Real Measurements Research Articles

Virtual Digital Laboratory Vernier as a Tool of Implementing STEM-Education Principles in Physics Lessons

The article highlights the results of the theoretical and methodological analysis of the issue of the use of the Vernier digital virtual laboratory as an innovative tool for implementing the principles of STEM education in physics lessons in high school. The purpose of this research paper is to justify the feasibility of integrating digital laboratories into the physics curriculum, which allows for its modernization through the integration of science, technology, engineering and mathematics. The study's methodological foundation is based on the active learning concept developed by D. Sokoloff, R. Thornton and P. Laws. According to it, the active nature of learning physics using the Vernier digital laboratory is ensured by the ability to conduct real, high-precision, and multiple measurements of various physical quantities, analyze the obtained data, visualize them as graphs or charts, and interactively adjust and generalize the results of the experiment. The main advantages and disadvantages of using this innovative learning tool have been analyzed, and its compliance with safety, accessibility and adaptability requirements has been determined. The content of implementing the scientific, technological, engineering and mathematical aspects of STEM education through the methodology of using the Vernier digital laboratory in physics lessons has been explored. An example of a tentative lesson plan for a physics class using the Vernier digital laboratory is provided. Based on the conducted research and the practice of using the Vernier digital laboratory in middle school physics lessons, it has been concluded that it has significant and comprehensive educational potential as an innovative tool for implementing STEM education principles.

2º Capítulo

This paper presents the results of a study by the Hegel-Ceará study group on the first part of Media Real, contained in Hegel's Science of Logic, more specifically in the Doctrine of Being. On that occasion, we presented this research at the 8th Meeting of Readings in Logic. The conception of measure in question was immediately put forward as a dialectical relationship between different measures, since we can properly consider it as a relationship of measures, because in the conception in question there are various elements that present themselves dialectically in the different relationships. Based on this understanding, we present the proposed speculative dialectical development, in order to understand the systematic importance of Real Measure, Item A.

Fundamental effects of array density and modulation frequency on image quality of diffuse optical tomography.

Diffuse optical tomography (DOT) provides three-dimensional image reconstruction of chromophore perturbations within a turbid volume. Two leading strategies to optimize DOT image quality include, (i) arrays of regular, interlacing, high-density (HD) grids of sources and detectors with closest spacing less than 15mm, or (ii) source modulated light of order ∼100MHz. However, the general principles for how these crucial design parameters of array density and modulation frequency may interact to provide an optimal system design have yet to be elucidated. Herein, we systematically evaluated how these design parameters effect image quality via multiple key metrics. Specifically, we simulated 32 system designs with realistic measurement noise and quantified localization error, spatial resolution, signal-to-noise, and localization depth of field for each of ∼85000 point spread functions in each model. We found that array density had a far stronger effect on image quality metrics than modulation frequency. Additionally, model fits for image quality metrics revealed that potential improvements diminish with regular arrays denser than 9mm closest spacing. Further, for a given array density, 300MHz source modulation provided the deepest reliable imaging compared to other frequencies. Our results indicate that both array density and modulation frequency affect the spatial sampling of tissue, which asymptotically saturates due to photon diffusivity within a turbid volume. In summary, our results provide comprehensive perspectives for optimizing future DOT system designs in applications from wearable functional brain imaging to breast tumor detection.

Underwater Refractive Stereo Vision Measurement and Simulation Imaging Model Based on Optical Path

When light passes through air–glass and glass–water interfaces, refraction occurs, which affects the accuracy of stereo vision three-dimensional measurements of underwater targets. To eliminate the impact of refraction, we developed a refractive stereo vision measurement model based on light propagation paths, utilizing the normalized coordinate of the underwater target. This model is rigorous in theory, and easy to understand and apply. Additionally, we established an underwater simulation imaging model based on the principle that light travels the shortest time between two points. Simulation experiments conducted using this imaging model verified the performance of the underwater stereo vision measurement model. The results demonstrate that the accuracy achieved by the new measurement model is comparable to that of the stereo vision measurement model in the air and significantly higher than that of the existing refractive measurement model. This is because the light rays from the camera’s optical center to the refraction point at the air–glass interface do not always intersect. The experiments also indicate that the deviation in the refractive index of water lead to corresponding systematic errors in the measurement results. Therefore, in real underwater measurements, it is crucial to carefully calibrate the refractive index of water and maintain the validity of the calibration results.

Rapid-response, low-detection-limit, positive-negative air pressure sensing: GaN chips integrated with hydrophobic PDMS films

Despite the importance of positive and negative pressure sensing in numerous domains, the availability of a single sensing unit adept at handling this dual task remains highly limited. This study introduces a compact optical device capable of swiftly and precisely detecting positive and negative pressures ranging from −35 kPa to 35 kPa. The GaN chip, which serves as a core component of the device, is monolithically integrated with light-emitting and light-detecting elements. By combining a deformable PDMS film coated with a hydrophobic layer, the chip can respond to changes in optical reflectance induced by pressure fluctuations. The integrated sensing device has low detection limits of 4.3 Pa and −7.8 Pa and fast response times of 0.14 s and 0.22 s for positive and negative pressure variations, respectively. The device also demonstrates adaptability in capturing distinct human breathing patterns. The proposed device, characterized by its compactness, responsiveness, and ease of operation, holds promise for a variety of pressure-sensing applications.

Lattice Structures—Mechanical Description with Respect to Additive Manufacturing

Lattice structures, characterized by their repetitive, interlocking patterns, provide an efficient balance of strength, flexibility, and reduced weight, making them essential in fields such as aerospace and automotive engineering. These structures use minimal material while effectively distributing stress, providing high resilience, energy absorption, and impact resistance. Composed of unit cells, lattice structures are highly customizable, from simple 2D honeycomb designs to complex 3D TPMS forms, and they adapt well to additive manufacturing, which minimizes material waste and production costs. In compression tests, lattice structures maintain stiffness even when filled with powder, suggesting minimal effect from the filler material. This paper shows the principles of creating finite element simulations with 3D-printed specimens and with usage of the lattice structure. The comparing of simulation and real testing is also shown in this research. The efficiency in material and energy use underscores the ecological and economic benefits of lattice-based designs, positioning them as a sustainable choice across multiple industries. This research analyzes three selected structures—solid material, pure latices structure, and boxed lattice structure with internal powder. The experimental findings reveal that the simulation error is less than 8% compared to the real measurement. This error is caused by the simplified material model, which is considering the isotropic behavior of the used material PA12GB (not the anisotropic model). The used and analyzed production method was multi jet fusion.

국내 간호대학생의 핵심간호술 교육 중재의 효과: 체계적 고찰

Objectives This study systematically reviewed the effectiveness of core nursing skill training intervention programs for nursing students in Korea. Methods Literature searches were conducted using the databases RISS, KISS, DBpia, and KCI for papers published up to June 2024, with the keyword ‘core nursing skills’. A total of 130 papers were identified, and ultimately, 14 papers were selected for the literature review. Results The literature review revealed that among the research designs, 1 was randomized and 13 were nonrandomized. Core nursing skill training interventions included studies using various methods of retraining and evaluation (10 papers) and studies using various methods of self-practice and evaluation (4 papers). Retraining and evaluation methods included traditional retraining, STEPS Model retraining, senior mentoring retraining, multimedia retraining, and online learning retraining, while self-practice and evaluation methods included traditional self-practice, scenario-based self-practice, Virtual Reality-based self-practice, and self-observation methods. The most frequently applied core nursing skill was subcutaneous injection, appearing in 10 studies, followed by vital signs measurement, intramuscular injection, intermittent gastric tube feeding, and foley catheterization, each appearing in 8 studies. Outcome variables of core nursing skill training programs showed significant effects on confidence in performance (9 papers), clinical performance ability (4 papers), self-efficacy (3 papers), and knowledge (3 papers). Conclusions Korean nursing colleges have researched various intervention programs to achieve core nursing skill competency levels in accordance with the Nursing Education Evaluation Criteria. These programs have shown significant effects on performance confidence, clinical performance ability, and self-efficacy. Therefore, there is a need to develop and utilize diverse intervention programs to enhance learning motivation and satisfaction among nursing students.

Accelerating Deep Learning in Radar Systems: A Simulation Framework for 60 GHz Indoor Radar

FMCW radar systems are increasingly used in diverse applications, and emerging technologies like JCAS offer new opportunities. However, machine learning for radar faces challenges due to limited application-specific datasets, often requiring advanced simulations to supplement real-world data. This paper presents a setup for generating synthetic radar data for indoor environments, evaluated using CNNs. The setup involves comprehensive modeling, including far-field antenna simulations, variations in human radar cross-section, and detailed representations of indoor environments with their corresponding propagation channel properties. These synthetic data are used to train CNNs, and their performance is assessed on real measurement data. The results demonstrate that CNNs trained on synthetic data can perform well when tested on real measurement data. Specifically, the models trained with synthetic data showed performance comparable to models trained with real measurement data, which required a minimum of 300 samples to reach similar levels of accuracy. This result demonstrates that synthetic data can effectively train neural networks, providing an alternative to real measurement data, particularly when collecting sufficient real-world samples is difficult or costly. This approach significantly reduces the time required for generating datasets, and the ability to quickly label data in simulations simplifies and accelerates post-processing. Additionally, the generated datasets can be made more heterogeneous by introducing varying signal conditions, enhancing the diversity and robustness of the training data.

Towards Practical Antenna Selection Based on Multilabel CNN for Large‐Scale MIMO System in an Indoor Scenario

ABSTRACTLarge‐scale multiple input multiple output (MIMO), also known as massive MIMO, serves as a transformative technology that effectively addresses the surging need for data‐intensive applications in the realm of 5G mobile networks and beyond. With a multitude of antennas at its disposal, a large‐scale MIMO base station possesses the capability to concurrently improve by orders of magnitude system spectral and energy efficiencies. Nevertheless, hardware cost and power consumption arise as serious challenge. To circumvent this latter, we investigate the potential of multilabel convolutional neural network (ML‐CNN) to develop an antenna selection (AS) model that based on the available channel state information (CSI) at the transmitter, it dynamically selects the optimal subset of antennas in real‐time. We evaluate the model performance using real indoor channel measurements under three different antenna array configurations. The obtained results demonstrate that the proposed ML‐CNN approach performs similarly to the convex relaxation‐based method, a mathematical technique often used for AS problems that provides optimal solutions with high computation cost, with the advantage of significantly reduced computation time. Moreover, it exhibits strong resilience across various antenna array configurations. Additionally, assessing the ML‐CNN's performance in scenario with imperfect channel estimation confirms its robustness.

3D reconstruction from focus for lensless imaging

The lensless camera is an ultra-thin imaging system that utilizes encoding elements instead of lenses to perceive the light field and reconstruct it through computational methods. Early studies have demonstrated that lensless cameras can encode 3D scenes at various depths in caustic patterns with varying sizes, known as point spread functions (PSFs). By deconvolving measurements with these PSFs, the reconstruction exhibits distinct focusing effects: objects in the focal plane appear sharp, while objects in other planes become blurred. Building upon this feature, we propose a feedforward network based on depth from focus to generate the depth map and the all-in-focus image by reconstructing the focal stack and deriving the probability of pixel clarity. Using our optimization framework, we present superior and more stable depth estimation than previous methods in both simulated data and real measurements captured by our lensless camera.

Simulation study on parameter optimization of transcranial direct current stimulation based on rat brain slices

Transcranial direct current stimulation (tDCS) is an important method for treating mental illnesses and neurodegenerative diseases. This paper reconstructed two ex vivo brain slice models based on rat brain slice staining images and magnetic resonance imaging (MRI) data respectively, and the current densities of hippocampus after cortical tDCS were obtained through finite element calculation. Subsequently, a neuron model was used to calculate the response of rat hippocampal pyramidal neuron under these current densities, and the neuronal responses of the two models under different stimulation parameters were compared. The results show that a minimum stimulation voltage of 17 V can excite hippocampal pyramidal neuron in the model based on brain slice staining images, while 24 V is required in the MRI-based model. The results indicate that the model based on brain slice staining images has advantages in precision and electric field propagation simulation, and its results are closer to real measurements, which can provide guidance for the selection of tDCS parameters and scientific basis for precise stimulation.

Numerical simulation of flow around a transversely oscillating square cylinder at Re=22000

The study utilized OpenFOAM software, combined with the k-ω shear stress transport (SST) turbulence model and Arbitrary Lagrangian-Eulerian (ALE) dynamic mesh method, to investigate the influence of the oscillation amplitude on the flow dynamics around a square cylinder at Re = 2.2 × 104. It was found that various oscillation amplitudes affect the non-Gaussian characteristics of fluctuating pressure differently along the cylinder's surface: diminishing at the leading edge while intensifying at the trailing-edge corner. Concurrently, secondary recirculation bubbles near the cylinder's leading and trailing edges gradually diminish and eventually disappear with increasing oscillation amplitudes. Analysis of the amplitude spectrum of transverse velocity indicates the exclusive presence of odd-order harmonics along the central axis, while both odd and even-order harmonics are observed on either side of the central axis. Additionally, heightened oscillation amplitudes result in increased energy transfer from the cylinder to the fluid, with the energy density function predominantly exhibiting negative values and periodic variations occurring at twice the frequency of cylinder displacement or lift coefficient. As the oscillation amplitude increases, the vortex in the wake region transitions from a single-row to a double-row configuration. The research results provide important theoretical guidance for deepening the understanding of the flow characteristics around the oscillating square cylinder.

Deep Dive Into Noninvasive Biometrics: A Pilot Journey Using Stereo-Video in a Public Aquarium.

Accurate collection of biometric data is important for understanding the biology and conservation of marine organisms, including elasmobranch and teleost fish, both in nature and controlled environments where monitoring marine specimens' health is mandatory. Traditional methods involving specimen capture and handling are invasive, stressful, and disruptive. Some techniques like underwater visual census or laser photogrammetry have been used for noninvasive data collection, but they have limitations and biases. The application of stereo-video photogrammetry through the use of diver-operated stereo-video systems (stereo-DOV) is a noninvasive method that overcomes these challenges, providing highly accurate measurements. It has become popular for species monitoring, studying anthropogenic impacts, and assessing length distributions. However, this technique is still uncommon and barely reported in aquarium settings. This study describes an innovative pilot study targeting multiple species carried out in a Public Aquarium, using a low-cost house-made device. The results revealed that measuring more than 100 individuals in approximately 1 day's work is possible. Total and fork lengths were estimated using specific software for 31 teleost and 16 elasmobranch species and compared with real measurements for the available species. Despite technical limitations that must be reviewed for application in future studies that resulted in high root mean square (RMS) values (> 20 mm), differences between methodological approaches revealed a minimal discrepancy (1.37%-5% in large sharks and rays and 1.8%-5.5% in teleost fish). This technique has time and cost requirements, but might represent a major advance in husbandry and in the contribution to conservation that ex situ studies can provide.

Contingent negative variation for assessment of neurological deficits in children with hypothyroidism

Objectives: Hypothyroidism is one of the most common endocrine disorders. Its effect on the central nervous system is more pronounced, especially in the pediatric age group. Despite receiving adequate thyroid hormone replacement therapy, several patients continue to suffer from neurological impairments including cognitive dysfunction. Contingent negative variation (CNV) is an event-related potential (ERP) that is considered as an indicator of cognitive function. In this study, CNV was recorded in children with hypothyroidism. To the best of our knowledge to date, there have been no studies of CNV in hypothyroidism. Materials and Methods: This prospective study included 52 children between 8 and 15 years of age who were newly diagnosed with hypothyroidism. Diagnosis of hypothyroidism was based on laboratory thyroid function tests. CNV ERP was recorded in the enrolled children at the time of diagnosis, 1-month, and 6-month follow-up. Initial CNV (iCNV) and late CNV (lCNV) amplitudes and latencies were recorded each time. Results: Although the amplitudes of iCNV and lCNV appeared to increase during follow-ups, the changes were not statistically significant (P > 0.05). Similarly, there appeared to be a modest reduction in latencies of iCNV or lCNV during follow-up; however, these changes were not statistically significant either. Conclusion: Our study did not show any significant changes in neurophysiological parameters. This may be attributed to a shorter time period of follow-up of six months and a smaller sample size. There is a possibility that CNV parameters may show more pronounced changes after a prolonged duration of treatment.

An Assessment of an Inpatient Robotic Nurse Assistant: A Mixed-Method Study

The worldwide nursing shortage has led to the exploration of using robotics to support care delivery and reduce nurses’ workload. In this observational, mixed-method study, we examined the implementation of a robotic nurse assistant (RNA) in a hospital ward to support vital signs measurements, medication, and item delivery. Human–robot interaction was assessed in four domains: usability, social acceptance, user experience, and its societal impact. Patients in a general medicine ward were recruited to participate in a one-time trial with the RNA and a post-trial 75-question survey. Patients’ interactions with the RNA were video recorded for analysis including patients’ behaviours, facial emotions, and visual attention. Focus group discussions with nurses elicited their perceptions of working with the RNA, areas for improvement, and scalability. Sixty-seven patients aged 21–79 participated in the trial. Eight in 10 patients reported positive interactions with the RNA. When the RNA did not perform to expectations, only 25% of patients attributed fault to the RNA. Video analysis showed patients at ease interacting with the RNA despite some technical problems. Nurses saw potential for the RNA taking over routine tasks. However, they were sceptical of real time savings and were concerned with the RNA’s ability to work well with older patients. Patients and nurses suggested greater interactivity between RNA and patients. Future studies should examine potential timesaving and whether time saved translated to nurses performing higher value clinical tasks. The utility of improved RNA’s social capability in a hospital setting should be explored as well.

Efficacy and Safety of Sarpogrelate on Symptom Improvement in Patients with Peripheral Arterial Disease (PAD) and/or Being at Risk of PAD: A Single Arm, Multi-Centered, Open-Label Trial.

To assess the efficacy and safety of sarpogrelate (300 mg) for symptom improvement in patients having peripheral arterial disease (PAD) and/or being at risk of PAD in clinical practice using the Peripheral Artery Questionnaire (PAQ). Symptomatic changes with antiplatelets in patients with PAD are limited. To determine the effect and safety of sarpogrelate on the PAQ at 24 weeks from baseline. A total of 1003 patients having PAD and/or being at risk of PAD from 17 tertiary hospitals in South Korea who were treated with sarpogrelate, were enrolled in this study. PAQs were collected at baseline and at 12 and 24 weeks, together with physical examination and vital signs measurements. Lifestyle pattern was also investigated. The average PAQ Summary Score in the efficacy evaluation analysis group significantly improved from 62.9 ± 23.7 at baseline to 68.9 ± 21.7 at 24 weeks (P<0.0001). Physical limitation items significantly improved from 69.5 ± 30.0 at baseline to 72.9 ± 28.3 after 24 weeks (P=0.0011). Symptom stability also significantly improved from 52.1 ± 21.6 at baseline to 63.6 ± 22.9 after 24 weeks (P<0.0001). Symptoms, treatment satisfaction, quality of life, and social limitation domains all improved after treatment. A total of 201 patients reported adverse events (20.0%), not directly associated with treatment. Treatment with 300 mg (orally) of sarpogrelate demonstrated statistically significant improvements in all domains and for the summary score of the PAQ at 24 weeks, it gave good results in terms of safety. Sarpogrelate may be helpful in reducing symptoms related to PAD.

Early Hospital Discharge on Day Two Post-Robotic Lobectomy with Telehealth Home Monitoring.

Background: Despite the implementation of enhanced recovery programs, the reported average postoperative length of stay after robotic lobectomy remains as 4 days. In this prospective study, we present the outcomes of early discharge (on day 2) with telehealth home monitoring device after robotic lobectomy for lung cancer in selected patients. Methods: All patients with a caregiver were discharged on postoperative day 2 (POD 2) with a telemonitoring device provided they met the specific discharge criteria. Inclusion criteria: <75 years old, stage I-II NSCLC, with caregiver, ECOG 0-2, scheduled for lobectomy, logistic proximity to hospital (<60 km); intra-postoperative exclusion criteria: conversion to open surgery, early complications needing hospital monitoring or redo-operation, difficult pain management, <92 HbO2% saturation on room air or need for O2 supplementation, altered vital or laboratory parameters. Teleconsultations were scheduled as follows: the first one in afternoon of POD2, two on POD3, then once a day until chest tube removal. After discharge, patients recorded their vital signs at least four times a day using the device, which allowed two surgeons to monitor them via a mobile application. In the event of sudden changes in vital signs or the occurrence of adverse events, patients had access to a direct phone line and a dedicated re-hospitalization pathway. The primary outcome was safety, assessed by the occurrence of post-discharge complications or readmissions, as well as feasibility. Secondary outcomes: comparison of safety profile with a matched control group in which the standard of care and the evaluation of resource optimization were maintained and economic evaluation. Results: Between July 2022 and February 2024, 48 patients were enrolled in the present study. Six patients (12.5%) dropped out due to unsatisfied discharge criteria on POD2. Exclusion causes were: significant air leaks (n:2) requiring monitoring and the use of suction device, uncontrolled pain (n:2), atrial fibrillation, and occurrence of cerebral ischemia (n:1 each). The adherence rate to vital signs monitoring by patients was 100%. A mean number of four measurements per day was performed by each patient. During telehealth home monitoring, a total of 71/2163 (1.4%) vital sign measurements violated the established acceptable threshold in 22 (52%) patients. All critical violations were managed at home. During the surveillance period (defined as the time from POD 2 to the day of chest tube removal), a persistent air leak was recorded in one patient requiring readmission to the hospital (on POD 13) and re-intervention with placement of a second thoracic drainage due to unsatisfactory lung expansion. No other postoperative complication occurred nor was there any readmission needed. Compared to the control group, the discharge gain was 2.5 days, with an economic benefit of 528 €/day (55.440 € on the total enrolled population). Conclusions: Our results confirm that the adoption of telehealth home monitoring is feasible and allows a safe discharge on postoperative day two after robotic surgery for stage I-II NSCLC in selected patients. A potential economic benefit (141 days of hospitalizations avoided) for the healthcare system could result from the adoption of this protocol.

Rhythm-based Temporal Expectations: Unique Contributions of Predictability and Periodicity.

Anticipating events and focusing attention accordingly are crucial for navigating our dynamic environment. Rhythmic patterns of sensory input offer valuable cues for temporal expectations and facilitate perceptual processing. Rhythm-based temporal expectations may rely on oscillatory entrainment, where neural activity and perceptual sensitivity synchronize with periodic stimuli. However, whether entrainment models can account for aperiodic predictable rhythms remains unclear. Our study aimed to delineate the distinct roles of predictability and periodicity in rhythm-based expectations. Participants performed a pitch-identification task preceded by periodic predictable, aperiodic predictable, or aperiodic unpredictable temporal sequences. By manipulating the temporal position of the target sound, we observed how auditory perceptual performance was modulated by the target position's relative phase relationship to the preceding sequences. Results revealed a significant performance advantage for predictable sequences, both periodic and aperiodic, compared with unpredictable ones. However, only the periodic sequence induced an entrained modulation pattern, with performance peaking in synchrony with the inherent sequence continuation. Event-related brain potentials corroborated these findings. The target-evoked P3b, possibly a neural marker of attention allocation, mirrored the behavioral performance patterns. This supports our hypothesis that temporal attention guided by rhythm-based expectations modulates perceptual performance. Furthermore, the predictive sequences were associated with enhanced target-preceding negativity (akin to the contingent negative variation), indicating enhanced target preparation. The periodic-specific modulation likely reflects more precise temporal expectations, potentially involving neural entrainment and/or more focused attention. Our findings suggest that predictability and periodicity influence perception through distinct mechanisms.

Comparing peripheral limb and forehead vital sign monitoring in newborn infants at birth.

To study the feasibility of measuring heart rate (HR) and oxygen saturation (SpO2) on the forehead, during newborn transition at birth, and to compare these measurements with those obtained from the wrist. Vital signs were measured and compared between forehead-mounted reflectance (remittance) photoplethysmography sensor (fhPPG) and a wrist-mounted pulse oximeter sensor (wrPO), from 20 enrolled term newborns born via elective caesarean section, during the first 10 min of life. From the datasets available (n = 13), the median (IQR) sensor placement times for fhPPG, ECG and wrPO were 129 (70) s, 143 (68) s, and 159 (76) s, respectively, with data recorded for up to 10 min after birth. The success rate (percentage of total possible HR values reported once sited) of fhPPG (median = 100%) was higher compared to wrPO (median = 69%) during the first 6 min of life (P < 0.005). Both devices exhibited good HR agreement with ECG, achieving >95% agreement by 3 (fhPPG) and 4 (wrPO) min. SpO2 for fhPPG correlated with wrPO (r = 0.88), but there were significant differences in SpO2 between the two devices between 3 and 8 min (P < 0.005), with less variance observed with fhPPG SpO2. In the period of newborn transition at birth in healthy term infants, forehead measurement of vital signs was feasible and exhibited greater HR accuracy and higher estimated SpO2 values compared to wrist-sited pulse oximetry. Further investigation of forehead monitoring based on the potential benefits over peripheral monitoring is warranted. This study demonstrates the feasibility of continuously monitoring heart rate and oxygen saturation from an infant's forehead in the delivery room immediately after birth. Significantly higher SpO2 measurements were observed from the forehead than the wrist during the transition from foetal to newborn life. Continuous monitoring of vital signs from the forehead could become a valuable tool to improve the delivery of optimal care provided for newborns at birth.

Automated Unmanned Aerial System for Camera-Based Semi-Automatic Triage Categorization in Mass Casualty Incidents

Using drones to obtain vital signs during mass-casualty incidents can be extremely helpful for first responders. Thanks to technological advancements, vital parameters can now be remotely assessed rapidly and robustly. This motivates the development of an automated unmanned aerial system (UAS) for patient triage, combining methods for the automated detection of respiratory-related movements and automatic classification of body movements and body poses with an already published algorithm for drone-based heart rate estimation. A novel UAS-based triage algorithm using UAS-assessed vital parameters is proposed alongside a robust UAS-based respiratory rate assessment and pose classification algorithm. A pilot concept study involving 15 subjects and 30 vital sign measurements under outdoor conditions shows that with our approach, an overall triage classification accuracy of 89% and an F1 score of 0.94 can be achieved, demonstrating its basic feasibility.