283 research outputs found

    Shape Localization and Recognition using a Magnetorheological-fluid Haptic Display

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    Smart materials such as magnetorheological fluids (MRF) offer an interesting technology for use in haptic displays as changes in the magnetic field are rapid, reversible, and controllable. These interfaces have been evaluated in a number of medical and surgical simulators where they can provide cues regarding the viscoelastic properties of tissues. The objective of the present set of experiments was first to determine whether a shape embedded in the MRF could be precisely localized and second whether 10 shapes rendered in a MRF haptic display could be accurately identified. It was also of interest to determine how the information transfer associated with this type of haptic display compares to that achieved using other haptic channels of communication. The overall performance of participants at identifying the shapes rendered in the MRF was good with a mean score of 73 percent correct and an Information Transfer (IT) of 2.2 bits. Participants could also localize a rigid object in the display accurately. These findings indicate that this technology has potential for use in training manual palpation skills and in exploring haptic shape perception in dynamic environments

    Robotic simulators for tissue examination training with multimodal sensory feedback

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    Tissue examination by hand remains an essential technique in clinical practice. The effective application depends on skills in sensorimotor coordination, mainly involving haptic, visual, and auditory feedback. The skills clinicians have to learn can be as subtle as regulating finger pressure with breathing, choosing palpation action, monitoring involuntary facial and vocal expressions in response to palpation, and using pain expressions both as a source of information and as a constraint on physical examination. Patient simulators can provide a safe learning platform to novice physicians before trying real patients. This paper reviews state-of-the-art medical simulators for the training for the first time with a consideration of providing multimodal feedback to learn as many manual examination techniques as possible. The study summarizes current advances in tissue examination training devices simulating different medical conditions and providing different types of feedback modalities. Opportunities with the development of pain expression, tissue modeling, actuation, and sensing are also analyzed to support the future design of effective tissue examination simulators

    Performance Factors in Neurosurgical Simulation and Augmented Reality Image Guidance

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    Virtual reality surgical simulators have seen widespread adoption in an effort to provide safe, cost-effective and realistic practice of surgical skills. However, the majority of these simulators focus on training low-level technical skills, providing only prototypical surgical cases. For many complex procedures, this approach is deficient in representing anatomical variations that present clinically, failing to challenge users’ higher-level cognitive skills important for navigation and targeting. Surgical simulators offer the means to not only simulate any case conceivable, but to test novel approaches and examine factors that influence performance. Unfortunately, there is a void in the literature surrounding these questions. This thesis was motivated by the need to expand the role of surgical simulators to provide users with clinically relevant scenarios and evaluate human performance in relation to image guidance technologies, patient-specific anatomy, and cognitive abilities. To this end, various tools and methodologies were developed to examine cognitive abilities and knowledge, simulate procedures, and guide complex interventions all within a neurosurgical context. The first chapter provides an introduction to the material. The second chapter describes the development and evaluation of a virtual anatomical training and examination tool. The results suggest that learning occurs and that spatial reasoning ability is an important performance predictor, but subordinate to anatomical knowledge. The third chapter outlines development of automation tools to enable efficient simulation studies and data management. In the fourth chapter, subjects perform abstract targeting tasks on ellipsoid targets with and without augmented reality guidance. While the guidance tool improved accuracy, performance with the tool was strongly tied to target depth estimation – an important consideration for implementation and training with similar guidance tools. In the fifth chapter, neurosurgically experienced subjects were recruited to perform simulated ventriculostomies. Results showed anatomical variations influence performance and could impact outcome. Augmented reality guidance showed no marked improvement in performance, but exhibited a mild learning curve, indicating that additional training may be warranted. The final chapter summarizes the work presented. Our results and novel evaluative methodologies lay the groundwork for further investigation into simulators as versatile research tools to explore performance factors in simulated surgical procedures

    Microscope Embedded Neurosurgical Training and Intraoperative System

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    In the recent years, neurosurgery has been strongly influenced by new technologies. Computer Aided Surgery (CAS) offers several benefits for patients\u27 safety but fine techniques targeted to obtain minimally invasive and traumatic treatments are required, since intra-operative false movements can be devastating, resulting in patients deaths. The precision of the surgical gesture is related both to accuracy of the available technological instruments and surgeon\u27s experience. In this frame, medical training is particularly important. From a technological point of view, the use of Virtual Reality (VR) for surgeon training and Augmented Reality (AR) for intra-operative treatments offer the best results. In addition, traditional techniques for training in surgery include the use of animals, phantoms and cadavers. The main limitation of these approaches is that live tissue has different properties from dead tissue and that animal anatomy is significantly different from the human. From the medical point of view, Low-Grade Gliomas (LGGs) are intrinsic brain tumours that typically occur in younger adults. The objective of related treatment is to remove as much of the tumour as possible while minimizing damage to the healthy brain. Pathological tissue may closely resemble normal brain parenchyma when looked at through the neurosurgical microscope. The tactile appreciation of the different consistency of the tumour compared to normal brain requires considerable experience on the part of the neurosurgeon and it is a vital point. The first part of this PhD thesis presents a system for realistic simulation (visual and haptic) of the spatula palpation of the LGG. This is the first prototype of a training system using VR, haptics and a real microscope for neurosurgery. This architecture can be also adapted for intra-operative purposes. In this instance, a surgeon needs the basic setup for the Image Guided Therapy (IGT) interventions: microscope, monitors and navigated surgical instruments. The same virtual environment can be AR rendered onto the microscope optics. The objective is to enhance the surgeon\u27s ability for a better intra-operative orientation by giving him a three-dimensional view and other information necessary for a safe navigation inside the patient. The last considerations have served as motivation for the second part of this work which has been devoted to improving a prototype of an AR stereoscopic microscope for neurosurgical interventions, developed in our institute in a previous work. A completely new software has been developed in order to reuse the microscope hardware, enhancing both rendering performances and usability. Since both AR and VR share the same platform, the system can be referred to as Mixed Reality System for neurosurgery. All the components are open source or at least based on a GPL license

    Real-time hybrid cutting with dynamic fluid visualization for virtual surgery

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    It is widely accepted that a reform in medical teaching must be made to meet today's high volume training requirements. Virtual simulation offers a potential method of providing such trainings and some current medical training simulations integrate haptic and visual feedback to enhance procedure learning. The purpose of this project is to explore the capability of Virtual Reality (VR) technology to develop a training simulator for surgical cutting and bleeding in a general surgery

    A Virtual University Infrastructure For Orthopaedic Surgical Training With Integrated Simulation

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    This thesis pivots around the fulcrum of surgical, educational and technological factors. Whilst there is no single conclusion drawn, it is a multidisciplinary thesis exploring the juxtaposition of different academic domains that have a significant influence upon each other. The relationship centres on the engineering and computer science factors in learning technologies for surgery. Following a brief introduction to previous efforts developing surgical simulation, this thesis considers education and learning in orthopaedics, the design and building of a simulator for shoulder surgery. The thesis considers the assessment of such tools and embedding into a virtual learning environment. It explains how the performed experiments clarified issues and their actual significance. This leads to discussion of the work and conclusions are drawn regarding the progress of integration of distributed simulation within the healthcare environment, suggesting how future work can proceed

    Serious Games and Mixed Reality Applications for Healthcare

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    Virtual reality (VR) and augmented reality (AR) have long histories in the healthcare sector, offering the opportunity to develop a wide range of tools and applications aimed at improving the quality of care and efficiency of services for professionals and patients alike. The best-known examples of VR–AR applications in the healthcare domain include surgical planning and medical training by means of simulation technologies. Techniques used in surgical simulation have also been applied to cognitive and motor rehabilitation, pain management, and patient and professional education. Serious games are ones in which the main goal is not entertainment, but a crucial purpose, ranging from the acquisition of knowledge to interactive training.These games are attracting growing attention in healthcare because of their several benefits: motivation, interactivity, adaptation to user competence level, flexibility in time, repeatability, and continuous feedback. Recently, healthcare has also become one of the biggest adopters of mixed reality (MR), which merges real and virtual content to generate novel environments, where physical and digital objects not only coexist, but are also capable of interacting with each other in real time, encompassing both VR and AR applications.This Special Issue aims to gather and publish original scientific contributions exploring opportunities and addressing challenges in both the theoretical and applied aspects of VR–AR and MR applications in healthcare
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