Virtual and Augmented Reality in Medical Education

Virtual reality (VR) and augmented reality (AR) are two contemporary simulation models that are currently upgrading medical education. VR provides a 3D and dynamic view of structures and the ability of the user to interact with them. The recent technological advances in haptics, display systems, and motion detection allow the user to have a realistic and interactive experience, enabling VR to be ideal for training in hands-on procedures. Consequently, surgical and other interventional procedures are the main fields of application of VR. AR provides the ability of projecting virtual information and structures over physical objects, thus enhancing or altering the real environment. The integration of AR applications in the understanding of anatomical structures and physiological mechanisms seems to be beneficial. Studies have tried to demonstrate the validity and educational effect of many VR and AR applications, in many different areas, employed via various hardware platforms. Some of them even propose a curriculum that integrates these methods. This chapter provides a brief history of VR and AR in medicine, as well as the principles and standards of their function. Finally, the studies that show the effect of the implementation of these methods in different fields of medical training are summarized and presented

Performance Factors in Neurosurgical Simulation and Augmented Reality Image Guidance

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

Augmented Reality Simulation Modules for EVD Placement Training and Planning Aids

When a novice neurosurgeon performs a psychomotor surgical task (e.g., tool navigation into brain structures), a potential risk of damaging healthy tissues and eloquent brain structures is unavoidable. When novices make multiple hits, thus a set of undesirable trajectories is created, and resulting in the potential for surgical complications. Thus, it is important that novices not only aim for a high-level of surgical mastery but also receive deliberate training in common neurosurgical procedures and underlying tasks. Surgical simulators have emerged as an adequate candidate as effective method to teach novices in safe and free-error training environments. The design of neurosurgical simulators requires a comprehensive approach to development and. In that in mind, we demonstrate a detailed case study in which two Augmented Reality (AR) training simulation modules were designed and implemented through the adoption of Model-driven Engineering. User performance evaluation is a key aspect of the surgical simulation validity. Many AR surgical simulators become obsolete; either they are not sufficient to support enough surgical scenarios, or they were validated according to subjective assessments that did not meet every need. Accordingly, we demonstrate the feasibility of the AR simulation modules through two user studies, objectively measuring novices’ performance based on quantitative metrics. Neurosurgical simulators are prone to perceptual distance underestimation. Few investigations were conducted for improving user depth perception in head-mounted display-based AR systems with perceptual motion cues. Consequently, we report our investigation’s results about whether or not head motion and perception motion cues had an influence on users’ performance

TIMS: A Tactile Internet-Based Micromanipulation System with Haptic Guidance for Surgical Training

Microsurgery involves the dexterous manipulation of delicate tissue or fragile structures such as small blood vessels, nerves, etc., under a microscope. To address the limitation of imprecise manipulation of human hands, robotic systems have been developed to assist surgeons in performing complex microsurgical tasks with greater precision and safety. However, the steep learning curve for robot-assisted microsurgery (RAMS) and the shortage of well-trained surgeons pose significant challenges to the widespread adoption of RAMS. Therefore, the development of a versatile training system for RAMS is necessary, which can bring tangible benefits to both surgeons and patients. In this paper, we present a Tactile Internet-Based Micromanipulation System (TIMS) based on a ROS-Django web-based architecture for microsurgical training. This system can provide tactile feedback to operators via a wearable tactile display (WTD), while real-time data is transmitted through the internet via a ROS-Django framework. In addition, TIMS integrates haptic guidance to `guide' the trainees to follow a desired trajectory provided by expert surgeons. Learning from demonstration based on Gaussian Process Regression (GPR) was used to generate the desired trajectory. User studies were also conducted to verify the effectiveness of our proposed TIMS, comparing users' performance with and without tactile feedback and/or haptic guidance.Comment: 8 pages, 7 figures. For more details of this project, please view our website: https://sites.google.com/view/viewtims/hom

Clinicians' Perspectives of a Novel Home-based Multidisciplinary Telehealth Service for Patients with Chronic Spinal Pain

Chronic spinal pain conditions can often be successfully managed by a non-surgical, multidisciplinary approach, however many individuals are unable to access such specialised services within their local community. A possible solution may be the delivery of care via telerehabilitation. This study aimed to evaluate clinicians’ perspectives on providing clinical care via telerehabilitation during the early implementation of a novel spinal telerehabilitation service.  Eight clinicians’ were recruited, completing surveys at four separate time points. Confidence in providing treatment via telerehabilitation significantly improved with time (?2(3)=16.22, p=0.001). Clinicians became significantly more accepting of telerehabilitation being a time- (?2(3)=11.237, p=0.011), and cost-effective (?2(3)=9.466, p=0.024) platform in which they could deliver care. Overall satisfaction was high, with technology becoming easier to use (p=0.026) and ability to establish rapport significantly improved with experience (p=0.043). Understanding clinicians’ perspectives throughout the early implementation phase of a new telerehabilitation service is a critical component in determining long-term sustainability.

Telemedicine in neurosurgery during SARS-CoV2 Pandemic

Introduction and purposeFirst large scale introduction and research of telecommunication in medicine was conducted in year 1977. However, until current SARS-CoV-2 Pandemic, telemedicine has been used only in emergency interventions or in cases in which only remote healthcare provision services were available. Healthcare was forced to implement telemedical changes in a scale broader beyond imagination, in order to limit the risk of COVID transmission and preserve the scarce healthcare resources. Especially in surgical fields, such as neurosurgery, which strongly depend on on-site procedures, this time has been extremely demanding. The aim of the study is to present the current views and effectiveness of implementation of telemedicine in neurosurgery during SARS-CoV2 pandemic. Substantial articles on implementation and challenges of telemedicine in neurosurgery from period 02.2020-09.2020 were analyzed.  Current state of knowledgeWithin 581 articles of PubMED database, 15 substantial articles on advancements of telemedicine in neurosurgery during SARS-CoV2 Pandemic were included in the review. 60% of the articles discussed telemedicine implementation and improvements made, 40% of the articles discussed the legislative changes, telemedicine recommendations and good pratices. Most of the articles noted the significant increase in provision of services using telemedicine and high satisfaction of patients and professionals from the remote visits. However, many challenges of the technology has been encountered including difficulties in conducting proper remote examination, lack of standarized protocols, concerns of the ethical and social matters, such as patient’s confidentiality and privacy concerns, digital illiteracy in patients, and the need for more advanced hardware and more secure software for the provision of high quality services. Conclusions Reviewed research presents significant improvements in introduction of telemedicine in neurosurgical field in times of COVID Pandemic, however due to many multidisciplinary concerns regarding telemedicine implementation, face-to-face examination and communication still should take priority over the telemedicine interventions in the non-emergency future.  

Immersive Facility Management – a methodological approach based on BIM and Mixed Reality for training and maintenance operations

Innovation technology in industries including manufacturing and aerospace is moving towards the use of Mixed Reality (MR) and advanced tools while Architecture, Engineering and Construction (AEC) sector is still remaining behind it. Moreover, the use of immersive technologies in the AEC digital education, as well as for professional training, is still little considered. Augmented and Mixed reality (AR/MR) have the capability to provide a “X-ray vision”, showing hidden objects in a virtual/real overlay. This feature in the digital object visualization is extremely valuable for improving operation performance and maintenance activities. The present study gives an overview of literature about the methodologies to integrate virtual technologies such as AR/MR and Building Information Modelling (BIM) to provide an immersive technology framework for training purposes together with the Digital Twin Model (DTM)-based approach. Furthermore, the Facility Management (FM) tasks’ training on complex building systems can benefit from a virtual learning approach since it provides a collaborative environment enhancing and optimizing efficiency and productivity in FM learning strategies. For this purpose, the technological feasibility is analysed in the proposed case study, focusing on the realization of a methodological framework prototype of immersive and interactive environment for building systems’ FM. Cloud computing technologies able to deal with complex and extensive information databases and to support users' navigation in geo-referenced and immersive virtual interfaces are include as well. Those ones enable the DTM-based opera-tion for building maintenance both in real-time FM operators’ training and FM tasks’ optimization

State of the art and practice in AI in education

Recent developments in Artificial Intelligence (AI) have generated great expectations for the future impact of AI in education and learning (AIED). Often these expectations have been based on misunderstanding current technical possibilities, lack of knowledge about state-of-the-art AI in education, and exceedingly narrow views on the functions of education in society. In this article, we provide a review of existing AI systems in education and their pedagogic and educational assumptions. We develop a typology of AIED systems and describe different ways of using AI in education and learning, show how these are grounded in different interpretations of what AI and education is or could be, and discuss some potential roadblocks on the AIED highway

From Concept to Market: Surgical Robot Development

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

The role of artificial intelligence in surgical simulation

Artificial Intelligence (AI) plays an integral role in enhancing the quality of surgical simulation, which is increasingly becoming a popular tool for enriching the training experience of a surgeon. This spans the spectrum from facilitating preoperative planning, to intraoperative visualisation and guidance, ultimately with the aim of improving patient safety. Although arguably still in its early stages of widespread clinical application, AI technology enables personal evaluation and provides personalised feedback in surgical training simulations. Several forms of surgical visualisation technologies currently in use for anatomical education and presurgical assessment rely on different AI algorithms. However, while it is promising to see clinical examples and technological reports attesting to the efficacy of AI-supported surgical simulators, barriers to wide-spread commercialisation of such devices and software remain complex and multifactorial. High implementation and production costs, scarcity of reports evidencing the superiority of such technology, and intrinsic technological limitations remain at the forefront. As AI technology is key to driving the future of surgical simulation, this paper will review the literature delineating its current state, challenges, and prospects. In addition, a consolidated list of FDA/CE approved AI-powered medical devices for surgical simulation is presented, in order to shed light on the existing gap between academic achievements and the universal commercialisation of AI-enabled simulators. We call for further clinical assessment of AI-supported surgical simulators to support novel regulatory body approved devices and usher surgery into a new era of surgical education