While metaverse is widely discussed, comprehension of its intricacies remains limited to a select few. Conceptually akin to a three-dimensional embodiment of the Internet, the metaverse facilitates simultaneous existence in both physical and virtual domains. Fundamentally, it embodies a visually immersive virtual environment, striving for authenticity, where individuals engage in real-world activities such as commerce, gaming, social interaction, and leisure pursuits. The global pandemic has accelerated digital innovations across diverse sectors. Beyond strides in telehealth, payment systems, remote monitoring, and secure data exchange, substantial advancements have been achieved in artificial intelligence (AI), virtual reality (VR), augmented reality (AR), and blockchain technologies. Nevertheless, the metaverse, in its nascent stage, continues to evolve, harboring significant potential for revolutionizing healthcare. Through integration with the Internet of Medical Devices, quantum computing, and robotics, the metaverse stands poised to redefine healthcare systems, offering enhancements in surgical precision and therapeutic modalities, thus promising profound transformations within the industry.

With software developments and advances in display technologies substantially improved, augmented reality (AR) application has gained popularity. In this study, we discuss using classic PowerPoint and AR for two kinds of scaffolding tasks (task-lifeline assembly and hedge assembly) for users with different spatial ability. We considered both objective and subjective measures of performance, i.e., correct rate and system usability and the ITC-sense of presence inventory (ITC-SOPI) scale. The results of the study show that participants using AR achieved higher operating performance than those using PowerPoint. Furthermore, the users\' learning effect was influenced by spatial ability when using PowerPoint. Participants with high spatial ability achieved higher performance than participants with low spatial ability in PowerPoint. However, participants who used AR as a training method did not show significantly different operating performance at different levels of spatial ability. Consequently, AR was believed to be a potential method for enhancing training performance.

BACKGROUND: This study introduced an Augmented Reality (AR) navigation system to address limitations in conventional high tibial osteotomy (HTO). The objective was to enhance precision and efficiency in HTO procedures, overcoming challenges such as inconsistent postoperative alignment and potential neurovascular damage.
METHODS: The AR-MR (Mixed Reality) navigation system, comprising HoloLens, Unity Engine, and Vuforia software, was employed for pre-clinical trials using tibial sawbone models. CT images generated 3D anatomical models, projected via HoloLens, allowing surgeons to interact through intuitive hand gestures. The critical procedure of target tracking, essential for aligning virtual and real objects, was facilitated by Vuforia\'s feature detection algorithm.
RESULTS: In trials, the AR-MR system demonstrated significant reductions in both preoperative planning and intraoperative times compared to conventional navigation and metal 3D-printed surgical guides. The AR system, while exhibiting lower accuracy, exhibited efficiency, making it a promising option for HTO procedures. The preoperative planning time for the AR system was notably shorter (4 min) compared to conventional navigation (30.5 min) and metal guides (75.5 min). Intraoperative time for AR lasted 8.5 min, considerably faster than that of conventional navigation (31.5 min) and metal guides (10.5 min).
CONCLUSIONS: The AR navigation system presents a transformative approach to HTO, offering a trade-off between accuracy and efficiency. Ongoing improvements, such as the incorporation of two-stage registration and pointing devices, could further enhance precision. While the system may be less accurate, its efficiency renders it a potential breakthrough in orthopedic surgery, particularly for reducing unnecessary harm and streamlining surgical procedures.

Real-world understanding serves as a medium that bridges the information world and the physical world, enabling the realization of virtual-real mapping and interaction. However, scene understanding based solely on 2D images faces problems such as a lack of geometric information and limited robustness against occlusion. The depth sensor brings new opportunities, but there are still challenges in fusing depth with geometric and semantic priors. To address these concerns, our method considers the repeatability of video stream data and the sparsity of newly generated data. We introduce a sparsely correlated network architecture (SCN) designed explicitly for online RGBD instance segmentation. Additionally, we leverage the power of object-level RGB-D SLAM systems, thereby transcending the limitations of conventional approaches that solely emphasize geometry or semantics. We establish correlation over time and leverage this correlation to develop rules and generate sparse data. We thoroughly evaluate the system\'s performance on the NYU Depth V2 and ScanNet V2 datasets, demonstrating that incorporating frame-to-frame correlation leads to significantly improved accuracy and consistency in instance segmentation compared to existing state-of-the-art alternatives. Moreover, using sparse data reduces data complexity while ensuring the real-time requirement of 18 fps. Furthermore, by utilizing prior knowledge of object layout understanding, we showcase a promising application of augmented reality, showcasing its potential and practicality.

Periacetabular osteotomy (PAO) is an effective approach for the surgical treatment of developmental dysplasia of the hip (DDH). However, due to the complex anatomical structure around the hip joint and the limited field of view (FoV) during the surgery, it is challenging for surgeons to perform a PAO surgery. To solve this challenge, we propose a robot-assisted, augmented reality (AR)-guided surgical navigation system for PAO. The system mainly consists of a robot arm, an optical tracker, and a Microsoft HoloLens 2 headset, which is a state-of-the-art (SOTA) optical see-through (OST) head-mounted display (HMD). For AR guidance, we propose an optical marker-based AR registration method to estimate a transformation from the optical tracker coordinate system (COS) to the virtual space COS such that the virtual models can be superimposed on the corresponding physical counterparts. Furthermore, to guide the osteotomy, the developed system automatically aligns a bone saw with osteotomy planes planned in preoperative images. Then, it provides surgeons with not only virtual constraints to restrict movement of the bone saw but also AR guidance for visual feedback without sight diversion, leading to higher surgical accuracy and improved surgical safety. Comprehensive experiments were conducted to evaluate both the AR registration accuracy and osteotomy accuracy of the developed navigation system. The proposed AR registration method achieved an average mean absolute distance error (mADE) of 1.96 ± 0.43 mm. The robotic system achieved an average center translation error of 0.96 ± 0.23 mm, an average maximum distance of 1.31 ± 0.20 mm, and an average angular deviation of 3.77 ± 0.85°. Experimental results demonstrated both the AR registration accuracy and the osteotomy accuracy of the developed system.

BACKGROUND: Virtual reality (VR) and augmented reality (AR) are emerging technologies that can be used for cardiopulmonary resuscitation (CPR) training. Compared to traditional face-to-face training, VR/AR-based training has the potential to reach a wider audience, but there is debate regarding its effectiveness in improving CPR quality. Therefore, we conducted a meta-analysis to assess the effectiveness of VR/AR training compared with face-to-face training.
METHODS: We searched PubMed, Embase, Cochrane Library, Web of Science, CINAHL, China National Knowledge Infrastructure, and Wanfang databases from the inception of these databases up until December 1, 2023, for randomized controlled trials (RCTs) comparing VR- and AR-based CPR training to traditional face-to-face training. Cochrane\'s tool for assessing bias in RCTs was used to assess the methodological quality of the included studies. We pooled the data using a random-effects model with Review Manager 5.4, and assessed publication bias with Stata 11.0.
RESULTS: Nine RCTs (involving 855 participants) were included, of which three were of low risk of bias. Meta-analyses showed no significant differences between VR/AR-based CPR training and face-to-face CPR training in terms of chest compression depth (mean difference [MD], -0.66 mm; 95% confidence interval [CI], -6.34 to 5.02 mm; P = 0.82), chest compression rate (MD, 3.60 compressions per minute; 95% CI, -1.21 to 8.41 compressions per minute; P = 0.14), overall CPR performance score (standardized mean difference, -0.05; 95% CI, -0.93 to 0.83; P = 0.91), as well as the proportion of participants meeting CPR depth criteria (risk ratio [RR], 0.79; 95% CI, 0.53 to 1.18; P = 0.26) and rate criteria (RR, 0.99; 95% CI, 0.72 to 1.35; P = 0.93). The Egger regression test showed no evidence of publication bias.
CONCLUSIONS: Our study showed evidence that VR/AR-based training was as effective as traditional face-to-face CPR training. Nevertheless, there was substantial heterogeneity among the included studies, which reduced confidence in the findings. Future studies need to establish standardized VR/AR-based CPR training protocols, evaluate the cost-effectiveness of this approach, and assess its impact on actual CPR performance in real-life scenarios and patient outcomes.
BACKGROUND: CRD42023482286.

OBJECTIVE: Patients with total knee arthroplasty (TKA) often suffer from severe postoperative pain, which seriously hinders postoperative rehabilitation. Extended reality (XR), including virtual reality, augmented reality, and mixed reality, has been increasingly used to relieve pain after TKA. The purpose of this study was to evaluate the effectiveness of XR on relieving pain after TKA.
METHODS: The electronic databases including PubMed, Embase, Web of Science, Cochrane Central Register of Controlled Trials (CENTRAL), and clinicaltrials.gov were searched for studies from inception to July 20, 2023. The outcomes were pain score, anxiety score, and physiological parameters related to pain. Meta-analysis was performed using the Review Manager 5.4 software.
RESULTS: Overall, 11 randomized control trials (RCTs) with 887 patients were included. The pooled results showed XR had lower pain scores (SMD = - 0.31, 95% CI [- 0.46 to - 0.16], P < 0.0001) and anxiety scores (MD = - 3.95, 95% CI [- 7.76 to - 0.13], P = 0.04) than conventional methods. The subgroup analysis revealed XR had lower pain scores within 2 weeks postoperatively (SMD = - 0.49, 95% CI [- 0.76 to - 0.22], P = 0.0004) and XR had lower pain scores when applying XR combined with conventional methods (SMD = - 0.43, 95% CI [- 0.65 to - 0.20], P = 0.0002).
CONCLUSIONS: This systematic review and meta-analysis found applying XR could significantly reduce postoperative pain and anxiety after TKA. When XR was combined with conventional methods, postoperative pain can be effectively relieved, especially within 2 weeks after the operation. XR is an effective non-pharmacological analgesia scheme.

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The technology of robot-assisted prostate seed implantation has developed rapidly. However, during the process, there are some problems to be solved, such as non-intuitive visualization effects and complicated robot control. To improve the intelligence and visualization of the operation process, a voice control technology of prostate seed implantation robot in augmented reality environment was proposed. Initially, the MRI image of the prostate was denoised and segmented. The three-dimensional model of prostate and its surrounding tissues was reconstructed by surface rendering technology. Combined with holographic application program, the augmented reality system of prostate seed implantation was built. An improved singular value decomposition three-dimensional registration algorithm based on iterative closest point was proposed, and the results of three-dimensional registration experiments verified that the algorithm could effectively improve the three-dimensional registration accuracy. A fusion algorithm based on spectral subtraction and BP neural network was proposed. The experimental results showed that the average delay of the fusion algorithm was 1.314 s, and the overall response time of the integrated system was 1.5 s. The fusion algorithm could effectively improve the reliability of the voice control system, and the integrated system could meet the responsiveness requirements of prostate seed implantation.

OBJECTIVE: To evaluate the outcome of Augmented reality technology in the recognizing of oral and maxillofacial anatomy.
METHODS: This study was conducted on the undergraduate students in Peking University School of Stomatology who were learning oral and maxillofacial anatomy. The image data were selected according to the experiment content, and the important blood vessels and bone tissue structures, such as upper and lower jaws, neck arteries and veins were reconstructed in 3D(3-dimensional) by digital software to generate experiment models, and the reconstructed models were encrypted and stored in the cloud. The QR (quick response) code corresponding to the 3D model was scanned by a networked mobile device to obtain augmented reality images to assist experimenters in teaching and subjects in recognizing. Augmented reality technology was applied in both the theoretical explanation and cadaveric dissection respectively. Subjects\' feedback was collected in the form of a post-class questionnaire to evaluate the effectiveness of augmented reality technology-assisted recognizing.
RESULTS: In the study, 83 undergraduate students were included as subjects in this study. Augmented reality technology could be successfully applied in the recognizing of oral and maxillofacial anatomy. All the subjects could scan the QR code through a connected mobile device to get the 3D anatomy model from the cloud, and zoom in/out/rotate the model on the mobile. Augmented reality technology could provide personalized 3D model, based on learners\' needs and abilities. The results of likert scale showed that augmented reality technology was highly recognized by the students (9.19 points), and got high scores in terms of forming a three-dimensional sense and stimulating the enthusiasm for learning (9.01 and 8.85 points respectively).
CONCLUSIONS: Augmented reality technology can realize the three-dimensional visualization of important structures of oral and maxillofacial anatomy and stimulate students\' enthusiasm for learning. Besides, it can assist students in building three-dimensional space imagination of the anatomy of oral and maxillofacial area. The application of augmented reality technology achieves favorable effect in the recognizing of oral and maxillofacial anatomy.