Augmented System Research Articles

Non-neuronal cholinergic system in the heart influences its homeostasis and an extra-cardiac site, the blood-brain barrier.

The non-neuronal cholinergic system of the cardiovascular system has recently gained attention because of its origin. The final product of this system is acetylcholine (ACh) not derived from the parasympathetic nervous system but from cardiomyocytes, endothelial cells, and immune cells. Accordingly, it is defined as an ACh synthesis system by non-neuronal cells. This system plays a dispensable role in the heart and cardiomyocytes, which is confirmed by pharmacological and genetic studies using murine models, such as models with the deletion of vesicular ACh transporter gene and modulation of the choline acetyltransferase (ChAT) gene. In these models, this system sustained the physiological function of the heart, prevented the development of cardiac hypertrophy, and negatively regulated the cardiac metabolism and reactive oxygen species production, resulting in sustained cardiac homeostasis. Further, it regulated extra-cardiac organs, as revealed by heart-specific ChAT transgenic (hChAT tg) mice. They showed enhanced functions of the blood-brain barrier (BBB), indicating that the augmented system influences the BBB through the vagus nerve. Therefore, the non-neuronal cardiac cholinergic system indirectly influences brain function. This mini-review summarizes the critical cardiac phenotypes of hChAT tg mice and focuses on the effect of the system on BBB functions. We discuss the possibility that a cholinergic signal or vagus nerve influences the expression of BBB component proteins to consolidate the barrier, leading to the downregulation of inflammatory responses in the brain, and the modulation of cardiac dysfunction-related effects on the brain. This also discusses the possible interventions using the non-neuronal cardiac cholinergic system.

Multi-objective seismic optimization and evaluation of core-damper-frame tall buildings considering SSI effect

To control the seismic response of the core-frame (CF) structure and attenuate the stress level of the core tube, a novel core-damper-frame (CDF) system is proposed by decoupling the perimeter frame and the central core with flexible damper connectors. In this way, the large inertia force of the perimeter frame cannot be fully transmitted to the core, and the stress of the core is mitigated. In the meantime, the damper connectors would absorb a considerable amount of seismic energy, protecting the perimeter frame as the relative displacement between the two subsystems (perimeter frame and core tube) occurs. By incorporating the soil-structure-interaction (SSI) and the filtered Gaussian white-noise excitation model, the "excitation-soil-core-damper-frame" augmented system is established. Combing the augmented system and the genetic algorithm, a stochastic optimization procedure of the CDF considering the SSI effect is proposed. The optimization aims to minimize a series of performance objectives including displacement, acceleration, shear force, and overturning moment of the CDF system. The conflicting relationships between the multiple objectives are discussed; the influence of the SSI effect and the excitation parameters are evaluated. From an illustrative 40-story CDF structural example, the system shows great superiority in controlling the higher mode vibrations, and could significantly reduce the peak core acceleration (by 54.44 %), frame acceleration (by 56.48 %), core drift (by 28.83 %), frame drift (by 39.28 %), core shear (by 83.67 %), and frame moment (by 22.41 %), as compared to its conventional CF counterpart. In special, over 50 % of the input seismic energy is dissipated by the damper connectors in the CDF system.

Immunomodulation of Cancer Cells Using Autologous Blood Concentrates as a Patient-Specific Cell Culture System: A Comparative Study on Osteosarcoma and Fibrosarcoma Cell Lines.

The understanding that tumor cells might evade immunity through various mutations and the potential of an augmented immune system to eliminate abnormal cells led to the idea of utilizing platelet-rich fibrin (PRF), a blood concentrate containing the body's immune elements as an adjunctive therapy for localized tumors. This study is the first that evaluated the effect of PRF generated with different relative centrifugal forces (RCFs) on osteoblastic and fibroblastic tumor cell lines MG63 and HT1080 with regard to cell viability, cytokine and growth factor release, and the gene expression of factors related to the cell cycle and apoptosis. Our findings could demonstrate decreased cell proliferation of MG63 and HT1080 when treated indirectly with PRF compared to cell cultures without PRF. This effect was more distinct when the cells were treated with low-RCF PRF, where higher concentrations of growth factors and cytokines with reduced RCFs can be found. Similar patterns were observed when assessing the regulation of gene expression related to the cell cycle and apoptosis in both MG63 and HT1080 cells treated with PRF. Despite variations, there was a consistent trend of an up-regulation of tumor-suppressive genes and a down-regulation of anti-apoptotic genes in both cell types following treatment with high- and, particularly, low-RCF PRF formulations.

Application of augmented reality in physical rehabilitation

Augmented reality (AR) has become a popular multidisciplinary research field in recent decades. Augmented reality adds to the subject's real-world sensory information through computer-generated sound, text, and graphics that are projected into the user's natural visual and auditory fields to provide a real-time interactive experience in a common environment. A bibliographic review was carried out with the objective of updating the current state of the use of augmented reality in physical rehabilitation. Augmented reality systems consist of a user interface that offers a motivational component to patients to perform exercises, distracting them from the potential pain they may feel during exercises. Additionally, they can be implemented in the patient's home and eliminate frequent visits to rehabilitation clinics. Among the most used systems are ARS, RehaBio, NeuroR, AR Fruit Ninja, MirrARbilitation, SleeveAR, ARIS and BRU. Its uses have been focused mainly on post-surgical orthopedic and neurological rehabilitation in patients with strokes. Augmented reality offers significant benefits over in-person rehabilitation and other technologies such as virtual reality, which can speed up the recovery process and improve patients' quality of life

Current understanding of nociplastic pain.

Nociplastic pain by the "International Association for the Study of Pain" is defined as pain that arises from altered nociception despite no clear evidence of nociceptive or neuropathic pain. Augmented central nervous system pain and sensory processing with altered pain modulation are suggested to be the mechanism of nociplastic pain. Clinical criteria for possible nociplastic pain affecting somatic structures include chronic regional pain and evoked pain hypersensitivity including allodynia with after-sensation. In addition to possible nociplastic pain, clinical criteria for probable nociplastic pain are pain hypersensitivity in the region of pain to non-noxious stimuli and presence of comorbidity such as generalized symptoms with sleep disturbance, fatigue, or cognitive problems with hypersensitivity of special senses. Criteria for definitive nociplastic pain is not determined yet. Eight specific disorders related to central sensitization are suggested to be restless leg syndrome, chronic fatigue syndrome, fibromyalgia, temporomandibular disorder, migraine or tension headache, irritable bowel syndrome, multiple chemical sensitivities, and whiplash injury; non-specific emotional disorders related to central sensitization include anxiety or panic attack and depression. These central sensitization pain syndromes are overlapped to previous functional pain syndromes which are unlike organic pain syndromes and have emotional components. Therefore, nociplastic pain can be understood as chronic altered nociception related to central sensitization including both sensory components with nociceptive and/or neuropathic pain and emotional components. Nociplastic pain may be developed to explain unexplained chronic pain beyond tissue damage or pathology regardless of its origin from nociceptive, neuropathic, emotional, or mixed pain components.

A Web-Based Augmented Reality System

Web-based augmented reality (AR) systems have many use cases and opportunities in Product Visualisation, Education and Training, Advertising and Marketing, Navigation and Wayfinding, Virtual Try-On, Interactive Storey Telling, Museums and Cultural Heritage, Training and Simulation, Gamification and more. As such, this research paper, A Web-Based Augmented Reality System, will explore these technologies and their use cases in the form of a literature review and several examples utilising the likes of Vectary, Blippar, Model Viewer and World Cast AR. The purpose of which, is to demonstrate a level of understanding of these virtual technologies, to develop them and to develop their future with practical use cases.

A Randomized Controlled Trial Comparing Face-to-Face Versus Remote Delivery of Low-Tech Augmentative and Alternative Communication in Nonspeaking Children With Autism Spectrum Disorder.

Thirty percent of children diagnosed with autism spectrum disorder (ASD) do not develop spoken language. To provide a means of communication for this subset of the population, augmentative and alternative communication (AAC) systems are often utilized. Low-tech options have traditionally been delivered through the in-person modality. However, due to the COVID-19 pandemic, changes to service delivery models have been required. This randomized controlled trial was conducted in order to assess the efficacy of low-tech AAC delivered face-to-face versus remotely on communication outcomes in nonspeaking children with ASD. Both participant groups demonstrated similar gains in AAC proficiency, number and type of nonspeaking acts, and number of spoken communication acts. Remote delivery of low-tech AAC treatment is a viable alternative to face-to-face instruction.

Single-center experience with Knee+™ augmented reality navigation system in primary total knee arthroplasty.

Computer-assisted systems obtained an increased interest in orthopaedic surgery over the last years, as they enhance precision compared to conventional hardware. The expansion of computer assistance is evolving with the employment of augmented reality. Yet, the accuracy of augmented reality navigation systems has not been determined. To examine the accuracy of component alignment and restoration of the affected limb's mechanical axis in primary total knee arthroplasty (TKA), utilizing an augmented reality navigation system and to assess whether such systems are conspicuously fruitful for an accomplished knee surgeon. From May 2021 to December 2021, 30 patients, 25 women and five men, underwent a primary unilateral TKA. Revision cases were excluded. A preoperative radiographic procedure was performed to evaluate the limb's axial alignment. All patients were operated on by the same team, without a tourniquet, utilizing three distinct prostheses with the assistance of the Knee+™ augmented reality navigation system in every operation. Postoperatively, the same radiographic exam protocol was executed to evaluate the implants' position, orientation and coronal plane alignment. We recorded measurements in 3 stages regarding femoral varus and flexion, tibial varus and posterior slope. Firstly, the expected values from the Augmented Reality system were documented. Then we calculated the same values after each cut and finally, the same measurements were recorded radiologically after the operations. Concerning statistical analysis, Lin's concordance correlation coefficient was estimated, while Wilcoxon Signed Rank Test was performed when needed. A statistically significant difference was observed regarding mean expected values and radiographic measurements for femoral flexion measurements only (Z score = 2.67, P value = 0.01). Nonetheless, this difference was statistically significantly lower than 1 degree (Z score = -4.21, P value < 0.01). In terms of discrepancies in the calculations of expected values and controlled measurements, a statistically significant difference between tibial varus values was detected (Z score = -2.33, P value = 0.02), which was also statistically significantly lower than 1 degree (Z score = -4.99, P value < 0.01). The results indicate satisfactory postoperative coronal alignment without outliers across all three different implants utilized. Augmented reality navigation systems can bolster orthopaedic surgeons' accuracy in achieving precise axial alignment. However, further research is required to further evaluate their efficacy and potential.

Development of an augmented reality system for tracheal intubation guidance of airway management.

Tracheal intubation is a crucial procedure performed in airway management to sustain life during various procedures. However, difficult airways can make intubation challenging, which is associated with increased mortality and morbidity. This is particularly important for children who undergo intubation where the situation is difficult. Improved airway management will decrease incidences of repeated attempts, decrease hypoxic injuries in patients, and decrease hospital stays, resulting in better clinical outcomes and reduced costs. Currently, 3D printed models based on CT scans and ultrasound-guided intubation are being used or tested for device fitting and procedure guidance to increase the success rate of intubation, but both have limitations. Maintaining a 3D printing facility can be logistically inconvenient, and it can be time consuming and expensive. Ultrasound-guided intubation can be hindered by operator dependence, limited two-dimensional visualization, and potential artifacts. In this study, we developed an augmented reality (AR) system that allows the overlay of intubation tools and internal airways, providing real-time guidance during the procedure. A child manikin was used to develop and test the AR system. Three-dimensional CT images were acquired from the manikin. Different tissues were segmented to generate the 3D models that were imported into Unity to build the holograms. Phantom experiments demonstrated the AR-guided system for potential applications in tracheal intubation guidance.

Augmented reality system based on the integration of polarization-independent metalens and micro-LEDs.

Augmented reality (AR), a technology that superimposes virtual information onto a user's direct view of real-world scenes, is considered one of the next-generation display technologies and has been attracting considerable attention. Here, we propose a flat optic AR system that synergistically integrates a polarization-independent metalens with micro light-emitting diodes (LEDs). A key component is a meticulously designed metalens with a numerical aperture of 0.25, providing a simulated focusing efficiency of approximately 76.5% at a wavelength of 532 nm. Furthermore, the laser measurement system substantiates that the fabricated metalens achieves a focusing efficiency of 70.8%. By exploiting the reversibility of light characteristics, the metalens transforms the divergent light from green micro-LEDs into a collimated beam that passes through the pupil and images on the retina. Monochromatic pixels with a size of 5×5 µm2 and a pitch of 10 µm can be distinctly resolved with a power efficiency of 50%. This work illustrates the feasibility of integrating the metalens with microdisplays, realizing a high-efficiency AR device without the need for additional optical components and showcasing great potential for the development of near-eye display applications.

Inception‐YOLO: Computational cost and accuracy improvement of the YOLOv5 model based on employing modified CSP, SPPF, and inception modules

AbstractThe demand for less complex and more accurate architectures has always been a priority since the broad usage of computer vision in everyday life, like auto‐drive cars, portable applications, augmented reality systems, medical image analysis etc. There are a lot of methods that have been developed to improve the accuracy and complexity of object detection, like the generations of R‐CNNs and YOLOs. However, these methods are not the most efficient architectures, and there is always room to improve. In this study, the 5th version of YOLO is employed and the improved architecture, Inception‐YOLO, is presented. The model significantly outperforms the SOTA YOLO family. Specifically, the improvements can be summarised as follows: impressive improvement of floating point operations (FLOPs) and number of parameters, as well as improvement in accuracy compared to the models with fewer FLOPs. All our presented approaches, like the optimized inception module, proposed structures for CSP and SPPF, and the improved loss function used in this research, work together to incrementally improve detection results, accuracy, demanded memory, and FLOPs simultaneously. For a glimpse of performance, the Inception‐YOLO‐S model hits 38.7% AP with 5.9M parameters and 11.5 BFLOPs and outperforms YOLOv5‐S with 37.4% AP, 7.2M parameters, and 16.5 BFLOPs.

Human-AI collaboration to mitigate decision noise in financial underwriting: A study on FinTech innovation in a lending firm

Financial institutions have recognized the value of collaborating human expertise and AI to create high-performance augmented decision-support systems. Stakeholders at lending firms have increasingly acknowledged that plugging data into AI algorithms and eliminating the role of human underwriters by automation, with the expectation of immediate returns on investment from business process automation, is a flawed strategy. This research emphasizes the necessity of auditing the consistency of decisions (or professional judgment) made by human underwriters and monitoring the ability of data to capture the lending policies of a firm to lay a strong foundation for a legitimate system before investing millions in AI projects. The judgments made by experts in the past re-emerge in the future as outcomes or labels in the data used to train and evaluate algorithms. This paper presents Evidential Reasoning-eXplainer, a methodology to estimate probability mass as an extent of support for a given decision on a loan application by jointly assessing multiple independent and conflicting pieces of evidence. It quantifies variability in past decisions by comparing the subjective judgments of underwriters during manual financial underwriting with outcomes estimated from data. The consistency analysis improves decision quality by bridging the gap between past inconsistent decisions and desired ultimate-true decisions. A case study on a specialist lending firm demonstrates the strategic work plan adapted to configure underwriters and developers to capture the correct data and audit the quality of decisions.

Intravenous lipopolysaccharide challenge in early- versus mid-lactation dairy cattle. II: The production and metabolic responses

Most immunometabolic research uses mid-lactation (ML) cows. Cows in early lactation (EL) are in a presumed state of immune suppression/dysregulation and less is known about how they respond to a pathogen. Study objectives were to compare the production and metabolic responses to i.v. LPS and to differentiate between the direct effects of immune activation and the indirect effects of illness-induced hypophagia in EL and ML cows. Cows in EL (n = 11; 20 ± 2 DIM) and ML (n = 12; 131 ± 31 DIM) were enrolled in a 2 × 2 factorial design containing 2 experimental periods (P). During P1 (3 d), cows were fed ad libitum and baseline data were collected. At the initiation of P2 (3 d), cows were randomly assigned to 1 of 2 treatments by lactation stage (LS): (1) EL (EL-LPS; n = 6) or ML (ML-LPS; n = 6) cows administered i.v. a single bolus of 0.09 µg LPS/kg of BW; Escherichia coli O55:B5 or (2) pair-fed (PF) EL (EL-PF; n = 5) or ML (ML-PF; n = 6) cows administered i.v. saline. Administering LPS decreased DMI and this was more severe in EL-LPS than ML-LPS cows (34% and 11% relative to baseline, respectively). By design, P2 DMI patterns were similar in the PF groups compared with their LPS counterparts. Milk yield decreased following LPS (42% on d 1 relative to P1) and despite an exacerbated decrease in EL-LPS cows on d 1 (25% relative to ML-LPS), remained similar between LS from d 2 to 3. The EL-LPS cows had increased milk fat content, but no difference in protein and lactose percentages compared with ML-LPS cows. Further, cumulative ECM yield was increased (21%) in EL-LPS compared with ML-LPS cows. During P2, EL-LPS cows had a more intense increase in MUN and BUN than ML-LPS and EL-PF cows. Administering LPS did not cause hypoglycemia in either EL-LPS or ML-LPS cows, but glucose was increased (33%) in EL-LPS compared with EL-PF. Hyperinsulinemia occurred after LPS, and insulin was further increased in ML-LPS than EL-LPS cows (2.2-fold at 12 h peak). During P2, circulating glucagon increased only in EL-LPS cows (64% relative to all other groups). Both EL groups had increased NEFA at 3 and 6 h after LPS from baseline (56%), but NEFA in EL-LPS cows gradually returned to baseline thereafter and were reduced relative to EL-PF until 36 h (50% from 12 to 24 h). Alterations in BHB did not differ between ML groups, but EL-LPS had reduced BHB compared with EL-PF from 24 to 72 h (51%). Results indicate that there are distinct LS differences in the anorexic and metabolic responses to immune activation. Collectively, EL cows are more sensitive to the catabolic effects of LPS than ML cows, but these exacerbated metabolic responses appear coordinated to fuel an augmented immune system while simultaneously supporting milk synthesis.

Augmented reality-assisted microvascular decompression for glossopharyngeal neuralgia: a case report

Abstract Glossopharyngeal neuralgia is a rare condition characterized by pain along the distribution of the glossopharyngeal nerve. Surgical approaches via microvascular decompression represent a common treatment strategy. For this procedure, an understanding of the location of the cranial nerve and the offending vasculature is critically important. A mixed reality system was used to register patient-specific 3D models onto the patients head for operative planning and anatomical visualization. A 58-year-old female presented to neurosurgery with severe right-sided facial, tongue, and jaw pain unresponsive to multiple conservative therapies including medication. T2-weighted MRI with FIESTA sequence demonstrated right posterior inferior communicating artery compression of the right glossopharyngeal nerve entry zone. An augmented reality system was used to visualize the patients’ anatomy overlaid onto the patients’ head. A microvascular decompression of Cranial Nerves IX and X was performed via a retrosigmoid approach. Patient obtained significant relief of preoperative pain symptoms without complications.

Holorailway: an augmented reality system to support assembly operations in the railway industry

During the last two decades, industrial applications of augmented reality (AR) have been incorporated in sectors such as automotive or aeronautics in tasks including manufacturing, maintenance, and assembly. However, AR’s potential has yet to be demonstrated in the railway sector due to its complexity and difficulties in automating tasks. This work aims to present an AR system based on HoloLens 2 to assist the assembly process of insulation panels in the railway sector significantly decreasing the time required to perform the assembly. Along with the technical description of the system, an exhaustive validation process is provided where the assembly using the developed system is compared to the traditional assembly method as used by a company that has facilitated a case study. The results obtained show that the system presented outperforms the traditional solution by 78% in the time spent in the localization subtask, which means a 47% decrease in the global assembly time. Additionally, it decreases the number of errors in 88% of the cases, obtaining a more precise and almost error-free assembly process. Finally, it is also proven that using AR removes the dependence on users’ prior knowledge of the system to facilitate assembly.

Dual defect detection and generation system in planar surface

The main problem of applying neural networks in the task of defect detection is that there is a limitation in the size of the set of annotated defect images compared to the set of defect-free images. This imbalance in the dataset poses a challenge for the model to effectively learn and generalize patterns associated with defects. The scarcity of annotated defect samples hinders the model's ability to capture the diverse characteristics of anomalies, making it prone to misdetection and reduced performance on real-world data. To solve this problem, the authors have proposed a neural network architecture based on two neural networks U-Net++ and PatchCore trained in the student-teacher paradigm. In this paradigm, the student model undergoes initial training exclusively on defect-free images. Consequently, disparities emerge in the learned features between the student and teacher models, facilitating the computation of an anomaly metric and streamlining the anomaly localization process. The aim of the research is to improve the efficiency of defect detection by creating methods and algorithms, and dataset augmentation systems, as an option to solve the problem of defect-free images. The overarching goal of this research is to enhance the efficacy of defect detection through the development of methodologies, algorithms, and dataset augmentation systems. This serves as a strategic approach to address the inherent challenge posed by the scarcity of annotated defect images in comparison to their defect-free counterparts. By creating methods and augmenting datasets, we aim to mitigate the limitations imposed by the uneven distribution of defect and defect-free samples, ultimately advancing the robustness and performance of defect detection models. A dual system of defect detection based on the U-Net++ pre-trained network and feature estimation of individual fragments based on the PatchCore network is presented. The research incorporates computational experiments designed to assess the effectiveness of the proposed method in comparison to existing counterparts. An in-depth efficiency analysis has been conducted, focusing on dataset enrichment using the generative-adversarial network ResStyleGAN. This examination aims to provide empirical evidence of the method's performance and its potential advantages over established approaches in the context of defect detection. The method developed, centered around the dual system PatchNet++ and preliminary generation of new defects using ResStyleGAN, is positioned for practical application in real production scenarios. Subsequent stages involve a detailed analysis to evaluate its performance and suitability in real-world settings.

Observer‐based dual event‐triggered control for non‐weighted L2$$ {\mathcal{L}}_2 $$‐gain of switched linear systems

AbstractAs everyone knows, strict mode‐dependent event‐triggered mechanism (MDETM) is rarely studied for switched systems due to the difficulty in settling down the relationship between the dwell time (DT) and triggered intervals. This problem is satisfactorily solved by considering the exponential stabilization via observer‐based dual MDETMs in switched linear systems. The dual MDETMs on the sensor‐controller (S‐C) channel and controller‐actuator (C‐A) channel are designed respectively according to mode‐dependent average dwell time (MDADT). The MDETMs on the C‐A channel are generated based on the MDETMs on the S‐C channel, which makes the new control technique strict mode‐dependent and reduces conservatism as much as possible. Furthermore, when there exists external disturbance, a non‐weighted ‐gain with better performance than existing results is given. By studying an augmented system, exponential stabilization is achieved through a new event‐triggered state estimation (ETSE) and dual MDETMs. The observer gain, controller gain, and non‐weighted ‐gain are derived through an effective algorithm. Finally, two numerical examples are given to illustrate the effectiveness of theoretical research.

Breath Measurement Method for Synchronized Reproduction of Biological Tones in an Augmented Reality Auscultation Training System.

An educational augmented reality auscultation system (EARS) is proposed to enhance the reality of auscultation training using a simulated patient. The conventional EARS cannot accurately reproduce breath sounds according to the breathing of a simulated patient because the system instructs the breathing rhythm. In this study, we propose breath measurement methods that can be integrated into the chest piece of a stethoscope. We investigate methods using the thoracic variations and frequency characteristics of breath sounds. An accelerometer, a magnetic sensor, a gyro sensor, a pressure sensor, and a microphone were selected as the sensors. For measurement with the magnetic sensor, we proposed a method by detecting the breathing waveform in terms of changes in the magnetic field accompanying the surface deformation of the stethoscope based on thoracic variations using a magnet. During breath sound measurement, the frequency spectra of the breath sounds acquired by the built-in microphone were calculated. The breathing waveforms were obtained from the difference in characteristics between the breath sounds during exhalation and inhalation. The result showed the average value of the correlation coefficient with the reference value reached 0.45, indicating the effectiveness of this method as a breath measurement method. And the evaluations suggest more accurate breathing waveforms can be obtained by selecting the measurement method according to breathing method and measurement point.

The Development and Usability Assessment of an Augmented Reality Decision Support System to Address Burn Patient Management

Critical care injuries, such as burn trauma, require specialized skillsets and knowledge. A clinical decision support system to aid clinicians in providing burn patient management can increase proficiency and provide knowledge content for specific interventions. In austere environments, decision support tools can be used to aid in decision making and task guidance when skilled personnel or resources are limited. Therefore, we developed a novel software system that utilizes augmented reality (AR) capabilities to provide enhanced step-by-step instructions based on best practices for managing burn patients. To better understand how new technologies, such as AR, can be used for burn care management, we developed a burn care application for use on a heads-up display. We developed four sub-set applications for documenting and conducting burn wound mapping, fluid resuscitation, medication calculations, and an escharotomy. After development, we conducted a usability study utilizing the System Usability Scale, pre- and post- simulation surveys, and after-action reviews to evaluate the AR-based software application in a simulation scenario. Results of the study indicate that the decision support tool has generalized usability and subjects were able to use the software as intended. Here we present the first use case of a comprehensive burn management system utilizing augmented reality capabilities to deliver care.

NEW STRATEGY THE FOR DESIGNATION OF THE INTEGRITY PARAMETER IN SBAS POSITIONING IN AIR TRANSPORT

The article shows the results of a study on the determination of SBAS satellite positioning integrity parameters as a HPL and VPL protection levels. To this end, a modified algorithm was developed to determine the HPL and VPL protection levels from a common aircraft position navigation solution based on EGNOS and SDCM augmentation systems. The developed mathematical scheme was verified on real GNSS kinematic data recorded by two onboard Septentrio AsterRx2i and Trimble Alloy receivers installed on a Diamond DA 20-C aircraft. Based on the conducted tests, it was found that the HPL parameter does not exceed 12.24 m, while respectively the VPL does not exceed 18.01 m. In addition, in the course of the study it was found that the proposed EGNOS+SDCM solution improves the HPL/VPL integrity determination in relation to the EGNOS solution by 8÷66%. The mathematical scheme used in the study was also applied to designation the HPL/VPL terms for the UAV platform. The obtained results of the HPL/VPL values for the positioning of the aircraft and the UAV platform show a high efficiency of the developed algorithm for improving the integrity parameter.