Usefulness of driver's eye movement measurement to detect potential risks under combined conditions of taking second-generation antihistamines and calling tasks.

BACKGROUND: Concerns persist regarding the potential reduction in driving performance due to taking second-generation antihistamines or performing hands-free calling. Previous studies have indicated a potential risk to driving performance under an emergency event when these two factors are combined, whereas a non-emergency event was operated effectively. Currently, there is a lack of a discriminative index capable of detecting the potential risks of driving performance impairment. This study aims to investigate the relationship between driving performance and eye movements under combined conditions of taking second-generation antihistamines and a calling task, and to assess the usefulness of eye movement measurements as a discriminative index for detecting potential risks of driving performance impairment. METHODS: Participants engaged in a simulated driving task, which included a calling task, both under taking or not taking second-generation antihistamines. Driving performance and eye movements were monitored during both emergency and non-emergency events, assessing their correlation between driving performance and eye movements. The study further evaluated the usefulness of eye movement as a discriminative index for potential driving impairment risk through receiver operating characteristic (ROC) analysis. RESULTS: In the case of a non-emergency event, no correlation was observed between driving performance and eye movement under the combined conditions. Conversely, a correlation was observed during an emergency event. The ROC analysis, conducted to assess the discriminative index capability of eye movements in detecting the potential risk of driving performance impairment, demonstrated a high discriminative power, with an area under the curve of 0.833. CONCLUSIONS: The findings of this study show the correlation between driving performance and eye movements under the concurrent influence of second-generation antihistamines and a calling task, suggesting the usefulness of eye movement measurement as a discriminant index for detecting potential risks of driving performance impairment.

Ribosomal computing: implementation of the computational method.

BACKGROUND: Several computational and mathematical models of protein synthesis have been explored to accomplish the quantitative analysis of protein synthesis components and polysome structure. The effect of gene sequence (coding and non-coding region) in protein synthesis, mutation in gene sequence, and functional model of ribosome needs to be explored to investigate the relationship among protein synthesis components further. Ribosomal computing is implemented by imitating the functional property of protein synthesis. RESULT: In the proposed work, a general framework of ribosomal computing is demonstrated by developing a computational model to present the relationship between biological details of protein synthesis and computing principles. Here, mathematical abstractions are chosen carefully without probing into intricate chemical details of the micro-operations of protein synthesis for ease of understanding. This model demonstrates the cause and effect of ribosome stalling during protein synthesis and the relationship between functional protein and gene sequence. Moreover, it also reveals the computing nature of ribosome molecules and other protein synthesis components. The effect of gene mutation on protein synthesis is also explored in this model. CONCLUSION: The computational model for ribosomal computing is implemented in this work. The proposed model demonstrates the relationship among gene sequences and protein synthesis components. This model also helps to implement a simulation environment (a simulator) for generating protein chains from gene sequences and can spot the problem during protein synthesis. Thus, this simulator can identify a disease that can happen due to a protein synthesis problem and suggest precautions for it.

Driving assistant using generative AI pre-generated messages in simulator-based driving assessment: A step towards low-cost simulator-based driving assessment.

This paper presents a novel approach for a low-cost simulator-based driving assessment system incorporating a speech-based assistant, using pre-generated messages from Generative AI to achieve real-time interaction during the assessment. Simulator-based assessment is a crucial apparatus in the research toolkit for various fields. Traditional assessment approaches, like on-road evaluation, though reliable, can be risky, costly, and inaccessible. Simulator-based assessment using stationary driving simulators offers a safer evaluation and can be tailored to specific needs. However, these simulators are often only available to research-focused institutions due to their cost. To address this issue, our study proposes a system with the aforementioned properties aiming to enhance drivers' situational awareness, and foster positive emotional states, i.e., high valence and medium arousal, while assessing participants to prevent subpar performers from proceeding to the next stages of assessment and/or rehabilitation. In addition, this study introduces the speech-based assistant which provides timely guidance adaptable to the ever-changing context of the driving environment and vehicle state. The study's preliminary outcomes reveal encouraging progress, highlighting improved driving performance and positive emotional states when participants are engaged with the assistant during the assessment.

Effects of within-day intervals on adaptation to visually induced motion sickness in a virtual-reality motorcycling simulator.

This study investigated the effects of the time interval between virtual reality (VR) sessions on visually induced motion sickness (VIMS) reduction to better understand adaptation to and recovery from a nauseating VR experience. The participants experienced two 6-min VR sessions of a first-person motorcycle ride through a head-mounted display with (1) a 6-min interval, (2) an interval until the VIMS score reached zero, and (3) a 60-min interval. The results showed that for each condition, VIMS in the second session was aggravated, unchanged, or attenuated, respectively, indicating that additional resting time was necessary for VIMS adaptation. This study suggests that a certain type of multisensory learning attenuates VIMS symptoms within a relatively short time, requiring at least 20 min of additional resting time after subjective recovery from VIMS symptoms. This finding has important implications for reducing the time interval between repeated challenges when adapting to nauseating stimuli during VR experiences.

Meta-analysis of set-based multiple phenotype association test based on GWAS summary statistics from different cohorts.

Genome-wide association studies (GWAS) have emerged as popular tools for identifying genetic variants that are associated with complex diseases. Standard analysis of a GWAS involves assessing the association between each variant and a disease. However, this approach suffers from limited reproducibility and difficulties in detecting multi-variant and pleiotropic effects. Although joint analysis of multiple phenotypes for GWAS can identify and interpret pleiotropic loci which are essential to understand pleiotropy in diseases and complex traits, most of the multiple phenotype association tests are designed for a single variant, resulting in much lower power, especially when their effect sizes are small and only their cumulative effect is associated with multiple phenotypes. To overcome these limitations, set-based multiple phenotype association tests have been developed to enhance statistical power and facilitate the identification and interpretation of pleiotropic regions. In this research, we propose a new method, named Meta-TOW-S, which conducts joint association tests between multiple phenotypes and a set of variants (such as variants in a gene) utilizing GWAS summary statistics from different cohorts. Our approach applies the set-based method that Tests for the effect of an Optimal Weighted combination of variants in a gene (TOW) and accounts for sample size differences across GWAS cohorts by employing the Cauchy combination method. Meta-TOW-S combines the advantages of set-based tests and multi-phenotype association tests, exhibiting computational efficiency and enabling analysis across multiple phenotypes while accommodating overlapping samples from different GWAS cohorts. To assess the performance of Meta-TOW-S, we develop a phenotype simulator package that encompasses a comprehensive simulation scheme capable of modeling multiple phenotypes and multiple variants, including noise structures and diverse correlation patterns among phenotypes. Simulation studies validate that Meta-TOW-S maintains a desirable Type I error rate. Further simulation under different scenarios shows that Meta-TOW-S can improve power compared with other existing meta-analysis methods. When applied to four psychiatric disorders summary data, Meta-TOW-S detects a greater number of significant genes.

Assessing the impact of cannabis use on freeway driving performance and practices: A comparative analysis with placebo and alcohol-influenced driving.

OBJECTIVE: The objectives of this study were 1) to identify the effects cannabis has on driving performance and individual motor practices when on the freeway compared to placebo and 2) to bring context to the effects of cannabis on driving by comparing effect sizes to those of alcohol. METHODS: Data for analysis was collected from a study of fifty-three participants with a history of tetrahydrocannabinol (THC) cannabis use who completed three visits in randomized order (placebo (0% THC), 6.18% THC, and 10.5% THC). Data for the alcohol analysis was from a subset of eighteen of these participants with a history of recent alcohol use that completed a fourth alcohol visit that targeted a .05 g/210L breath alcohol content (BrAC) during the drive. Comparisons were made using an analysis of variance approach with the SAS General Linear Models Procedure. Cohen's d effect sizes were calculated for the cannabis and alcohol conditions relative to placebo for both the full sample and alcohol subset. RESULTS: Standard deviation of lane position (SDLP) for cannabis significantly increased compared to placebo and the effect size was comparable to that of alcohol at .05 BrAC. Lane departures for cannabis significantly increased relative to placebo as did the time out of the lane. Cannabis use resulted in an increased amount of time at 10% or more below the speed limit for the 6.18% THC condition. Relative to alcohol, cannabis produced more time at slower speeds and less time at speeds more than 10% above the speed limit. CONCLUSIONS: Multiple factors of lateral and longitudinal vehicle control on the freeway showed statistical significance. Drivers under the influence of cannabis exhibited higher rates of driving errors but also showed more cautious behaviors such as generally lower speeds on the freeway. Compared with alcohol, effect sizes varied. For longitudinal control, there were larger effect sizes for alcohol with speed effects in opposite directions, but relatively equivalent effect sizes for lateral control and driving errors associated with lane keeping.

Effects of hippotherapy on motor function of children with cerebral palsy: a systematic review study.

Cerebral palsy includes a spectrum of neurodevelopmental disorders caused by brain damage, leading to impairment of movement, posture, and balance for a lifetime. There are many therapeutic interventions for cerebral palsy. One of them is hippotherapy, an alternative physical therapy. It is a type of equine-assisted activity and therapy where children with cerebral palsy and motor function skills interact with a horse. We aimed to study the effects of hippotherapy, as an alternative therapy, on the motor function of children with cerebral palsy. We performed a review of the latest literature on hippotherapy and cerebral palsy. The criteria we used were specific keywords, publication date, age of the subjects/studied population, and article type. The outcome of our research resulted in ten relevant studies. The findings demonstrate improvements in various aspects of motor function - more specifically in gross motor function skills, balance, coordination, gait parameters, and muscle strength. Two of ten studies used the Horse-Riding Simulator with significant improvements in postural control in sitting, motor function, and hip abduction range of motion. Hippotherapy can improve motor function skills of children between 2 and 14 years of age with cerebral palsy, affecting their well-being and overall quality of life. It can have a positive effect either as a standalone treatment or as a part of other traditional therapies. Extended research is needed to assess whether hippotherapy may present significant long-term changes in motor skills in children with cerebral palsy.

Investigating looming tactile takeover requests with various levels of urgency in automated vehicles.

Designing an effective takeover request (TOR) in conditionally automated vehicles is crucial to ensure driving safety when the system reaches its limit. In our study, we aimed to investigate the effects of looming tactile TORs (whose urgency is dynamically mapped to the situation's criticality as the vehicle approaches the upcoming obstacle) on takeover performance and subjective experience compared with conventional non-looming TORs (several tactile pulses with consistent inter-pulse intervals). In addition, the impact of the TOR urgency level (with urgency levels matched or unmatched to the situation's criticality) was considered. A total of 30 participants were recruited for this study. They were first asked to map the urgency of tactile signals to the criticality of takeover situations with various times to collision according to the recorded video clips. The looming TORs were constructed based on these mapping results. Then, a simulated driving experiment, employing a within-subject design, was conducted to explore the effects of the tactile TOR type (looming vs. non-looming) and urgency level (less urgency vs. matched urgency vs. greater urgency) on takeover performance and drivers' subjective experience. The results showed that the looming TOR can lead to a shorter takeover time and less maximum lateral acceleration compared with the non-looming TOR. Drivers also rated the looming TOR as more useful. Therefore, the looming TOR has great application potential for enhancing driving safety in automated vehicles. In addition, we found that as the TOR's level of urgency increased, the takeover time decreased. However, the TOR with an urgency level matched to the situation's criticality received higher usefulness and satisfaction ratings, suggesting that there was an important trade-off between the advantage of high-urgency TORs in speeding up driver responses and its cost of a poor experience. The findings of our study shed some light on the design and implementation of the takeover warning system for related practitioners.

Systematic review of subjective validation methods for computerized colonoscopy simulators.

Introduction: In recent years, different approaches have been used to conduct a subjective assessment of colonoscopy simulators. The purpose of this paper is to review these different approaches, specifically the ones used for computerized simulators, as the first step for the design of a standard validation procedure for this type of simulators. Methods: A systematic review was conducted by searching papers after 2010 in PubMed, Google Scholar, ScienceDirect, and IEEE Xplore databases. Papers were screened and reviewed for procedures regarding the subjective validation of computerized simulators for traditional colonoscopy with an endoscope. Results: An initial search in the databases identified 2094 papers, of which 7 remained after exhaustive review and application of exclusion criteria. All studies used questionnaires for subjective validation, with "face" being the most common validity type tested, while "content" validity and "usability" were less prominent. Conclusions: A classification of subscales for testing face validity was derived from the studies. The Colonoscopy Simulator Realism Questionnaire (CSRQ) was selected as the guide to follow for the development of future questionnaires related to subjective validation. Mislabeling of the validity tested in the studies due to ambiguous interpretations of the validity types was a common occurrence observed in the reviewed studies.

Bacterial accumulation dynamics in runoff from extreme precipitation.

Extreme precipitation can significantly influence the water quality of surface waters. However, the total amount of bacteria carried by rainfall runoff is poorly understood. Here, thirty rainfall scenarios were simulated by artificial rainfall simulators, with designed rainfall intensity ranging from 19.3 to 250 mm/h. The instantaneous concentration ranges of R2A, nutrient agar (NA) culturable bacteria, and viable bacteria in runoff depended on the types of underlying surfaces. The instantaneous bacterial concentrations in runoff generated by forest lands, grasslands and bare soil were: R2A culturable bacteria = 104.5-6.3, 104.5-6.1, 104.0-5.3 colony-forming units (CFU)/mL, NA culturable bacteria = 104.0-6.0, 103.9-5.8, 103.2-4.9 CFU/mL, and viable bacteria = 106.4-8.0, 107.0-8.9, 106.4-7.6 cells/mL. Based on the measured bacterial instantaneous concentration in runoff, cumulative dynamic models were established, and the maximum amount of culturable bacteria and viable bacteria entering water sources were estimated to be 109.38-11.31 CFU/m2 and 1011.84-13.25 cells/m2, respectively. The model fitting and the bacterial accumulation dynamics were influenced by the rainfall types (p < 0.01). Surface runoff from the underlying surface of forest lands and grasslands had a high microbial risk that persisted even during the "Drought-to-Deluge Transition". Bacterial accumulation models provide valuable insight for predicting microbial risks in catchments during precipitation and can serve as theoretical support for further ensuring the safety of drinking water under the challenge of climate change.

Partial weight-bearing and range of motion limitation significantly reduce the loads at medial meniscus posterior root repair sutures in a cadaveric biomechanical model.

PURPOSE: The aim of this study was to investigate the influence of medial meniscus posterior root avulsion (MMPRA) before and after surgical treatment on the biomechanics of the knee joint, including suture repair forces during daily and crutch-assisted gait movements. METHODS: MMPRA were investigated in eight human cadaver knee joint specimens by a dynamic knee joint simulator with daily (normal gait, gait with additional rotational movement, standing up, sitting down) and rehabilitation-associated movements (crutch-assisted gait with limited flexion range of motion [30°] and 30% [toe-touch weight-bearing, TTWB] and 50% of body weight [partial weight-bearing, PWB]) with simulated physiologic muscle forces. Each specimen was tested in intact, torn and repaired (transtibial suture) state. The biomechanical parameters were: medial mean contact pressure and area, knee joint kinematics, medial displacement of the posterior meniscus horn and loading on the anchoring suture. RESULTS: Significant reduction of the contact area due to the avulsion was observed in all movements except for PWB and sitting down. MMPRA repair significantly increased the contact areas during all movements, bringing them to levels statistically indistinguishable from the initial state. MMPRA resulted in a medial displacement up to 12.8 mm (sitting down) and could be reattached with a residual displacement ranging from 0.7 mm (PWB) to 5.7 mm (standing up), all significantly (p < 0.001) reduced compared to the torn state. The mean peak anchoring suture load increased from TTWB (77 N), PWB (91 N) to normal gait (194 N), gait rotation (207 N), sitting (201 N; p < 0.01) and to standing up (232 N; p = 0.03). CONCLUSION: Surgical treatment of MMPRA allows restoration of physiological knee joint biomechanics. Crutch-assisted movements reduce the loading of the repair suture, thus likewise the risk for failure. From a biomechanical point of view, crutch-assisted movements are recommended for the early rehabilitation phase after MMPRA repair. LEVEL OF EVIDENCE: Level V.

Characterization of an Advanced Blast Simulator for Investigation of Large Scale Blast Traumatic Brain Injury Studies.

Blast traumatic brain injury (bTBI) is a prominent military health concern. The pervasiveness and long-term impacts of this injury highlight the need for investigation of the physiological outcomes of bTBI. Preclinical models allow for the evaluation of behavioral and neuropathological sequelae associated with bTBI. Studies have implemented rodent models to investigate bTBI due to the relative small size and low cost; however, a large animal model with similar neuroanatomical structure to humans is essential for clinical translation. Small blast simulators are used to induce bTBI in rodents, but a large animal model demands a larger device. This study describes a large advanced blast simulator (ABS4) that is a gas-detonation-driven system consisting of 5 sections totaling 40 ft in length with a cross-section of 4 × 4 ft at the test section. It is highly suitable for large animals and human surrogate investigations. This work characterized the ABS4 in preparation of large-scale bTBI testing. An array of tests were conducted with target overpressures in the test section ranging from 10 to 50 psi, and the pressure-time profiles clearly illustrate the essential characteristics of a free-field blast wave, specifically a sharp peak pressure and a defined negative phase. Multiple blast tests conducted at the same target pressure produced very similar pressure profiles, exhibiting the reproducibility of the ABS4 system. With its extensive range of pressures and substantial size, the ABS4 will permit military-relevant translational blast testing.

Investigation of the effectiveness of preoperative intubation simulation using a custom-made simulator for pediatric patients with difficult airway: a pilot study.

The purpose of this study is to investigate whether preoperative intubation simulation using custom-made simulator is useful during anesthesia induction for the children who have difficult airway. We included the children under 15 years of age who have difficult airway which had been already known. Prior to the scheduled surgery, CT imaging was performed and a 3D reconstruction of the face from the chest was performed. Then custom-made airway simulator was made. We tried to intubate custom-made simulator of patients preoperatively. We planned how to intubate the patient for anesthesia induction from the result of intubation simulation. The findings of direct laryngoscopy were compared with the findings during intubation. Three patients were included in this study. It took up to 3 weeks to create a simulator, which was difficult due to time constraints to accommodate emergency surgeries. Simulation findings correlated well with findings during anesthesia induction. There were no cases of severe hypotension or hypoxia during induction of anesthesia with the planned intubation method. In conclusion, preoperative intubation simulation using custom-made simulator may be useful for the patients who have difficult airway.

Physiological control for left ventricular assist devices based on deep reinforcement learning.

BACKGROUND: The improvement of controllers of left ventricular assist device (LVAD) technology supporting heart failure (HF) patients has enormous impact, given the high prevalence and mortality of HF in the population. The use of reinforcement learning for control applications in LVAD remains minimally explored. This work introduces a preload-based deep reinforcement learning control for LVAD based on the proximal policy optimization algorithm. METHODS: The deep reinforcement learning control is built upon data derived from a deterministic high-fidelity cardiorespiratory simulator exposed to variations of total blood volume, heart rate, systemic vascular resistance, pulmonary vascular resistance, right ventricular end-systolic elastance, and left ventricular end-systolic elastance, to replicate realistic inter- and intra-patient variability of patients with a severe HF supported by LVAD. The deep reinforcement learning control obtained in this work is trained to avoid ventricular suction and allow aortic valve opening by using left ventricular pressure signals: end-diastolic pressure, maximum pressure in the left ventricle (LV), and maximum pressure in the aorta. RESULTS: The results show controller obtained in this work, compared to the constant speed LVAD alternative, assures a more stable end-diastolic volume (EDV), with a standard deviation of 5 mL and 9 mL, respectively, and a higher degree of aortic flow, with an average flow of 1.1 L/min and 0.9 L/min, respectively. CONCLUSION: This work implements a deep reinforcement learning controller in a high-fidelity cardiorespiratory simulator, resulting in increases of flow through the aortic valve and increases of EDV stability, when compared to a constant speed LVAD strategy.

Designing an Experimental Platform to Assess Ergonomic Factors and Distraction Index in Law Enforcement Vehicles during Mission-Based Routes.

Mission-based routes for various occupations play a crucial role in occupational driver safety, with accident causes varying according to specific mission requirements. This study focuses on the development of a system to address driver distraction among law enforcement officers by optimizing the Driver-Vehicle Interface (DVI). Poorly designed DVIs in law enforcement vehicles, often fitted with aftermarket police equipment, can lead to perceptual-motor problems such as obstructed vision, difficulty reaching controls, and operational errors, resulting in driver distraction. To mitigate these issues, we developed a driving simulation platform specifically for law enforcement vehicles. The development process involved the selection and placement of sensors to monitor driver behavior and interaction with equipment. Key criteria for sensor selection included accuracy, reliability, and the ability to integrate seamlessly with existing vehicle systems. Sensor positions were strategically located based on previous ergonomic studies and digital human modeling to ensure comprehensive monitoring without obstructing the driver's field of view or access to controls. Our system incorporates sensors positioned on the dashboard, steering wheel, and critical control interfaces, providing real-time data on driver interactions with the vehicle equipment. A supervised machine learning-based prediction model was devised to evaluate the driver's level of distraction. The configured placement and integration of sensors should be further studied to ensure the updated DVI reduces driver distraction and supports safer mission-based driving operations.

Mobile phone conversation during nighttime driving: Effects on driving behavior.

OBJECTIVES: This study aims to investigate the impact of mobile phone use (specifically, conversation), considering various use modes, on driving behavior at night. Mobile phone use is a source of driver distraction and has been associated with increased accident risk. Driving at night also entails higher accident risk and severity compared to daytime driving. Several studies have investigated the impact of mobile phone use on driving behavior; however, only a few have explored the differences between the different use modes. Most present studies involved daytime driving, although mobile phone use at night is equally if not more prevalent. METHOD: A driving simulator experiment was designed in which 55 participants drove under nighttime simulator conditions, in different road environments (urban and rural) and under different types of distraction: no distraction, handheld, wired earphone, and speaker mode. The drives were performed during late afternoon and evening hours to resemble nighttime conditions both in the simulator and in the actual environment. Participants also completed a questionnaire for collection of different types of data. RESULTS: Results highlight the effect of mobile phone use on driving behavior, through specific indicators. Mobile phone use resulted in reduced 85th percentile driving speed and 85th percentile acceleration and increased reaction time and lateral deviation. However, safer stopping distance was observed in rural roads. Parameters relative to mobile phone use familiarity and exposure were found to mitigate mobile phone use effects. CONCLUSIONS: Mobile phones affect driving behavior at night in a similar manner to that noted in several different studies considering daytime driving. The hands-free regulation should be revisited, because driver distraction also occurred under this particular use mode. Further research is required considering mobile phone use familiarity and exposure and effects of mobile phone use, because the latter is reduced with an increase in the former. Stopping distance, an understudied but more immediate surrogate measure of road safety, was increased with mobile phone use, mainly as a result of the risk compensation behavior that drivers adopt, indicating that more research is required in this field.

Realistic 3D Simulators for Automotive: A Review of Main Applications and Features.

Recent advancements in vehicle technology have stimulated innovation across the automotive sector, from Advanced Driver Assistance Systems (ADAS) to autonomous driving and motorsport applications. Modern vehicles, equipped with sensors for perception, localization, navigation, and actuators for autonomous driving, generate vast amounts of data used for training and evaluating autonomous systems. Real-world testing is essential for validation but is complex, expensive, and time-intensive, requiring multiple vehicles and reference systems. To address these challenges, computer graphics-based simulators offer a compelling solution by providing high-fidelity 3D environments to simulate vehicles and road users. These simulators are crucial for developing, validating, and testing ADAS, autonomous driving systems, and cooperative driving systems, and enhancing vehicle performance and driver training in motorsport. This paper reviews computer graphics-based simulators tailored for automotive applications. It begins with an overview of their applications and analyzes their key features. Additionally, this paper compares five open-source (CARLA, AirSim, LGSVL, AWSIM, and DeepDrive) and ten commercial simulators. Our findings indicate that open-source simulators are best for the research community, offering realistic 3D environments, multiple sensor support, APIs, co-simulation, and community support. Conversely, commercial simulators, while less extensible, provide a broader set of features and solutions.

Safety, Efficiency, and Mental Workload in Simulated Teledriving of a Vehicle as Functions of Camera Viewpoint.

Teleoperation services are expected to operate on-road and often in urban areas. In current teleoperation applications, teleoperators gain a higher viewpoint of the environment from a camera on the vehicle's roof. However, it is unclear how this viewpoint compares to a conventional viewpoint in terms of safety, efficiency, and mental workload. In the current study, teleoperators (n = 148) performed driving tasks in a simulated urban environment with a conventional viewpoint (i.e., the simulated camera was positioned inside the vehicle at the height of a driver's eyes) and a higher viewpoint (the simulated camera was positioned on the vehicle roof). The tasks required negotiating road geometry and other road users. At the end of the session, participants completed the NASA-TLX questionnaire. Results showed that participants completed most tasks faster with the higher viewpoint and reported lower frustration and mental demand. The camera position did not affect collision rates nor the probability of hard braking and steering events. We conclude that a viewpoint from the vehicle roof may improve teleoperation efficiency without compromising driving safety, while also lowering the teleoperators' mental workload.

Examining the applicability of virtual battle space for stress management training in military personnel-A validation study.

Military personnel are often exposed to high levels of both physical and psychological challenges in their work environment and therefore it is important to be trained on how to handle stressful situations. The primary aim of this study was to examine whether military-specific virtual battle space (VBS) scenarios could elicit a physiological and subjective stress response in healthy military personnel, as compared to that of a virtual reality height exposure (VR-HE) stress task that has shown to reliably increase stress levels. Twenty participants engaged in two VBS scenarios and the VR-HE during separate sessions, while measurements of heart rate (HR), heart rate variability (HRV), respiration rate, and subjective stress levels were collected. Contrary to our initial expectations, analysis revealed that neither of the VBS scenarios induced a significant stress response, as indicated by stable HR, HRV, and low subjective stress levels. However, the VR-HE task did elicit a significant physiological stress response, evidenced by increased HR and HRV changes, aligning with previous research findings. Moreover, no discernible alterations were detected in cognitive performance subsequent to these stressors. These results suggest that the current VBS scenarios, despite their potential, may not be effective for stress-related training activities within military settings. The absence of a significant stress response in the VBS conditions points to the need for more immersive and engaging scenarios. By integrating interactive and demanding elements, as well as physical feedback systems and real-time communication, VBS training might better mimic real-world stressors and improve stress resilience in military personnel. The findings of this study have broader implications for stress research and training, suggesting the need for scenario design improvements in virtual training environments to effectively induce stress and improve stress management across various high-stress professions.

Development and assessment of case-specific physical and augmented reality simulators for intracranial aneurysm clipping.

BACKGROUND: Microsurgical clipping is a delicate neurosurgical procedure used to treat complex Unruptured Intracranial Aneurysms (UIAs) whose outcome is dependent on surgeon's experience. Simulations are emerging as excellent complements to standard training, but their adoption is limited by the realism they provide. The aim of this study was to develop and validate a microsurgical clipping simulator platform. METHODS: Physical and holographic simulators of UIA clipping have been developed. The physical phantom consisted of a 3D printed hard skull and five (n = 5) rapidly interchangeable, perfused and fluorescence compatible 3D printed aneurysm silicone phantoms. The holographic clipping simulation included a real-time finite-element-model of the aneurysm sac, allowing interaction with a virtual clip and its occlusion. Validity, usability, usefulness and applications of the simulators have been assessed through clinical scores for aneurysm occlusion and a questionnaire study involving 14 neurosurgical residents (R) and specialists (S) for both the physical (p) and holographic (h) simulators by scores going from 1 (very poor) to 5 (excellent). RESULTS: The physical simulator allowed to replicate successfully and accurately the patient-specific anatomy. UIA phantoms were manufactured with an average dimensional deviation from design of 0.096 mm and a dome thickness of 0.41 ± 0.11 mm. The holographic simulation executed at 25-50 fps allowing to gain unique insights on the anatomy and testing of the application of several clips without manufacturing costs. Aneurysm closure in the physical model evaluated by fluorescence simulation and post-operative CT revealed Raymond 1 (full) occlusion respectively in 68.89% and 73.33% of the cases. For both the simulators content validity, construct validity, usability and usefulness have been observed, with the highest scores observed in clip selection usefulness Rp=4.78, Sp=5.00 and Rh=4.00, Sh=5.00 for the printed and holographic simulators. CONCLUSIONS: Both the physical and the holographic simulators were validated and resulted usable and useful in selecting valid clips and discarding unsuitable ones. Thus, they represent ideal platforms for realistic patient-specific simulation-based training of neurosurgical residents and hold the potential for further applications in preoperative planning.