Search Results (440)

Background: Augmented-reality (AR) navigation is emerging as a means of turning pre-operative cone-beam CT data into intuitive, in situ guidance for difficult tooth removal, yet the scattered evidence has never been consolidated nor illustrated with a full clinical workflow. Aims: This study aims to narratively synthesise AR applications limited to dental extractions and to illustrate a full AR-guided clinical workflow. Methods: We performed a PRISMA-informed narrative search (PubMed + Cochrane, January 2015–June 2025) focused exclusively on AR applications in dental extractions and found nine eligible studies. Results: These pilot reports—covering impacted third molars, supernumerary incisors, canines, and cyst-associated teeth—all used marker-less registration on natural dental surfaces and achieved mean target-registration errors below 1 mm with headset set-up times under three minutes; the only translational series (six molars) recorded a mean surgical duration of 21 ± 6 min and a System Usability Scale score of 79. To translate these findings into practice, we describe a case of AR-guided mandibular third-molar extraction. A QR-referenced 3D-printed splint, intra-oral scan, and CBCT were fused to create a colour-coded hologram rendered on a Magic Leap 2 headset. The procedure took 19 min and required only a conservative osteotomy and accurate odontotomy that ended without neurosensory disturbance (VAS pain 2/10 at one week). Conclusions: Collectively, the literature synthesis and clinical demonstration suggest that current AR platforms deliver sub-millimetre accuracy, minimal workflow overhead, and high user acceptance in high-risk extractions while highlighting the need for larger, controlled trials to prove tangible patient benefit. Full article

This study proposes a Two-points Spatial Alignment System (TSAS) for accurate positioning of Building Information Modeling (BIM) objects in Mixed Reality (MR) environments at construction sites. Conventional spatial alignment methods present limitations: marker-based approaches require precise marker installation and setup in predefined locations, while drag-based methods rely considerably on user manipulation skills. TSAS utilizes Y-axis rotation and vector-based scaling mechanisms to facilitate alignment processes. Through usability evaluation with 30 participants in MR environments, TSAS demonstrated a performance with a 50.3 mm alignment error, compared to marker-based (64.0 mm) and drag methods (199.7 mm). A one-way Analysis of Variance (ANOVA) confirmed that these differences in accuracy were statistically significant (p < 0.001). Notably, TSAS meets the Korean building regulation’s tolerance while maintaining consistent accuracy in indoor environments. Although the marker method showed better efficiency in operation time, this evaluation excluded initial installation time requirements. The usability evaluation suggests this approach could be beneficial for BIM visualization and review processes in construction settings. Future research will focus on validating the system’s performance in diverse construction environments, including larger buildings and complex sites. Full article

Digital twins represent a transformative innovation for battery energy storage systems (BESS), offering real-time virtual replicas of physical batteries that enable accurate monitoring, predictive analytics, and advanced control strategies. These capabilities promise to significantly enhance system efficiency, reliability, and lifespan. Yet, despite the clear technical potential, large-scale deployment of digital twin-enabled battery systems faces critical governance barriers. This study identifies three major challenges: fragmented standards and lack of interoperability, weak or misaligned market incentives, and insufficient cybersecurity safeguards for interconnected systems. The central contribution of this research is the development of a comprehensive governance framework that aligns these three pillars—standards, market and regulatory incentives, and cybersecurity—into an integrated model. Findings indicate that harmonized standards reduce integration costs and build trust across vendors and operators, while supportive regulatory and market mechanisms can explicitly reward the benefits of digital twins, including improved reliability, extended battery life, and enhanced participation in energy markets. For example, simulation-based evidence suggests that digital twin-guided thermal and operational strategies can extend usable battery capacity by up to five percent, providing both technical and economic benefits. At the same time, embedding robust cybersecurity practices ensures that the adoption of digital twins does not introduce vulnerabilities that could threaten grid stability. Beyond identifying governance gaps, this study proposes an actionable implementation roadmap categorized into short-, medium-, and long-term strategies rather than fixed calendar dates, ensuring adaptability across different jurisdictions. Short-term actions include establishing terminology standards and piloting incentive programs. Medium-term measures involve mandating interoperability protocols and embedding digital twin requirements in market rules, and long-term strategies focus on achieving global harmonization and universal plug-and-play interoperability. International examples from Europe, North America, and Asia–Pacific illustrate how coordinated governance can accelerate adoption while safeguarding energy infrastructure. By combining technical analysis with policy and governance insights, this study advances both the scholarly and practical understanding of digital twin deployment in BESSs. The findings provide policymakers, regulators, industry leaders, and system operators with a clear framework to close governance gaps, maximize the value of digital twins, and enable more secure, reliable, and sustainable integration of energy storage into future power systems. Full article

Background: Accurate route planning is a core challenge in logistics, particularly for small- and medium-sized enterprises that lack access to costly geospatial tools. This study explores whether usable distance matrices and routing outputs can be generated solely from geographic coordinates without relying on full map-based infrastructure. Methods: A dataset of over 5000 Hungarian postal locations was used to evaluate five models: Haversine-based scaling with circuity, linear regression, second- and third-degree polynomial regressions, and a trained artificial neural network. Models were tested on the full dataset, and three example routes representing short, medium, and long distances. Both statistical accuracy and route-level performance were assessed, including a practical optimization task. Results: Statistical models maintained internal consistency, but systematically overestimated longer distances. The ANN model provided significantly better accuracy across all scales and produced routes more consistent with map-based paths. A new evaluation method was introduced to directly compare routing outputs. Conclusions: Practical route planning can be achieved without GIS services. ML-based estimators offer a cost-effective alternative, with potential for further improvement using larger datasets, additional input features, and the integration of travel time prediction. This approach bridges the gap between simplified approximations and commercial routing systems. Full article

Background: Inpatient palliative care consultation services operate with an interdisciplinary team, where effective handoffs are crucial for coordinated patient care. We aimed to replace encrypted email handoffs with a more concise and uniform handoff using I-PASS (illness severity, patient summary, action list, situational awareness, contingency planning, and synthesis by receiver) integrated within the electronic medical record (EMR). Aim and Measures: Within six months of launch, our goal was to achieve 90% I-PASS utilization for hospitalized acutely ill patients with cancer receiving palliative care consultation. Intervention: In January 2021, our quality improvement team, consisting of physicians, advanced practice providers, and trainees, began implementing I-PASS using the plan–do–study–act cycle. After providing training sessions for all palliative care clinicians, I-PASS went live on October 1, 2021. I-PASS utilization was tracked via random and monthly audits of EMRs. Through anonymous surveys, both pre- and post-implementation, we gathered clinician feedback and concerns about the handoff system. Survey responses were compared using the Mann–Whitney test. Outcomes: Within six months of implementation, the I-PASS utilization rate reached > 99%. The survey participation rates were 70% (45/64) and 82% (49/60) for the pre-and post-implementation periods, respectively. Respondents provided answers on one to five scale (mean, standard deviation, SD): lower accuracy with email (3.53, SD = 0.98) vs. I-PASS (4.20, SD = 0.83), p < 0.001; handoff lengthier with email (4.17, SD = 1.05) vs. I-PASS (2.1, SD = 1.15), p < 0.001; the time required was longer with email (3.0, SD = 1.22) vs. I-PASS (1.71, SD = 0.73), p < 0.001. Overall, respondents found I-PASS to be significantly better (4.69, SD = 0.58). Conclusion: I-PASS was fully adopted by the team, with nearly 100% utilization and strong clinician endorsement as an effective communication tool. Future efforts should focus on optimizing usability, particularly by educating clinicians on smartphone EMR access and enabling the timely and streamlined editing of I-PASS. Full article

The prioritization of user requirements is neglected in most existing interface designs for driverless vehicle systems, which may incur safety risks, fragmented user experiences, development resource wastage, and weakened market competitiveness. Accordingly, this paper proposes a hybrid interface design method for a virtual reality (VR) driverless vehicle system by combining a A-KANO model and system usability scale (SUS). Firstly, we obtain key words, and a total of 23 demand points are collected through word frequency analysis via combining with user interview and observation method; secondly, 21 demand points are derived from A-KANO model analysis and prioritized for function development; and finally, design practice is carried out according to the ranking results, and virtual reality technology is used to build a VR unmanned vehicle system in order to simulate the interface interaction of a driverless vehicle system. Then, the VR driverless vehicle system is used as a test experimental environment for user evaluation, and combined with the SUS scale to evaluate the user-prioritized experience requirements for practical verification. Empirical results demonstrate that this method effectively categorizes multifaceted user needs, providing actionable solutions to enhance passenger experience and optimize service system design in future autonomous driving scenarios. Full article

Urbanization in China and the proliferation of high-rise office buildings have led to increased demand for daylighting and thermal comfort. These requirements often result in reliance on active systems, including heating, cooling, and artificial lighting, which increase energy consumption. Existing studies have often focused on individual cases or room-scale models, which makes it difficult to generalize findings to the design of various high-rise office building types. Therefore, in this study, parametric prototype building models for high-rise office buildings were developed based on surveys of completed and under-construction projects. These surveys reflected actual design practices and were used to support systematic performance evaluation and typology-level optimization. Building performance was simulated using Grasshopper and Honeybee to generate large-scale datasets, and stacking ensemble learning models were used as surrogate predictors for energy use, daylighting, and thermal comfort. Multi-objective optimization was conducted using the non-dominated sorting genetic algorithm III (NSGA-III), followed by strategy formulation. The results revealed the following: (1) the proposed prototype model establishes clear parameter ranges for geometry, envelope design, and thermal performance, offering reusable models and data; (2) the stacking ensemble model outperforms individual models, improving the coefficient of determination (R²) by 0.5–16.1%, with mean squared error (MSE) reductions of 4.4–70.6%, and mean absolute error (MAE) reductions of 2.8–45.8%; (3) space length, aspect ratio, usable area ratio, window U-value, and solar heat gain coefficient (SHGC) were identified as primary performance drivers; and (4) optimized solutions reduced energy use by 3.79–11.81% and enhanced daylighting comfort by 40.16–50.32% while maintaining thermal comfort. The proposed framework provides localized, data-driven guidance for early-stage performance optimization in high-rise office building design. Full article

This study investigates the effectiveness of designing a gamified Virtual Reality (VR) intervention, grounded in Kolb’s Experiential Learning Theory, in enhancing social reciprocity, affective expression, and daily living skills among Thai children with Autism Spectrum Disorder (ASD). Utilizing the Meta Quest 2 headset, the intervention simulated five real-world contexts—home routines, classroom behavior, street crossing, supermarket shopping, and fast-food interactions. A quasi-experimental pretest-posttest control group design was employed with 33 children aged 6–12, complemented by thematic analysis of caregiver and therapist interviews. Results from the Social Responsiveness Scale, Second Edition (SRS-2), indicated significant improvements in social communication (p = 0.001) and social motivation (p = 0.045), while changes in social awareness (p = 0.233) and repetitive behaviors (p = 0.169) were not statistically significant. However, an ANCOVA analysis controlling for pre-test scores found that the difference in post-test outcomes between the intervention and control groups did not reach statistical significance (p = 0.073), suggesting that observed improvements may be influenced by baseline variability. Qualitative feedback highlighted the program’s engagement value, cultural relevance, and usability, alongside suggestions for increased adaptivity and contextual nuance. These results underscore the potential of VR-based learning while highlighting the need for further research with larger samples and more adaptive systems. These findings offer practical insights for educators, researchers, teachers, and program developers by demonstrating how culturally grounded, gamified VR interventions when guided by experiential learning principles can effectively enhance engagement and support targeted social skill development in children with ASD. Full article

(1) Background: Upper limb (UL) function plays a central role in daily life, enabling essential tasks such as reaching, grasping, and eating. While numerous tools exist to evaluate UL kinematics, their application in pediatric populations is often limited by a lack of age-specific validation. This study presents a novel motion analysis protocol featuring a customized marker set, aimed at assessing UL movements in the three anatomical planes across different age groups, with a focus on pediatric applicability. (2) Materials and Methods: A SmartDX motion capture system was used, with 30 markers positioned on the upper body, referencing the trunk as the root of the kinematic chain. Ten healthy participants (mean age: 18.69 ± 12.45 years; range: 8.0–41.4) without UL impairments were recruited. The broad age range was intentionally selected to assess the protocol’s transversal applicability. (3) Results: Results showed excellent intra-operator reliability for shoulder and wrist kinematics (ICC > 0.906) and good reliability for elbow movements (ICC > 0.755). Inter-operator reliability was good to excellent (shoulder ICC > 0.958; elbow ICC > 0.762; wrist ICC > 0.826) Usability, measured via the System Usability Scale, was rated as good (83.25). (4) Conclusions: The proposed protocol demonstrated strong reliability and practical usability, supporting its adoption in clinical and research settings. Its design allows for adaptability across motion capture platforms, promoting wider implementation in pediatric UL functional assessment. Full article

Wilms’ tumor is a common pediatric renal malignancy. In selected cases, nephron-sparing surgery (NSS) may be employed as part of the surgical approach. To prevent positive margins, optimal understanding of the tumor–kidney edge is essential. Augmented reality (AR) enables intraoperative visualization of patient-specific three-dimensional (3D) holograms. In this study, we aim to validate the clinical feasibility of a holographic landmark-based registration system in pediatric patients planned for a total nephrectomy (TN), to ensure that the holographic visualization will not influence surgical decision making. In a single-center prospective study, ten pediatric patients undergoing TN were included. Patient-specific 3D holograms were created from preoperative MRI, and intraoperatively landmark-based registration was performed using the HoloLens 2. Clinical feasibility was conducted using accuracy measurements, the System Usability Scale (SUS), and a self-developed questionnaire. Three out of ten patients had a successful registration with a median measured accuracy of 7.0 mm (Interquartile Range (IQR) 6–13.5) and a median SUS score of 75 (IQR 65–77.5). Surgeons reported improved depth perception and anatomical understanding. However, in seven out of ten patients, registration failed due to multiple reasons. The most important factors were large tumor volumes obstructing landmark placement and insufficient spatial distributions of the landmarks, causing rotational misalignment. Although AR showed potential in improving the depth perception and relation in anatomical structures, the landmark-based registration with the HoloLens 2 was currently deemed insufficient for clinical implementation in pediatric abdominal surgery. Full article

Background: Mobility plays a fundamental role in causal reasoning (causal inference or cause–effect learning), which is essential for brain development at early ages. Children naturally develop causal reasoning through interaction with their environment. Therefore, children with severe motor disabilities (GMFCS levels IV–V), who face limited opportunities for interaction, often show delays in causal reasoning. Objective: This study investigates how a wheelchair-mounted, semi-autonomous mobility platform operated via a simple switch may enhance causal learning in children with severe disabilities, compared with traditional therapies. However, due to the scarcity of participants who meet the inclusion criteria and the need for long-term evaluation, recruitment poses a significant challenge. This study aims to provide an initial assessment of the platform and collect preliminary data to estimate the required sample size and number of sessions for future studies. Methods: We conducted a pilot randomized controlled trial (RCT) to assess platform usability and its effect on reaction time and keystroke accuracy. Four children, aged 8.5 ± 2.38, participated in seven 30 min sessions. They were randomly assigned in equal numbers, with two participants in the intervention group (using the platform) and two in the control group (receiving standard therapy). Usability was evaluated through a questionnaire completed by two therapists. Key outcome measures included the System Usability Scale (SUS), reaction time (RT), and keystroke accuracy (NIS). Results: Despite the small sample size and recruitment challenges, the data allowed for preliminary estimates of the sample size and number of sessions required for future studies. Therapists reported positive usability scores. Children using the platform showed promising trends in RT and NIS, suggesting improved engagement with cause–effect tasks. Conclusions: The findings support the feasibility and usability of the mobility platform by therapists, although some improvements should be implemented in the future. No conclusive evidence was found regarding the platform’s effectiveness on causal learning, despite a positive trend over time. This pilot study also provides valuable insights for designing larger, statistically powered trials, particularly focused on NIS. Full article

Supporting dementia carers is a global priority. As a Randomised Controlled Trial (RCT) (n = 352) of the Word Health Organization recommended, an internationally disseminated ‘iSupport’ e-health intervention was conducted, revealing no measurable benefits to the wellbeing of adult dementia carers. This process evaluation contributes original insights of the trial outcomes. Its aims were to ascertain the usability and acceptability of iSupport, participant engagement and adherence to iSupport, and contextual factors influencing its implementation and potential impact. The process evaluation followed a mixed-method design. The following data were collected from all participants randomised to iSupport (n = 175): (1) post-intervention evaluation questionnaire (n = 93) containing the 10-item System Usability Scale and bespoke items exploring acceptability, engagement, and perceived impact; (2) qualitative interviews (n = 52) with a sub-sample of participants who were purposively sampled according to age, scores on the outcome measures, and gender, as these interviews aimed to generate contextual detail and explanatory accounts; and (3) ‘Access’ data from the iSupport platform (n = 175). Descriptive statistics was used to report on the frequency of survey responses whilst a thematic analysis approach was followed to identify themes from the qualitative interview data. Data sets were analysed independently and then used with respect to one another in order to generate explanatory pathways related to the usability, acceptability, and the impact of iSupport. Despite good trial retention, 8.3% of participants (n = 32) did not spend any time on iSupport, and 54% (n = 94) spent between 30 min and 1.5 h. Factors driving this were the following: time constrains, method of delivery, and content characteristics. Positive impacts of iSupport were also described. Participants, including those with extensive caring experience, reported how iSupport had made them feel reassured, valued, and more able to ask for help. They also reported having an improved outlook on their caring role and on the needs and feelings of the person living with dementia. Research and practice should focus on exploring blended delivery, including self-directed and interactive components, such as regular contact with a health professional. These insights are critical for supporting the global implementation and adaptation of iSupport and offer valuable directions for future research. Full article

Neurodevelopmental disorders are one of the most prevalent conditions today, and among the limitations in activity and restrictions in the participation of children and their families, we find intervention in activities of daily living; therefore, research focused on outcome measurement is one of the most active lines, and after COVID-19, telerehabilitation has garnered special interest. Background/Objectives: The study objective was to evaluate the effectiveness of a mobile health (mHealth) application in improving the performance of activities of daily living in children with neurodevelopmental disorders. Methods: The study employed a quasi-experimental design with a control group, using a fully remote mHealth-based intervention. The instruments used were a sociodemographic ad hoc, Pediatric Evaluation of Disability Inventory Computer, Family Outcomes Survey, Family Confidence Scale, and System Usability Scale. The final sample consisted of 13 participants. Results: The mHealth intervention showed significant improvements in occupational performance in the experimental group, especially in the global score and in the Responsibility dimension of the PEDI-CAT. No relevant differences were observed in the CON-FAN and FOS scales between groups, although the latter showed improvements over time. The usability of the app was rated positively (SUS = 69.75). Conclusions: The developed application presents good usability for families of children with neurodevelopmental disorders, but to obtain better outcome measures, the intervention should combine face-to-face sessions and the use of mHealth, as well as employing the family-centered model. Full article

Effective water quality monitoring is very important for detecting pollution and protecting public health. However, traditional methods are slow, relying on costly equipment, central laboratories, and expert staffing, which delays real-time measurements. At the same time, significant advancements have been made in the field of plasmonic sensing technologies, making them ideal for environmental monitoring. However, their reliance on large, expensive spectrometers limits accessibility. This work aims to bridge the gap between advanced plasmonic sensing and practical water monitoring needs, by integrating plasmonic sensors with mobile technology. We present BioColor, a mobile platform that consists of a plasmonic sensor setup, mobile application, and cloud services. The platform processes captured colorimetric sensor images in real-time using optimized image processing algorithms, including region-of-interest segmentation, color extraction (mean and dominant), and comparison via the CIEDE2000 metric. The results are visualized within the mobile app, providing instant and automated access to the sensing outcome. In our validation experiments, the system consistently measured color differences in various sensor images captured under media with different refractive indices. A user experience test with 12 participants demonstrated excellent usability, resulting in a System Usability Scale (SUS) score of 93. The BioColor platform brings advanced sensing capabilities from hardware into software, making environmental monitoring more accessible, efficient, and continuous. Full article

Amblyopia, commonly affecting children aged 0–6 years, results from disrupted visual processing during early development and often leads to reduced visual acuity in one eye. This study presents the development and preliminary usability assessment of a non-invasive ocular monitoring device designed to support oculomotor engagement and therapy adherence in amblyopia management. The system incorporates an interactive maze-navigation task controlled via gaze direction, implemented during monocular and binocular sessions. The device tracks lateral and anteroposterior eye movements and generates visual reports, including displacement metrics and elliptical movement graphs. Usability testing was conducted with a non-probabilistic adult sample (n = 15), including individuals with and without amblyopia. The System Usability Scale (SUS) yielded an average score of 75, indicating good usability. Preliminary tests with two adults diagnosed with amblyopia suggested increased eye displacement during monocular sessions, potentially reflecting enhanced engagement rather than direct therapeutic improvement. This feasibility study demonstrates the device’s potential as a supportive, gaze-controlled platform for visual engagement monitoring in amblyopia rehabilitation. Future clinical studies involving pediatric populations and integration of visual stimuli modulation are recommended to evaluate therapeutic efficacy and adaptability for early intervention. Full article