0.2 mm and 1.56∘±0.1∘, when the robot reduced the fracture. Conclusions Experimental outcome demonstrates the accuracy and effectiveness of the proposed navigation system, presenting a fracture reduction accuracy of about 1 mm and 1.5∘, and meeting the clinical requirements for distal femur fracture reduction procedures

    Inovação responsável através de fronteiras: tensões, paradoxos e possibilidades

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    In March 2014 a group of early career researchers and academics from São Paulo state and from the UK met at the University of Campinas to participate in a workshop on ‘Responsible Innovation and the Governance of Socially Controversial Technologies’. In this Perspective we describe key reflections and observations from the workshop discussions, paying particular attention to the discourse of responsible innovation from a cross-cultural perspective. We describe a number of important tensions, paradoxes and opportunities that emerged over the three days of the workshop
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