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The intelligent service of the digital twin machine tool provides convenience for the human operation interaction in the machine tool, and the real-time operation interaction between the human and the machine tool has high requirements for the real-time machining model simulation algorithm. Firstly, this paper proposes a simulation method based on the combination of augmented reality (AR) and digital twin of machine tool machining virtual-real fusion. Secondly, to improve the real-time interoperability between human and machine tools in the AR virtual-real fusion machining process, this paper proposes a fast Dexel model generation method based on binary tree space segmentation. The method is based on the 3D model of the workpiece preprocessing to generate a one-way Dexel model of the binary tree storage structure, using the tool and the workpiece overlap envelope in the binary tree structure to determine the interference region, and ultimately calculating the intersection line between the one-way generation line and the tool geometry to get the model of the workpiece after cutting. By analyzing the real-time performance of the algorithm, the algorithm satisfies the simulation calculation of Dexel models of different scales. Finally, through the example of real-time interactive operation between human and machine tool AR, the results show that the average display frame rate of this algorithm in the machining process reaches 55–60 frames, and the parameter error between the model after virtual machining and the actual machining model is within 1.3%. At the same time, 100 people were randomly selected to carry out AR interaction training, and the real-time performance experience of AR virtual-real fusion machining was comprehensively evaluated, and the results showed that the system can meet the real-time demand of interaction operation of most participants. [ABSTRACT FROM AUTHOR]

Terahertz imaging is one of the most promising approaches for non-destructive control. An interesting approach to having cost-effective systems is to use frequency-modulated continuous wave (FMCW) radars with a raster scan configuration. Nevertheless, current systems using linear stages or robotic arms have the disadvantage of being heavy, requiring a long scan and not allowing a direct visualization of the result being measured. In addition, it is complex to evaluate the position of the measuring point on the real object, particularly if it is not flat. Here, we propose to solve these previous challenges with a portable system combining an FMCW radar with an augmented reality (AR) interface using a smartphone. This system achieves two goals: (i) first is to achieve data acquisition in the AR environment and (ii) the second is to make possible the visualization of data, even after post-processing, in the AR environment. [ABSTRACT FROM AUTHOR]

Introduction: Simulation training is an important component of medical education. In former studies, diagnostic simulation training for direct and indirect funduscopy was already proven to be an effective training method. In this prospective controlled trial, we investigated the effect of simulator-based fundus biomicroscopy training. Methods: After completing a 1-week ophthalmology clerkship, medical students at Saarland University Medical Center (n = 30) were block-randomized into two groups: The traditional group received supervised training examining the fundus of classmates using a slit lamp; the simulator group was trained using the Slit Lamp Simulator. All participants had to pass an Objective Structured Clinical Examination (OSCE); two masked ophthalmological faculty trainers graded the students' skills when examining patient's fundus using a slit lamp. A subjective assessment form and post-assessment surveys were obtained. Data were described using median (interquartile range [IQR]). Results: Twenty-five students (n = 14 in the simulator group, n = 11 in the traditional group) (n = 11) were eligible for statistical analysis. Interrater reliability was verified as significant for the overall score as well as for all subtasks (≤ 0.002) except subtask 1 (p = 0.12). The overall performance of medical students in the fundus biomicroscopy OSCE was statistically ranked significantly higher in the simulator group (27.0 [5.25]/28.0 [3.0] vs. 20.0 [7.5]/16.0 [10.0]) by both observers with an interrater reliability of IRR < 0.001 and a significance level of p = 0.003 for observer 1 and p < 0.001 for observer 2. For all subtasks, the scores given to students trained using the simulator were consistently higher than those given to students trained traditionally. The students' post-assessment forms confirmed these results. Students could learn the practical backgrounds of fundus biomicroscopy (p = 0.04), the identification (p < 0.001), and localization (p < 0.001) of pathologies significantly better with the simulator. Conclusions: Traditional supervised methods are well complemented by simulation training. Our data indicate that the simulator helps with first patient contacts and enhances students' capacity to examine the fundus biomicroscopically. [ABSTRACT FROM AUTHOR]

Human errors are prevalent in manual assembly line statistics, but humans are still a necessary and numerous working force for assembly tasks. Since faster and shorter production cycles lead to higher mental efforts, an alternative to decrease the cognitive load and errors of manual assembly lines is using augmented reality (AR). AR increases system interaction and assists operators in the step-by-step of any tasks performed. Its use allows granular production data, enabling an increase in quality control and timely detection of assembly problems. However, AR alone is not enough to avoid demotivation and lack of engagement in the task, which is repetitive. Gamification can become an auxiliary resource to increase operators' motivation and engagement. This paper presents a system model to integrate AR and gamification for a manual assembly line of printed circuit boards (PCBs) called GRAAL, used to develop an actual system for PCB assembly, which can guide operators using AR but also tracks down their efficiency and efficacy which is then used for gamifying their performance. A prototype system was implemented and assessed by 34 specialist respondents. TAM 3 (Technology Acceptance Model 3) Questionnaire was used to assess the system, which allowed us to find that GRAAL was well accepted (all scores were above the center of a Likert scale from 1 to 7 values), suggesting that GRAAL may be useful as an auxiliary resource to manual assembly lines. We conclude that modeling a system that merges AR and gamification is feasible but a non-trivial task in industry. The system's features are dependent on conditioning factors such as Application Environment, Application Context, Application Audience, AR hardware, and gamification elements. [ABSTRACT FROM AUTHOR]

Clustering is a popular data analysis technique that can explore the structure of data through cluster analysis. Similar data are put into the same cluster, while dissimilar data allocate to other clusters. The similarity/dissimilarity among data objects is determined using a distance function. Further, clustering algorithms aim to choose the optimal set of centroids for obtaining better partitioning, but clustering accuracy is always susceptible. This issue of clustering is addressed through meta-heuristic algorithms. This research also aims to handle the accuracy issue and presents a new algorithm for effective cluster analysis. The proposed clustering algorithm is inspired by a water flow optimizer (WFO). The WFO algorithm performance is validated on the well-defined clustering problems based on SSE, accuracy (AR) and detection rate (DR) parameters. The results indicate that the WFO algorithm gets higher clustering results in terms of SSE, AR and DR than the same class of algorithms. The performance is also validated using Friedman statistical test followed by a post hoc test. Results indicated that the proposed WFO gets better statistical results than other clustering algorithms. [ABSTRACT FROM AUTHOR]

As the field of three-dimensional (3D) visualization rapidly advances, how healthcare professionals perceive and interact with real and virtual objects becomes increasingly complex. Lack of clear vocabulary to navigate the changing landscape of 3D visualization hinders clinical and scientific advancement, particularly within the field of radiology. In this article, we provide foundational definitions and illustrative examples for 3D visualization in clinical care, with a focus on the pediatric patient population. We also describe how understanding 3D visualization tools enables better alignment of hardware and software products with intended use-cases, thereby maximizing impact for patients, families, and healthcare professionals. [ABSTRACT FROM AUTHOR]

Rapid technological advancements have created opportunities for new solutions in various industries, including healthcare. One exciting new direction in this field of innovation is the combination of skin-based technologies and augmented reality (AR). These dermatological devices allow for the continuous and non-invasive measurement of vital signs and biomarkers, enabling the real-time diagnosis of anomalies, which have applications in telemedicine, oncology, dermatology, and early diagnostics. Despite its many potential benefits, there is a substantial information vacuum regarding using flexible photonics in conjunction with augmented reality for medical purposes. This review explores the current state of dermal augmented reality and flexible optics in skin-conforming sensing platforms by examining the obstacles faced thus far, including technical hurdles, demanding clinical validation standards, and problems with user acceptance. Our main areas of interest are skills, chiroptical properties, and health platform applications, such as optogenetic pixels, spectroscopic imagers, and optical biosensors. My skin-enhanced spherical dichroism and powerful spherically polarized light enable thorough physical inspection with these augmented reality devices: diabetic tracking, skin cancer diagnosis, and cardiovascular illness: preventative medicine, namely blood pressure screening. We demonstrate how to accomplish early prevention using case studies and emergency detection. Finally, it addresses real-world obstacles that hinder fully realizing these materials' extraordinary potential in advancing proactive and preventative personalized medicine, including technical constraints, clinical validation gaps, and barriers to widespread adoption. [ABSTRACT FROM AUTHOR]

Introduction: This study aimed to investigate the accuracy of cup position and assess the changes in pelvic tilt during primary total hip arthroplasty (THA) in the lateral decubitus position using a new computed tomography (CT)-based navigation system with augmented reality (AR) technology. Materials and methods: There were 37 cementless THAs performed using a CT-based navigation system with AR technology in the lateral decubitus position and 63 cementless THAs performed using manual implant techniques in the lateral decubitus position in this retrospective study. Postoperative cup radiographic inclination and anteversion were measured using postoperative CT, and the proportion of hips within Lewinnek's safe zone was analyzed and compared between the two groups. The mean absolute values of navigation error were assessed. Intraoperative pelvic tilt angles were also recorded using navigation system. Results: The percentage of cups inside Lewinnek's safe zone was 100% in the navigation group and 35% in the control group (p < 0.001). The mean absolute values of navigation error in inclination and anteversion were 2.9° ± 2.1° and 3.3° ± 2.4°, respectively. The mean abduction angle of the pelvis was 5.1° ± 4.8° after placing the patients in the lateral decubitus position and 4.1° ± 6.0° after cup placement. The mean posterior tilt angle was 6.8° ± 5.1° after placing the patients in the lateral decubitus position and 9.3° ± 5.9° after cup placement. The mean internal rotation angle was 14.8° ± 7.4° after cup placement. There were no correlations between the navigation error in inclination or anteversion and the absolute values of changes of the pelvic tilt angle at any phase. Conclusions: Although progressive pelvic motion occurred in THA in the lateral decubitus position, especially during cup placement, the CT-based navigation system with AR technology improved cup placement accuracy. [ABSTRACT FROM AUTHOR]

Purpose: This bibliometric analysis of the top 100 cited articles on extended reality (XR) in neurosurgery aimed to reveal trends in this research field. Gender differences in authorship and global distribution of the most-cited articles were also addressed. Methods: A Web of Science electronic database search was conducted. The top 100 most-cited articles related to the scope of this review were retrieved and analyzed for trends in publications, journal characteristics, authorship, global distribution, study design, and focus areas. After a brief description of the top 100 publications, a comparative analysis between spinal and cranial publications was performed. Results: From 2005, there was a significant increase in spinal neurosurgery publications with a focus on pedicle screw placement. Most articles were original research studies, with an emphasis on augmented reality (AR). In cranial neurosurgery, there was no notable increase in publications. There was an increase in studies assessing both AR and virtual reality (VR) research, with a notable emphasis on VR compared to AR. Education, surgical skills assessment, and surgical planning were more common themes in cranial studies compared to spinal studies. Female authorship was notably low in both groups, with no significant increase over time. The USA and Canada contributed most of the publications in the research field. Conclusions: Research regarding the use of XR in neurosurgery increased significantly from 2005. Cranial research focused on VR and resident education while spinal research focused on AR and neuronavigation. Female authorship was underrepresented. North America provides most of the high-impact research in this area. [ABSTRACT FROM AUTHOR]

The installation and commissioning of production units are crucial for establishing efficient production systems. However, current approaches frequently face challenges such as lengthy commissioning cycles, low productivity, and limited intelligence. This study aims to leverage the synergistic capabilities of augmented reality (AR) technology and digital twin technology in the context of Industry 4.0 to address the challenges faced in production commissioning. Therefore, to achieve intelligent commissioning, optimize the installation and commissioning process of production systems and increase productivity. This paper proposes a novel virtual-real fusion commissioning method utilizing AR for production commissioning. Initially, a digital twin modeling and process planning simulation method is introduced for virtual-real fusion production units; secondly, real-time commissioning and fusion display of the production process are enabled through AR technology; lastly, the approach is applied to the operation and commissioning of the motor rotor–embedded wire production unit. The results demonstrate that the system can simulate the entire production logic and operation even in the absence of certain equipment while visualizing the production process and product status. Furthermore, compared to traditional physical production commissioning, this method has achieved a 43.6% reduction in the commissioning cycle and resulted in space cost savings of 21.8%. Subsequent applications validate the soundness of the proposed modeling and fusion commissioning approach and provide practical theoretical and methodological guidance for digital twin modeling and production commissioning in production systems. [ABSTRACT FROM AUTHOR]

Augmented reality (AR) has been used for navigation during total hip arthroplasty (THA). AR computed tomography (CT)-based navigation systems and AR-based portable navigation systems that use smartphones can also be used. This study compared the accuracy of cup insertion during THA using AR-CT-based and portable AR-based navigation systems. Patients with symptomatic hip disease who underwent primary THA in the supine position using both AR CT-based and portable AR-based navigation systems simultaneously between October 2021 and July 2023 were included. The primary outcome of this study was the absolute difference between cup angles in the intraoperative navigation record and those measured on postoperative CT. The secondary outcome was to determine the factors affecting the absolute value of the navigation error in radiographic inclination (RI) and radiographic anteversion (RA) of the cup, including sex, age, body mass index, left or right side, approach, and preoperative pelvic tilt. This study included 94 consecutive patients. There were 11 men and 83 women, with a mean age of 68 years. The mean absolute errors of RI were 2.7° ± 2.0° in the AR CT-based and 3.3° ± 2.4° in the portable AR-based navigation system. The mean absolute errors of RA were 2.5° ± 2.1° in the AR CT-based navigation system and 2.3° ± 2.2° in the portable AR-based navigation system. No significant differences were observed in RI or RA of the cup between the two navigation systems (RI: p = 0.706; RA: p = 0.329). No significant factors affected the absolute value of the navigation errors in RI and RA. In conclusion, there were no differences in the accuracy of cup insertion between the AR CT-based and portable AR-based navigation systems. [ABSTRACT FROM AUTHOR]

Higher education faculty members incorporate technologies into their teaching and learning practices in higher education for the benefit of their learners. Hence, general technologies, such as presentation software, online classrooms, and learning management systems are ubiquitous in higher education teaching practices. However, emerging technologies (i.e., augmented reality, virtual reality, robotics, tangible user interfaces, wearable technologies, and mixed reality) are not currently in wide use in higher education. As emerging technologies can broaden access to content and increase accessibility for all learners, investigating faculty members' intention to incorporate these technologies was explored in this study. Faculty participants from higher education institutions (N = 174) completed a 33-item survey, based on the theoretical framework of the decomposed theory of planned behavior. A path analysis of factors that influence faculty members' intention to integrate emerging technologies in teaching and learning were conducted. Results indicated that attitude, subjective norms, and perceived behavioral control are indicators of intention to use emerging technologies in teaching and learning. [ABSTRACT FROM AUTHOR]

Although numerous studies have demonstrated the potential benefits of augmented reality (AR) in education, the influence of education students' learning experiences on their AR technology acceptance in the classroom has yet to be examined thoroughly. In this empirical study, we explored the affective experiences (i.e., positive emotions, negative emotions, and situational interest) of education students in AR training and examined how their affective experiences influence their AR technology acceptance (i.e., perceived ease of AR use, perceived usefulness of AR, and intention to use AR) by using the partial least squares path modeling method. Our results show that situational interest significantly predicts both the perceived ease of AR use and the perceived usefulness of AR. Moreover, positive emotions significantly predict the perceived ease of AR use. However, negative emotions were not noted as a factor influencing either the perceived ease of AR use or its perceived usefulness. These findings indicate the importance of promoting situational interest and positive emotions in AR training to increase AR technology acceptance among education students in the classroom setting. [ABSTRACT FROM AUTHOR]

Background: Cognitive impairment and chronic fatigue represent common characteristics of the long COVID syndrome. Different non-pharmacological treatments have been proposed, and physiotherapy has been proposed to improve the symptoms. This study aimed to evaluate the effects of a dual-task augmented reality rehabilitation protocol in people with long COVID fatigue and cognitive impairment. Methods and materials: Ten non-hospitalized adults with reported fatigue and "brain fog" symptoms after COVID (7/10 females, 50 years, range 41–58) who participated in 20 sessions of a 1-h "dual-task" training, were compared to 10 long COVID individuals with similar demographics and symptoms (9/10 females, 56 years, range 43–65), who did not participate to any rehabilitation protocol. Cognitive performance was assessed with the Trail Making Test (TMT-A and -B) and Frontal Assessment Battery (FAB), and cardiovascular and muscular fatigue were assessed with the fatigue severity scale (FSS), six-minute walking test and handgrip endurance. Finally, transcranial magnetic stimulation (TMS) investigated cortical excitability. Results: The mixed-factors analysis of variance found a significant interaction effect only in cognitive performance evaluation, suggesting TMT-B execution time decreased (− 15.9 s, 95% CI 7.6–24.1, P = 0.001) and FAB score improved (1.88, 95% CI 2.93–0.82, P = 0.002) only in the physiotherapy group. For the remaining outcomes, no interaction effect was found, and most parameters similarly improved in the two groups. Conclusion: The preliminary results from this study suggest that dual-task rehabilitation could be a feasible protocol to support cognitive symptoms recovery after COVID-19 and could be helpful in those individuals suffering from persisting and invalidating symptoms. [ABSTRACT FROM AUTHOR]

This review synthesizes the literature base evaluating the effects of behavior analytic interventions delivered via augmented reality (AR) technology for individuals with autism. We also conducted a quality review. We identified 14 studies with a majority of the studies (n = 11; 79%) utilizing single-case research design. Of the 14 studies, three met the quality criteria to be classified as "strong" and can offer evidence on the integration of AR technology into the practice of behavior analysis. All three studies taught a functional skill (i.e., tooth brushing and navigation). The remaining studies focused on skill acquisition with zero studies utilizing AR within the context of behavior assessment or behavior reduction interventions. This literature base is emerging with additional research required. [ABSTRACT FROM AUTHOR]

In this work, we present an accurate and quaternion-based solution for the Perspective-n-Point method for determining the position and orientation of a calibrated camera from a set of n 3D points and their corresponding 2D projections on the image plane referred to as AQPnP. Most of the previous PnP methods have not handled the uncertainty of image feature points directly. In the proposed method, uncertainty of image points is integrated into PnP method. This is achieved by mapping the covariance (uncertainty) matrices of the image points to PnP method. It then uses the alternating direction method of multipliers (ADMM) method to minimize the modeled cost function, which has the ability to find the desired solution in real time. The ADMM method solves the system of equations in a manner that is convergent to the global optimal. The ADMM, a widely used operator splitting technique, has drawn significant attention due to its excellent performance in various applications. Quaternion-based rotation parameterization allows AQPnP to be highly accurate in estimating the rotation matrix. We compared AQPnP method with the state-of-the-art PnP methods, and pose estimation results show that our proposed method outperforms better than other methods. [ABSTRACT FROM AUTHOR]

Today, the global prevalence of autism is high and continues to increase dramatically. Effective support and interventions are therefore warranted. Augmented reality (AR), one of the recent modalities of immersive technology, is gaining traction in autism interventions. However, there is currently a lack of reviews on the use of AR in children with autism, and what is more, to the authors' knowledge, no systematic review to date has been carried out to exclusively examine the effects of AR on basic social skills in children with autism. Therefore, an evidence-based systematic review was conducted to fill the gap and answer the specific research question: Can AR support children with an autism diagnosis towards developing or promoting social skills, such as greetings? The initial search yielded a total of 416 records. After excluding duplicate articles and screening the abstract and full text, 13 studies were included for analysis. A narrative approach was employed to synthesise and evaluate the research findings to substantially explore the effects of AR-based social interventions. The favourable role of AR technology in fostering social skills in children diagnosed with autism was widely recognised in the included studies although multiple methodological limitations were identified in relation to the quality of the included studies. Overall, the promising findings may suggest the effectiveness of AR in improving social skills in children with autism. Nonetheless, this field of research still calls for more high-quality studies relying on rigorous methodologies. [ABSTRACT FROM AUTHOR]

This exploratory study uses epistemic network analysis (ENA) to examine the use of extended reality (XR) technologies embedded in post-secondary classes, one in a traditional setting and the other a place-based setting, to examine climate change while utilizing a socioscientific issues (SSI) approach. One group used a virtual reality (VR) application on their smartphones in a traditional class setting to explore four different locations on the Outer Banks of North Carolina, USA (OBX). A second group used an augmented reality (AR) application on their smartphones while visiting the same four locations. Qualitative data was collected after each experience. Analysis of each group's networks indicated that both forms of technology engaged students in the SSI and were beneficial to their learning. However, differences in the networks revealed that virtual reality students made stronger connections between the technology, the physical impacts of climate change, and the political/socioeconomic aspects of climate change. In contrast, the augmented reality students made stronger connections between the technology and learning in general. Implications for practice and future research will be discussed. [ABSTRACT FROM AUTHOR]

With the development of digital technologies, the use of augmented reality in the tourism sector has received increasing attention. However, the understanding of the factors influencing tourists' post-experience intention with augmented reality devices is incomplete and there is a lack of empirical research. This study explores the impact of AR technical factors, individual factors and situational factors on users' post-experience AR usage intention and destination revisit intention through satisfaction based on a socio-technical perspective. The survey data collected from 254 visitors who visited the Liangzhu Museum using the corresponding AR glasses were analysed, and the results showed that the novelty of the technical aspect, the technology trust of the individual aspect and the aesthetics, education and authenticity of the situational aspect influenced visitors' AR usage intention and destination revisit intention through satisfaction. This study has an impact on future research on the application of augmented reality technology to heritage museums. [ABSTRACT FROM AUTHOR]

The concept of geo-localization broadly refers to the process of determining an entity's geographical location, typically in the form of Global Positioning System (GPS) coordinates. The entity of interest may be an image, a sequence of images, a video, a satellite image, or even objects visible within the image. Recently, massive datasets of GPS-tagged media have become available due to smartphones and the internet, and deep learning has risen to prominence and enhanced the performance capabilities of machine learning models. These developments have enabled the rise of image and object geo-localization, which has impacted a wide range of applications such as augmented reality, robotics, self-driving vehicles, road maintenance, and 3D reconstruction. This paper provides a comprehensive survey of visual geo-localization, which may involve either determining the location at which an image has been captured (image geo-localization) or geolocating objects within an image (object geo-localization). We will provide an in-depth study of visual geo-localization including a summary of popular algorithms, a description of proposed datasets, and an analysis of performance results to illustrate the current state of the field. [ABSTRACT FROM AUTHOR]

Episodic Memory (EM) is the neurocognitive capacity to consciously recollect personally experienced events in specific spatio-temporal contexts. Although the relevance of spatial and temporal information is widely acknowledged in the EM literature, it remains unclear whether and how EM performance and organisation is modulated by self-motion, and by motor- and visually- salient environmental features (EFs) of the encoding environment. This study examines whether and how EM is modulated by locomotion and the EFs encountered in a controlled lifelike learning route within a large-scale building. Twenty-eight healthy participants took part in a museum-tour encoding task implemented in walking Augmented Reality (AR) and stationary Virtual Reality (VR) conditions. EM performance and organisation were assessed immediately and 48-hours after trials using a Remember/Familiar recognition paradigm. Results showed a significant positive modulation effect of locomotion on distinctive EM aspects. Findings highlighted a significant performance enhancement effect of stairway-adjacent locations compared to dead-end and mid-route stimuli-presentation locations. The results of this study may serve as design criteria to facilitate neurocognitive rehabilitative interventions of EM. The underlying technological framework developed for this study represents a novel and ecologically sound method for evaluating EM processes in lifelike situations, allowing researchers a naturalistic perspective into the complex nature of EM. [ABSTRACT FROM AUTHOR]

Compared to traditional techniques, augmented reality (AR) confers notable benefits in facilitating complex product assembly processes. The efficacy of AR systems in assembly contexts is notably influenced by the pivotal role of AR instructions. As such, meeting users' demands for AR instructions is crucial during AR-guided assembly processes. In the present study, an investigation was conducted into the influence of complex assembly task types and user assembly experience on their demands for AR instructions. Firstly, complex assembly tasks were categorized into repetitive complex assembly tasks (RAT) and non-repetitive complex assembly tasks (NRAT) based on their complex characteristics. A user study was conducted using HMD-HoloLens 2 as the experimental device. User performances were recorded during iterative execution of AR experimental tasks under the aforementioned task conditions. The specific measures included users' attention process, interface interaction behaviors, assembly errors, and users' subjective experience. The results indicate significant differences in users' demands for AR instructions across different task types. Moreover, users' demands for AR instructions also changed with increasing assembly experience. Through comprehensive analysis, the rules of users' demands for AR instructions were summarized. The present findings enhance the current comprehension of users' demands regarding AR instructions and offer valuable insights for designing and developing efficient AR-guided assembly systems. [ABSTRACT FROM AUTHOR]

Mohs micrographic surgery (MMS) is a cornerstone of dermatological practice. Virtual reality (VR) and augmented reality (AR) technology, initially used for entertainment, have entered healthcare, offering real-time data overlaying a surgeon’s view. This paper explores potential applications of VR and AR in MMS, emphasizing their advantages and limitations. We aim to identify research gaps to facilitate innovation in dermatological surgery. We conducted a PubMed search using the following: “augmented reality” OR “virtual reality” AND “Mohs” or “augmented reality” OR “virtual reality” AND “surgery.” Inclusion criteria were peer-reviewed articles in English discussing these technologies in medical settings. We excluded non-peer-reviewed sources, non-English articles, and those not addressing these technologies in a medical context. VR alleviates patient anxiety and enhances patient satisfaction while serving as an educational tool. It also aids physicians by providing realistic surgical simulations. On the other hand, AR assists in real-time lesion analysis, optimizing incision planning, and refining margin control during surgery. Both of these technologies offer remote guidance for trainee residents, enabling real-time learning and oversight and facilitating synchronous teleconsultations. These technologies may transform dermatologic surgery, making it more accessible and efficient. However, further research is needed to validate their effectiveness, address potential challenges, and optimize seamless integration. All in all, AR and VR enhance real-world environments with digital data, offering real-time surgical guidance and medical insights. By exploring the potential integration of these technologies in MMS, our study identifies avenues for further research to thoroughly understand the role of these technologies to redefine dermatologic surgery, elevating precision, surgical outcomes, and patient experiences. [ABSTRACT FROM AUTHOR]

This study is about the metaverse environment which has recently heard a lot in life. Although many individuals and institutions are interested in metaverse, it is an imaginary future space, and the conceptual framework is not fully drawn. The metaverse is a mix of augmented, virtual, and mixed reality technologies that are predicted to affect our lives over the next decade including our money, possessions, and ownership. So, we examined to forecast metaverse token price using ANN and ANFIS methods. The market value of the five metaverse token firms: opening price, highest value, lowest value, closing price, volume value, and variables, is evaluated between October 17, 2017, and December 15, 2022, by YSA and ANFIS. The ANN method training was carried out using ten hidden layers and the Levenberg–Marquardt algorithm. In the ANFIS method, training was carried out with 100 iterations in a triple mesh structure. At the end of the method training, the training performed with the ANN method was 99.3% successful, and the ANFIS method was 99.1% successful. It is concluded that the model fitness of the R2 values of ANN and ANFIS methods is appropriate at 99.3 and 98.7%, respectively. As a result, ANN and ANFIS methods can be used for the prediction of metaverse token prices for the estimation of financial instruments. ANN and ANFIS are advanced tools for predicting metaverse token prices, with ANFIS having unique features like fuzzy logic. However, using only basic price data is not enough for precise predictions. While the EMA and SMA have less impact, gold (XAU), BTC, ETH, US dollar (USD), Chinese Yuan (CNY), and Brent oil (BRT) are observed to have a moderate impact on determining the market values of metaverse prices. The use of XAU and ETH prices in both ANN and ANFIS methods gives successful results. Especially, we have achieved favorable outcomes when employing the ANN method for analyzing EMA and BTC values. Additionally, we have obtained valuable and successful results by utilizing the ANFIS method for analyzing BRT. Using only opening, highest, lowest, closing prices, and volume values and USD, CNY, BRT, and SMA prices has not demonstrated usefulness in attaining favorable results. The findings of this research indicate that the utilization of the metaverse world has the potential to enhance learning capabilities and motivation, as well as make significant contributions to industrial production and the field of health. However, it is important to note that the existing body of research on the metaverse world remains limited in scope and depth. Users often hold preconceived notions and biases regarding ethical concerns associated with the metaverse world. Additionally, there are significant obstacles that need to be addressed in terms of fulfilling hardware requirements for its implementation. [ABSTRACT FROM AUTHOR]

Bioconservative bioethicists (e.g., Kass, 2002, Human Dignity and Bioethics, 297–331, 2008; Sandel, 2007; Fukuyama, 2003) offer various kinds of philosophical arguments against cognitive enhancement—i.e., the use of medicine and technology to make ourselves “better than well” as opposed to merely treating pathologies. Two notable such bioconservative arguments appeal to ideas about (1) the value of achievement, and (2) authenticity. It is shown here that even if these arguments from achievement and authenticity cut ice against specifically pharmacologically driven cognitive enhancement, they do not extend over to an increasingly viable form of technological cognitive enhancement – namely, cognitive enhancement via augmented reality. An important result is that AR-driven cognitive enhancement aimed at boosting performance in certain cognitive tasks might offer an interesting kind of “sweet spot” for proponents of cognitive enhancement, allowing us to pursue many of the goals of enhancement advocates without running into some of the most prominent objections from bioconservative philosophers. [ABSTRACT FROM AUTHOR]

Objective: Conventional freehand methods of pedicle screw placement are associated with significant complications due to close proximity to neural and vascular structures. Recent advances in augmented reality surgical navigation (ARSN) have led to its adoption into spine surgery. However, little is known regarding its overall accuracy. The purpose of this study is to delineate the overall accuracy of ARSN pedicle screw placement across various models. Methods: A systematic review was conducted of Medline/PubMed, Cochrane and Embase Library databases according to the PRISMA guidelines. Relevant data extracted included reports of pedicle screw placement accuracy and breaches, as defined by the Gertzbein–Robbins classification, in addition to deviation from pre-planned trajectory and entry point. Accuracy was defined as the summation of grade 0 and grade 1 events per the Gertzbein–Robbins classification. Results: Twenty studies reported clinically accurate placed screws. The range of clinically accurate placed screws was 26.3–100%, with 2095 screws (93.1%) being deemed clinically accurate. Furthermore, 5.4% (112/2088) of screws were reported as grade two breaches, 1.6% (33/2088) grade 3 breaches, 3.1% (29/926) medial breaches and 2.3% (21/926) lateral breaches. Mean linear deviation ranged from 1.3 to 5.99 mm, while mean angular/trajectory deviation ranged 1.6°–5.88°. Conclusion: The results of this study highlight the overall accuracy of ARSN pedicle screw placement. However, further robust prospective studies are needed to accurately compare to conventional methods of pedicle screw placement. [ABSTRACT FROM AUTHOR]

Introduction: The periacetabular osteotomy is a technically demanding procedure with the goal to improve the osseous containment of the femoral head. The options for controlled execution of the osteotomies and verification of the acetabular reorientation are limited. With the assistance of augmented reality, new possibilities are emerging to guide this intervention. However, the scientific knowledge regarding AR navigation for PAO is sparse. Methods: In this cadaveric study, we wanted to find out, if the execution of this complex procedure is feasible with AR guidance, quantify the accuracy of the execution of the three-dimensional plan, and find out what has to be done to proceed to real surgery. Therefore, an AR guidance for the PAO was developed and applied on 14 human hip cadavers. The guidance included performance of the four osteotomies and reorientation of the acetabular fragment. The osteotomy starting points, the orientation of the osteotomy planes, as well as the reorientation of the acetabular fragment were compared to the 3D planning. Results: The mean 3D distance between planned and performed starting points was between 9 and 17 mm. The mean angle between planned and performed osteotomies was between 6° and 7°. The mean reorientation error between the planned and performed rotation of the acetabular fragment was between 2° and 11°. Conclusion: The planned correction can be achieved with promising accuracy and without serious errors. Further steps for a translation from the cadaver to the patient have been identified and must be addressed in future work. [ABSTRACT FROM AUTHOR]

Purpose: This study evaluates the nnU-Net for segmenting brain, skin, tumors, and ventricles in contrast-enhanced T1 (T1CE) images, benchmarking it against an established mesh growing algorithm (MGA). Methods: We used 67 retrospectively collected annotated single-center T1CE brain scans for training models for brain, skin, tumor, and ventricle segmentation. An additional 32 scans from two centers were used test performance compared to that of the MGA. The performance was measured using the Dice-Sørensen coefficient (DSC), intersection over union (IoU), 95th percentile Hausdorff distance (HD95), and average symmetric surface distance (ASSD) metrics, with time to segment also compared. Results: The nnU-Net models significantly outperformed the MGA (p < 0.0125) with a median brain segmentation DSC of 0.971 [95CI: 0.945–0.979], skin: 0.997 [95CI: 0.984–0.999], tumor: 0.926 [95CI: 0.508–0.968], and ventricles: 0.910 [95CI: 0.812–0.968]. Compared to the MGA's median DSC for brain: 0.936 [95CI: 0.890, 0.958], skin: 0.991 [95CI: 0.964, 0.996], tumor: 0.723 [95CI: 0.000–0.926], and ventricles: 0.856 [95CI: 0.216–0.916]. NnU-Net performance between centers did not significantly differ except for the skin segmentations Additionally, the nnU-Net models were faster (mean: 1139 s [95CI: 685.0–1616]) than the MGA (mean: 2851 s [95CI: 1482–6246]). Conclusions: The nnU-Net is a fast, reliable tool for creating automatic deep learning-based segmentation pipelines, reducing the need for extensive manual tuning and iteration. The models are able to achieve this performance despite a modestly sized training set. The ability to create high-quality segmentations in a short timespan can prove invaluable in neurosurgical settings. [ABSTRACT FROM AUTHOR]

Emerging technological innovations offer the potential for experiential engagement through virtual scenarios, yet the viability of this approach for educational purposes remains significantly underexplored. This study aims to assess the feasibility of Augmented Reality (AR) and Virtual Reality (VR) technologies in providing users with aesthetic experiences when visiting digital exhibitions. A total of 190 students participated in this investigation. The control group visited traditional exhibits at the Palace Museum in Beijing. This group underwent a survey to evaluate their acquired aesthetic experience. In contrast, the experimental group, comprising 96 students, engaged with VR/AR scenarios at the Palace Museum in Beijing. Accordingly, students in the experimental group were also surveyed to evaluate both their aesthetic experiences and, additionally, their user experiences. The survey results unveiled significant distinctions in aesthetic experiences between students in the control and experimental groups. Moreover, there were notable correlations between individual variables related to user and aesthetic experiences within the experimental group. Furthermore, the study revealed disparities in both user and aesthetic experiences among male and female students. The findings have implications for aesthetic education teachers and officials in the context of developing sound strategies for providing aesthetic experiences to their students. This information is also of interest to employees of museums, exhibitions, and other cultural facilities, who are interested in holding or hold digital exhibitions. [ABSTRACT FROM AUTHOR]

Bodily resizing illusions typically use visual and/or tactile inputs to produce a vivid experience of one's body changing size. Naturalistic auditory input (an input that reflects the natural sounds of a stimulus) has been used to increase illusory experience during the rubber hand illusion, whilst non-naturalistic auditory input can influence estimations of finger length. We aimed to use a non-naturalistic auditory input during a hand-based resizing illusion using augmented reality, to assess whether the addition of an auditory input would increase both subjective illusion strength and measures of performance-based tasks. Forty-four participants completed the following three conditions: no finger stretching, finger stretching without tactile feedback and finger stretching with tactile feedback. Half of the participants had an auditory input throughout all the conditions, whilst the other half did not. After each condition, the participants were given one of the following three performance tasks: stimulated (right) hand dot touch task, non-stimulated (left) hand dot touch task, and a ruler judgement task. Dot tasks involved participants reaching for the location of a virtual dot, whereas the ruler task concerned estimates of the participant's own finger on a ruler whilst the hand was hidden from view. After all trials, the participants completed a questionnaire capturing subjective illusion strength. The addition of auditory input increased subjective illusion strength for manipulations without tactile feedback but not those with tactile feedback. No facilitatory effects of audio were found for any performance task. We conclude that adding auditory input to illusory finger stretching increased subjective illusory experience in the absence of tactile feedback but did not affect performance-based measures. [ABSTRACT FROM AUTHOR]

We present a marker-less AR/DR system that can replace the arm of the user with a virtual bionic prosthesis in real time including finger tracking. For this, we use a mixed reality HMD that provides the user with a stereo image based on video-see-through (VST). We apply chroma-keying to remove the user's arm from each captured image and input reconstructed background information into the removed pixels. Before rendering the prosthesis model into the image, we re-target motion capture data of the user's hand to the kinematic skeleton of the prosthesis to match the current hand pose. This system opens new research possibilities on self- and other-perception of bionic bodies. In a first evaluation study of the system, we propose that users perceive the virtual prosthesis model as a part of their body (i.e., that they experience a sense of ownership). We tested this assumption in a laboratory study with 27 individuals who used the system to perform a series of simple tasks in AR with their prosthesis. We measured body ownership and other measures with self-reports. In support of the hypothesis, users experienced a sense of body ownership. Also, a feeling of self-presence is induced during the task, and participants rated the overall experience as positive. [ABSTRACT FROM AUTHOR]

We are researching a new display device that allows the public to experience augmented reality without wearable devices. In this paper, we implement an image processing system that improves the dynamically changing image quality deterioration, which is a problem unique to optical systems that project images on the real space, and specify the necessary system requirements from the results of verification of the effect. We quantify the characteristics of blur for each of the three primary colors defined as digital image data, and implement image processing that applies filter correction to the input image data during aerial imaging. Since the effect on image quality depends on what kind of imaging optical path is formed, we designed the device structure assuming that it will be applied to signage products, and built an experimental environment that can analyze the aerial image that the user actually sees. The image subjected to the correction process follows an optical path that forms an image in the air, and the user visually recognizes the image with emphasized edges. We compared the results of the actual aerial image and the simulation results, and clarified the system requirements for realizing an image processing system with higher correction accuracy. [ABSTRACT FROM AUTHOR]

Galleries, libraries, archives, and museums are nowadays striving to implement innovative approaches to adequately use and distribute the wealth of knowledge found in cultural heritage. A range of technologies can be used to enhance the viewing experience for visitors and boost the expertise of museologists, art historians, scholars, and audience members. The present work aims to provide an overview of current methods and most pertinent studies addressing the use of the innovative technologies for enhancing the fruition of artifacts in traditional museums in an effort to improve the public experience and education. For all the technologies discussed, the paper focuses on the main results obtained in literature and on their possible implementation in the museal context. The overview demonstrates the liveliness of the world of research in the field of technologies for the digital development of museums and how many technologies commonly used in industry are increasingly finding their way into the cultural sphere. [ABSTRACT FROM AUTHOR]

We propose an augmented reality (AR)-based training system for basketball free-throws. The optimal shot trajectory for free-throws is projected by a head-mounted display according to the shooter's release point. The efficacy of the training system was assessed in novice shooters by comparing changes in success rates and eye-gaze behavior (quiet eye [QE]) between AR-training and control-training groups. The success rate during the AR training with the optimal trajectory did not differ from the pre-training rate; however, in post-AR training, i.e., after removal of the optimal trajectory, the success rate increased. Additionally, AR training increased the QE duration (QED) compared with that recorded during pre- and post-training blocks. In contrast, the control group showed no change in the success rate or QED. These findings imply that our AR training system affected QE behavior and improved free-throwing shooting performance after training. Thus, our system is expected to enhance basketball free-throw shooting performance. [ABSTRACT FROM AUTHOR]

Purpose: This bibliometric analysis of the top 100 cited articles on extended reality (XR) in neurosurgery aimed to reveal trends in this research field. Gender differences in authorship and global distribution of the most-cited articles were also addressed. Methods: A Web of Science electronic database search was conducted. The top 100 most-cited articles related to the scope of this review were retrieved and analyzed for trends in publications, journal characteristics, authorship, global distribution, study design, and focus areas. After a brief description of the top 100 publications, a comparative analysis between spinal and cranial publications was performed. Results: From 2005, there was a significant increase in spinal neurosurgery publications with a focus on pedicle screw placement. Most articles were original research studies, with an emphasis on augmented reality (AR). In cranial neurosurgery, there was no notable increase in publications. There was an increase in studies assessing both AR and virtual reality (VR) research, with a notable emphasis on VR compared to AR. Education, surgical skills assessment, and surgical planning were more common themes in cranial studies compared to spinal studies. Female authorship was notably low in both groups, with no significant increase over time. The USA and Canada contributed most of the publications in the research field. Conclusions: Research regarding the use of XR in neurosurgery increased significantly from 2005. Cranial research focused on VR and resident education while spinal research focused on AR and neuronavigation. Female authorship was underrepresented. North America provides most of the high-impact research in this area. [ABSTRACT FROM AUTHOR]

Purpose: This study evaluates the nnU-Net for segmenting brain, skin, tumors, and ventricles in contrast-enhanced T1 (T1CE) images, benchmarking it against an established mesh growing algorithm (MGA). Methods: We used 67 retrospectively collected annotated single-center T1CE brain scans for training models for brain, skin, tumor, and ventricle segmentation. An additional 32 scans from two centers were used test performance compared to that of the MGA. The performance was measured using the Dice-Sørensen coefficient (DSC), intersection over union (IoU), 95th percentile Hausdorff distance (HD95), and average symmetric surface distance (ASSD) metrics, with time to segment also compared. Results: The nnU-Net models significantly outperformed the MGA (p < 0.0125) with a median brain segmentation DSC of 0.971 [95CI: 0.945–0.979], skin: 0.997 [95CI: 0.984–0.999], tumor: 0.926 [95CI: 0.508–0.968], and ventricles: 0.910 [95CI: 0.812–0.968]. Compared to the MGA’s median DSC for brain: 0.936 [95CI: 0.890, 0.958], skin: 0.991 [95CI: 0.964, 0.996], tumor: 0.723 [95CI: 0.000–0.926], and ventricles: 0.856 [95CI: 0.216–0.916]. NnU-Net performance between centers did not significantly differ except for the skin segmentations Additionally, the nnU-Net models were faster (mean: 1139 s [95CI: 685.0–1616]) than the MGA (mean: 2851 s [95CI: 1482–6246]). Conclusions: The nnU-Net is a fast, reliable tool for creating automatic deep learning-based segmentation pipelines, reducing the need for extensive manual tuning and iteration. The models are able to achieve this performance despite a modestly sized training set. The ability to create high-quality segmentations in a short timespan can prove invaluable in neurosurgical settings. [ABSTRACT FROM AUTHOR]

In augmented reality applications it is essential to know the position and orientation of the user to correctly register virtual 3D content in the user's field of view. For this purpose, visual tracking through simultaneous localization and mapping (SLAM) is often used. However, when applied to the commonly occurring situation where the users are mostly stationary, many methods presented in previous research have two key limitations. First, SLAM techniques alone do not address the problem of global localization with respect to prior models of the environment. Global localization is essential in many applications where multiple users are expected to track within a shared space, such as spectators at a sporting event. Secondly, these methods often assume significant translational movement to accurately reconstruct and track from a local model of the environment, causing challenges for many stationary applications. In this paper, we extend recent research on Spherical Localization and Tracking to support relocalization after tracking failure, as well as global localization in large shared environments, and optimize the method for operation on mobile hardware. We also evaluate various state-of-the-art localization approaches, the robustness of our visual tracking method, and demonstrate the effectiveness of our system in real-life scenarios. [ABSTRACT FROM AUTHOR]

Objective: Dorsal instrumentation using pedicle screws is a standard treatment for multiple spinal pathologies, such as trauma, infection, or degenerative indications. Intraoperative three-dimensional (3D) imaging and navigated pedicle screw placement are used at multiple centers. For the present study, we evaluated a new navigation system enabling augmented reality (AR)-supported pedicle screw placement while integrating navigation cameras into the reference array and drill guide. The present study aimed to evaluate its clinical application regarding safety, efficacy, and accuracy. Methods: A total of 20 patients were operated on between 06/2021 and 01/2022 using the new technique for intraoperative navigation. Intraoperative data with a focus on accuracy and patient safety, including patient outcome, were analyzed. The accuracy of pedicle screw placement was evaluated by intraoperative CT imaging. Results: A median of 8 (4–18) pedicle screws were placed in each case. Percutaneous instrumentation was performed in 14 patients (70%). The duration of pedicle screw placement (duration scan–scan) was 56 ± 26 (30–107) min. Intraoperative screw revision was necessary for 3 of 180 pedicle screws (1.7%). Intraoperatively, no major complications occurred—one case of delay due to software issues and one case of difficult screw placement were reported. Conclusion: The current study's results could confirm the use of the present AR-supported system for navigated pedicle screw placement for dorsal instrumentation in clinical routine. It provides a reliable and safe tool for 3D imaging-based pedicle screw placement, only requires a minimal intraoperative setup, and provides new opportunities by integrating AR. [ABSTRACT FROM AUTHOR]

Simulation training is an educational tool that provides technical and cognitive proficiency in a risk-free environment. Several models have recently been presented in Latin America and the Caribbean (LAC). However, many of them were presented in non-indexed literature and not included in international reviews. This scoping review aims to describe the simulation models developed in LAC for neurosurgery training. Specifically, it focuses on assessing the models developed in LAC, the simulated neurosurgical procedures, the model's manufacturing costs, and the translational outcomes. Simulation models developed in LAC were considered, with no language or time restriction. Cadaveric, ex vivo, animal, synthetic, and virtual/augmented reality models were included for cranial and spinal procedures. We conducted a review according to the PRISMA-ScR, including international and regional reports from indexed and non-indexed literature. Two independent reviewers screened articles. Conflicts were resolved by a third reviewer using Covidence software. We collected data regarding the country of origin, recreated procedure, type of model, model validity, and manufacturing costs. Upon screening 917 studies, 69 models were developed in LAC. Most of them were developed in Brazil (49.28%). The most common procedures were related to general neurosurgery (20.29%), spine (17.39%), and ventricular neuroendoscopy and cerebrovascular (15.94% both). Synthetic models were the most frequent ones (38.98%). The manufacturing cost ranged from 4.00 to 2005.00 US Dollars. To our knowledge, this is the first scoping review about simulation models in LAC, setting the basis for future research studies. It depicts an increasing number of simulation models in the region, allowing a wide range of neurosurgical training in a resource-limited setting. [ABSTRACT FROM AUTHOR]

Due to its natural and fast characteristics, eye tracking, as a novel input modality, has been widely used in head-mounted displays for interaction. However, because of the inadvertent jitter of eyes and limitations of eye tracking devices, the eye-based selection often performs poorly in accuracy and stability compared with other input modalities, especially for small targets. To address this issue, we built a likelihood model by modeling the gaze point distribution and then combined it with Bayesian rules to infer the intended target from the perspective of probability as an alternative to the traditional selection criteria based on boundary judgment. Our investigation shows that using our model improves the selection performance significantly over the conventional ray-casting selection method and using the existing optimal likelihood model, especially in the selection of small targets. [ABSTRACT FROM AUTHOR]

Nowadays, augmented reality (AR) is becoming more and more prevalent and used in many fields, including education. Previous studies have reported the positive effect of AR to advocate the use of AR in the classroom. However, it is unclear whether such a positive effect can be reported for any student. In this study, we recruited students from a Chinese vocational college. Due to the peculiar conditions in China, students in vocational colleges may have weaker learning abilities and worse academic performance than students in research universities. Furthermore, the sex and grade of students were considered. We conducted a three-stage experiment for the PPT-based group and the AR-based group separately. We taught the students the orthographic projection, a lesson from the Engineering Drawing course, which is widely learned by students who majored in architecture. The students' academic performances were rated prior to class, right after class, and 1-week after class, through a direct examination at three stages. We found the inefficiency of AR for students in vocational colleges. The interaction effect between sex and grade of students was also reported. Students undergoing AR-based teaching could not perform better or even worse than students undergoing PPT-based teaching. We recommended that the teachers should consider whether to use AR in the classroom based on the characteristics of students. [ABSTRACT FROM AUTHOR]

AR assembly instruction is a method that helps users with manual assembly by overlaying virtual information on the real environment. However, users have to manually change the information display form, which fails to adapt to their varying information needs in different stages of the assembly task. This study proposes a user-centered adaptive visualization method for AR manual assembly that can provide the necessary information according to the user's intention in the assembly process. This paper develops a system (UIAVS) through an information hierarchy mechanism and a user intention recognition method based on the user's eye gaze, the spatial location, and current assembly task, which can adaptively adjust the visibility of information, how much information is displayed, and the change of visualization form. UIAVS was tested for the first time in a small engine assembly task. Twenty-four participants were randomly assigned to different task familiarity (novice and expert) and different information visualization response methods for assembly task experiments. The results show that UIAVS has better task performance and cognitive performance as well as user experience than traditional AR assembly instruction method, especially for experts. The research results have certain guiding significance for the design of AR assembly instructions, which extends the application of AR technology in practical complex assembly tasks. [ABSTRACT FROM AUTHOR]

In this paper, we present an exploratory study on the potential impact of holographic heart models and mixed reality technology on medical training, and in particular in teaching complex Congenital Heart Diseases (CHD) to medical students. Fifty-nine medical students were randomly allocated into three groups. Each participant in each group received a 30-minute lecture on a CHD condition interpretation and transcatheter treatment with different instructional tools. The participants of the first group attended a lecture in which traditional slides were projected onto a flat screen (group “regular slideware”, RS). The second group was shown slides incorporating videos of holographic anatomical models (group “holographic videos”, HV). Finally, those in the third group wore immersive, head-mounted devices (HMD) to interact directly with holographic anatomical models (group “mixed reality”, MR). At the end of the lecture, the members of each group were asked to fill in a multiple-choice questionnaire aimed at evaluating their topic proficiency, as a proxy to evaluate the effectiveness of the training session (in terms of acquired notions); participants from group MR were also asked to fill in a questionnaire regarding the recommendability and usability of the MS Hololens HMDs, as a proxy of satisfaction regarding its use experience (UX). The findings show promising results for usability and user acceptance. [ABSTRACT FROM AUTHOR]

Philosophical and technoculture studies surrounding the existential understanding of the human–technology–world experience have seen a slow but steady increase that makes a turn to material hermeneutics in the second decade of the twenty-first century (Ihde in Postphenomenology: essays in the postmodern context. Northwestern University Press, Evanston, 1993; Capurro in AI Soc 25(1):35–42, 2010; Romele in Digital hermeneutics: philosophical investigations in new media and technologies. Routledge, Abingdon, 2020; among others). This renewed focus makes sense because human–technology–world experiences need to be interpreted. And many of these are more complicated to study, precisely because technology is at the root of the experiences. One interesting subset of technologies is media technologies, also called digital media, which intertwines the device and the content to mediate together in the world (Irwin in Digital media: human-technology connection. Lexington Books, Lanham, 2016). Visual media technologies and media content, together, through what is called moving image technologies, create virtual role-playing, virtual and augmented reality, video games, and social media focused worlds that have become central experiences in contemporary culture. Just as image-based scientific instruments read the world in different ways, so to do these visual mediated experiences. How might this comingled "reading" of technology explain the digital film language and experience? I contend that understanding the existential "early" film experience helps understand the new age of cinema, with implications for digital media, digital representation of the visual, and technoscience and technoculture studies. The material hermeneutics perspective called postphenomenology is one way to study these visually focused human–technology–world perceptual and interpretive experiences. Don Ihde's methodological framework (1990, 1993, 1996, 2002, 2010, 2012, 2016, 2019) is both an idea from technoscience studies and a set of nuanced vocabulary that helps to explore and reveal variations, patterns, and trajectories of the whole-body experience of technology. This use case will first explore traditional cinema and then the "new age" term "moving image", to learn more about this complicated and radically transforming technological experience. Work by Don Ihde and Vivian Sobchack is considered. [ABSTRACT FROM AUTHOR]

Digital electronics is a fundamental subject for engineering students, and it enables the students to learn design-based approaches and solve complex engineering problems. Students learn about minimization techniques for reducing the hardware components and size of the circuit by solving complex Boolean equations. The Karnaugh map (K-map) is one such technique utilized in digital electronics to solve complex Boolean equations and design AND-OR-INVERT (AOI) logical diagrams. The K-map technique involves several steps to solve the Boolean expression, and students often find it difficult to follow the K-map process. In this study, an AR-based learning system was developed using Unity 3D and Vuforia SDK that aimed to teach the students about the step-wise operation of the K-map technique. An experimental study was conducted with 128 undergraduate engineering students to determine the impact of the AR learning system on the critical thinking skills, learning motivation, and knowledge gain of students. The students were divided into two groups: experimental group (N = 64) and control group (N = 64). The AR learning system was implemented in flipped learning mode and utilized to provide in-class activities during the learning. The experimental group students utilized the AR learning system for in-class activities whereas control group students performed in-class activities using the traditional approach. The experimental outcomes indicate that the use of AR technology has a significant positive impact on the critical thinking skills, learning motivation, and knowledge gain of students. The study also found that critical thinking skills and learning motivation have a significant positive correlation with the knowledge gain of students in the experimental group. [ABSTRACT FROM AUTHOR]

Augmented and virtual reality (AR, VR) are becoming promising tools in neurosurgery. AR and VR can reduce challenges associated with conventional approaches via the simulation and mimicry of specific environments of choice for surgeons. Awake craniotomy (AC) enables the resection of lesions from eloquent brain areas while monitoring higher cortical and subcortical functions. Evidence suggests that both surgeons and patients benefit from the various applications of AR and VR in AC. This paper investigates the application of AR and VR in AC and assesses its prospective utility in neurosurgery. A systematic review of the literature was performed using PubMed, Scopus, and Web of Science databases in accordance with the PRISMA guidelines. Our search results yielded 220 articles. A total of six articles consisting of 118 patients have been included in this review. VR was used in four papers, and the other two used AR. Tumour was the most common pathology in 108 patients, followed by vascular lesions in eight patients. VR was used for intraoperative mapping of language, vision, and social cognition, while AR was incorporated in preoperative training of white matter dissection and intraoperative visualisation and navigation. Overall, patients and surgeons were satisfied with the applications of AR and VR in their cases. AR and VR can be safely incorporated during AC to supplement, augment, or even replace conventional approaches in neurosurgery. Future investigations are required to assess the feasibility of AR and VR in various phases of AC. [ABSTRACT FROM AUTHOR]

In this survey, we present a systematic review of 3D hand pose estimation from the perspective of efficient annotation and learning. 3D hand pose estimation has been an important research area owing to its potential to enable various applications, such as video understanding, AR/VR, and robotics. However, the performance of models is tied to the quality and quantity of annotated 3D hand poses. Under the status quo, acquiring such annotated 3D hand poses is challenging, e.g., due to the difficulty of 3D annotation and the presence of occlusion. To reveal this problem, we review the pros and cons of existing annotation methods classified as manual, synthetic-model-based, hand-sensor-based, and computational approaches. Additionally, we examine methods for learning 3D hand poses when annotated data are scarce, including self-supervised pretraining, semi-supervised learning, and domain adaptation. Based on the study of efficient annotation and learning, we further discuss limitations and possible future directions in this field. [ABSTRACT FROM AUTHOR]

Augmented Reality (AR) is applied in almost every field, and a few, but not limited, are engineering, medical, gaming and internet of things. The application of image tracking is inclusive in all these mentioned fields. AR uses image tracking to localize and register the position of the user/AR device for superimposing the virtual image into the real-world. In general terms, tracking the image enhance the users' experience. However, in the image tracking application, establishing the interface between virtual realm and the physical world has many shortcomings. Many tracking systems are available, but it lacks in robustness and efficiency. The robustness of the tracking algorithm, is the challenging task of implementation. This study aims to enhance the users' experience in AR by describing an image using Directional Intensified Features with Tertiary Filtering. This way of describing the features improve the robustness, which is desired in the image tracking. A feature descriptor is robust, in the sense that it does not compromise, when the image undergoes various transformations. This article, describes the features based on the Directional Intensification using Tertiary Filtering (DITF). The robustness of the algorithm is improved, because of the inherent design of Tri-ocular, Bi-ocular and Dia-ocular filters that can intensify the features in all required directions. The algorithm's robustness is verified with respect to various image transformations. The oxford dataset is used for performance analysis and validation. DITF model is designed to achieve the repeatability score of illumination-variation , blur changes and view-point variation, as 100%, 100% and 99% respectively. The comparative analysis has been performed in terms of precision and re-call. DITF outperforms the state-of-the-art descriptors, namely, BEBLID, BOOST, HOG, LBP, BRISK and AKAZE. An Implementation of DITF source code is available in the following GitHub repository: github.com/Johnchristopherclement/Directional-Intensified-Feature-Descriptor. [ABSTRACT FROM AUTHOR]

Extracerebral tumors often occur on the surface of the brain or at the skull base. It is important to identify the peritumoral sulci, gyri, and nerve fibers. Preoperative visualization of three-dimensional (3D) multimodal fusion imaging (MFI) is crucial for surgery. However, the traditional 3D-MFI brain models are homochromatic and do not allow easy identification of anatomical functional areas. In this study, 33 patients with extracerebral tumors without peritumoral edema were retrospectively recruited. They underwent 3D T1-weighted MRI, diffusion tensor imaging (DTI), and CT angiography (CTA) sequence scans. 3DSlicer, Freesurfer, and BrainSuite were used to explore 3D-color-MFI and preoperative planning. To determine the effectiveness of 3D-color-MFI as an augmented reality (AR) teaching tool for neurosurgeons and as a patient education and communication tool, questionnaires were administered to 15 neurosurgery residents and all patients, respectively. For neurosurgical residents, 3D-color-MFI provided a better understanding of surgical anatomy and more efficient techniques for removing extracerebral tumors than traditional 3D-MFI (P < 0.001). For patients, the use of 3D-color MFI can significantly improve their understanding of the surgical approach and risks (P < 0.005). 3D-color-MFI is a promising AR tool for extracerebral tumors and is more useful for learning surgical anatomy, developing surgical strategies, and improving communication with patients. [ABSTRACT FROM AUTHOR]

Modern livestock farm technologies allow operators to have access to a multitude of data thanks to the high number of mobile and fixed sensors available on both the livestock farming machinery and the animals. These data can be consulted via PC, tablet, and smartphone, which must be handheld by the operators, leading to an increase in the time needed for on-field activities. In this scenario, the use of augmented reality smart glasses could allow the visualization of data directly in the field, providing for a hands-free environment for the operator to work. Nevertheless, to visualize specific animal information, a connection between the augmented reality smart glasses and electronic animal identification is needed. Therefore, the main objective of this study was to develop and test a wearable framework, called SmartGlove that is able to link RFID animal tags and augmented reality smart glasses via a Bluetooth connection, allowing the visualization of specific animal data directly in the field. Moreover, another objective of the study was to compare different levels of augmented reality technologies (assisted reality vs. mixed reality) to assess the most suitable solution for livestock management scenarios. For this reason, the developed framework and the related augmented reality smart glasses applications were tested in the laboratory and in the field. Furthermore, the stakeholders' point of view was analyzed using two standard questionnaires, the NASA-Task Load Index and the IBM-Post Study System Usability Questionnaire. The outcomes of the laboratory tests underlined promising results regarding the operating performances of the developed framework, showing no significant differences if compared to a commercial RFID reader. During the on-field trial, all the tested systems were capable of performing the task in a short time frame. Furthermore, the operators underlined the advantages of using the SmartGlove system coupled with the augmented reality smart glasses for the direct on-field visualization of animal data. [ABSTRACT FROM AUTHOR]