Thermal Imaging Camera Research Articles

Design and development of additivemanufactured multi-channel brachytherapy applicators for cancer treatment

Additive manufacturing (AM) is emerging as an effective manufacturing technology that benefits the medical field with its ease of quickly realizing complex designs. Brachytherapy is a process to cure cancer patients through a high dose rate of gamma radiation. This work aimed at AM-based development of multi-channel vaginal and penile brachytherapy applicators for selectively treating cancer cells in a direction sideways to the applicator rather than the uniform radiation dose possible around the conventional applicator used in cancer treatment. An analytical model was proposed to predict the maximum surface temperature on applicators during Ir-192 source radiation. Also, the predicted values of multi-physics-based finite element method simulation were experimentally validated using a thermal imaging camera. Thermal imaging is a non-contact measurement that is found superior to the brachytherapy scale to position radioactive sources inside the applicator. Experimentally examined multi-channel applicator shows dosimetry advantage in effective radiation control and shows promise of curing cancerous cells with minimal effects on normal cells.

Thermal Image Tracking for Search and Rescue Missions with a Drone

Infrared thermal imaging is useful for human body recognition for search and rescue (SAR) missions. This paper discusses thermal object tracking for SAR missions with a drone. The entire process consists of object detection and multiple-target tracking. The You-Only-Look-Once (YOLO) detection model is utilized to detect people in thermal videos. Multiple-target tracking is performed via track initialization, maintenance, and termination. Position measurements in two consecutive frames initialize the track. Tracks are maintained using a Kalman filter. A bounding box gating rule is proposed for the measurement-to-track association. This proposed rule is combined with the statistically nearest neighbor association rule to assign measurements to tracks. The track-to-track association selects the fittest track for a track and fuses them. In the experiments, three videos of three hikers simulating being lost in the mountains were captured using a thermal imaging camera on a drone. Capturing was assumed under difficult conditions; the objects are close or occluded, and the drone flies arbitrarily in horizontal and vertical directions. Robust tracking results were obtained in terms of average total track life and average track purity, whereas the average mean track life was shortened in harsh searching environments.

TSA and FEM Analysis Applied to CAD/CAM Titanium All-on-Four Prosthesis

Patient with fully edentulous maxillaries often suffer of several disease as an alteration of facial appearance, difficulties in eating, speech, and chews. Fixed and removable prosthesis can be a solution to rehabilitate this issue. The All-on-Four protocol is one of the possible treatment modalities for implant-supported prosthetics. It consists of placing four implants in an intermorainal position, two perpendicular to the occlusal plane and two tilted distally at a 45° angle. This paper aims to assess the stress distribution on an All-on-Four titanium prosthesis by means of a Thermoelastic Stress Analysis (TSA). This full-field non-contact measurement technique allows, through a thermal imaging camera, to observe how the surface temperature of an object changes under the effect of cyclic load. The principle on which thermoelastic analysis is based is the existence of a relationship between deformation, hence applied stress, and temperature change, called the thermoelastic effect. To perform the tests, the prosthesis was fixed to a resin jaw cast that has similar characteristics to the human bone, so that the same damping that would be present under normal working conditions could be accounted for. The distal artificial molar tooth was kept in contact to a narrow screw, which was attached to a Medium-Force (M-Series) Air-Cooled Shakers made by Santek. This shaker generates a sinusoidal load of 800N with a load cell at 10 Hz frequency, which can maintain the temperature variation of the prosthesis constant. A pre-load was applied before starting the tests. To see the change in temperature a Flir A6751SC thermal camera was used, and videos were acquired with a frame rate of 125 Hz and a resolution of 640x512 pixels. From the experimental TSA tests, the trend of the experimental stress concentration on the titanium specimen was detected. The outcomes of the experimental tests were compared to a 3D prosthesis model by Finite Element Analysis (FEM).

PCMs with perlite aggregate for snow melting applications

Phase Change Materials are used to provide a more stable micro-climate around the applied materials or surfaces. Using PCMs for snow melting applications is a very innovative and technical solution. These solutions are especially valuable in situations where flight delays can cause high costs when airport runways are covered with snow. In these applications, hot air is accumulated in PCMs and extracted during cold times. For this purpose, PCMs are incorporated into the pavements in different ways. One of the effective ways is to incorporate PCMs into lightweight aggregates. Perlite is a widely used lightweight aggregate that is also used with PCMs in building applications for insulation purposes. In this study, the performances of 3 different PCMs that were suitable for low temperature applications were investigated. These PCMs were incorporated into the raw and expanded perlite then a totally of 12 cement based composite mixtures including the reference mixture were produced. Thermal performances of the samples were monitored by both thermocouple measurements and thermal camera images. In addition to the thermal performances, the physical and mechanical performances of the composites were determined by the standard test methods. Results revealed that although using lightweight aggregates made an adverse effect on the mechanical values (these reductions, which were up to 87% when expanded perlite was used, were limited to 5.2% when raw perlite was used), they exhibited great potential for snow melting applications by keeping the surface warmer through more time.

A multispectral vision-based machine learning framework for non-contact vehicle weigh-in-motion

The present study proposes an automated non-contact weigh-in-motion framework using multispectral vision and machine learning method, which provides an all-weather monitoring of heavy vehicles on transportation infrastructures. Multispectral based computer vision techniques consist of two steps, one is acquiring the tire deformation parameters from thermal imaging camera and the latter is obtaining the sidewall characters from the ordinary one. A novel edge detection algorithm is designed for thermal image-based tire deformation estimation. A general recognition model with well-established tire characters database for universal tire sidewall markings, such as non-standard fonts or non-text characters, curved markings or inverted markings, and is developed based on Efficient neural network (E-NET) and YOLOV5S methods. A machine learning-based model for estimating the various vehicles tire-roadway contact forces is established based on eXtreme Gradient Boosting (XGBoost). A database of different vehicles’ tires with a total of 1127 samples from 19 types of tires and 648 of laboratory datasets from common vehicles are collected to train the model. The Bayesian optimization is employed to capture the optimal model, and a hybrid training strategy including biased data is applied to update the model. An importance analysis for 11 features is conducted to validate the performance proposed model. The accuracy, feasibility, and effectiveness of the proposed method is carefully investigated by field experiments for trucks and sport utility vehicles under static and low-speed drive. A maximum of 5 % difference is witnessed by comparing the results with that of the traditional WIM system. The present method presents a cost-effective means with no sensors on structures for vehicle weighting, that demonstrates a great potential to implement in toll station, highway infrastructures as well as health monitoring of civil engineering fields.

A Study on Defect Detection of Dissimilar Joints in Cu-STS Tubes Using Infrared Thermal Imaging of Induction Heating Brazing

We proposed a novel detection method for identifying joint defects in the brazing process between copper tubes and stainless steel using a convolutional neural network (CNN) model. The brazing joints were created using high-frequency induction heating equipment, and infrared thermal imaging cameras were employed to capture the thermal data generated during the jointing process. The experiments involved 15.88 mm diameter copper tubes commonly used in plate heat exchangers, stainless-steel tubes, and filler metal containing 20% Ag. The thermal data were obtained with a resolution of 80 × 80 pixels per frame, resulting in 4796 normal joint data and 5437 defective joint data collected over 100 high-frequency induction-heating brazing experiments. A total of 10,233 thermal imaging data were categorized into 6548 training data, 1638 validation data, and 2047 test data for the development of the predictive model. We designed CNN models with varying hyperparameters, specifically the number of kernel filters and nodes, to evaluate their impact on detection performance. A comparative analysis revealed that a CNN model structure, exhibiting 98.53% accuracy and 99.82% recall on test data, was the most effective. The selected CNN-based defect prediction model demonstrated the potential of using CNN models to discern joint defects in tube configurations that are challenging to identify visually. This study opens avenues for applying CNN-based models for detecting imperfections in complex tube structures.

The practical use of UAV systems in mine excavations and inspection works at LW “Bogdanka” S.A.

This publication presents the application of the Elios 3 caged drone in underground geodetic measurements at the LW “Bogdanka” coal mine. Traditional surveying methods are increasingly being replaced by modern technologies such as laser scanners and unmanned aerial vehicles (UAV). LW “Bogdanka” mine has wide experience in the use of drones in surface surveys, which has enabled the implementation of these devices also in underground mine excavations. The Elios 3 aircraft, equipped with a 4K camera, thermal imaging camera, distance sensor and LiDAR technology, provides precise scanning of the environment and creating high-density point clouds. The SLAM stabilization system ensures the accuracy of measurements even in difficult conditions. This article focuses on the practical applications of the Elios 3 drone in the mine, such as inspections of coal storage tanks, assessment of the technical condition of dewatering roadways and measurements in hard-to-reach areas. The use of UAV significantly improves operational efficiency, reduces survey time and minimizes risks to employees. Thanks to LiDAR technology, Elios 3 accurately represents the details of the object being measured, which is crucial for maintaining and improving the mine’s infrastructure. The introduction of a drone for surveying at the LW “Bogdanka” mine brings numerous benefits, including increased workplace safety and advanced measurement capabilities in hard-to-reach and dangerous areas.

Синтез поляризационных светоделителей для дальнего инфракрасного диапазона спектра

The technique and results of the synthesis of polarization beam splitters for the long-wavelength infrared region of the spectrum of 8–14 microns are presented. In this range, bodies with temperatures around zero degrees Celsius begin to emit. In addition, this radiation has a low attenuation in a relatively humid or aerosol-saturated atmosphere. Therefore, it is widely used in night vision devices, rangefinders and thermal imaging cameras, including mobile systems with a variable angle of the optical axis relative to the angle of arrival of the incident electromagnetic wave. In systems with active illumination, polarized radiation and beam splitters are used to reduce the effect of backscattering interference. A review of patents and literature showed the absence of finished products for the considered wavelength range. In this paper, original designs of polarization beam splitters are proposed and their spectral optical characteristics are obtained.

Correlating Light Intensity with Body Heat Changes: Implications for Screen Time and Well-being

This study investigates the correlation between light intensity and body heat changes during screen time activities, aiming to uncover potential implications for well-being. With the pervasive use of screens in modern society, understanding how light emitted from devices affects physiological responses is crucial. The research employs a multidisciplinary approach, combining thermal imaging techniques with light intensity measurements to explore the intricate relationship between these variables. The methodology involves recruiting participants to engage in screen-based activities, such as watching television or using laptops, under controlled conditions. Thermal imaging cameras are utilized to monitor changes in body heat, providing real-time data on thermal responses. Concurrently, light intensity meters measure the brightness emitted by the screens, allowing for the quantification of light exposure levels. Data analysis encompasses statistical techniques to identify correlations between light intensity and body heat changes. Factors such as screen type, content, and viewing distance are considered to elucidate potential moderating variables. The findings aim to provide insights into how different levels of light intensity impact physiological well-being during screen time activities. Implications of the study extend to various domains, including ergonomic design, health recommendations, and screen usage guidelines. Understanding the interplay between light exposure and body heat regulation can inform the development of anti-screen technologies or interventions aimed at mitigating potential negative effects of prolonged screen time on health and well-being. Overall, this research contributes to a comprehensive understanding of the complex relationship between screen-based activities, light exposure, and human physiology

The effects of foam rolling applied to delayed-onset muscle soreness of the quadriceps femoris after Tabata training

Abstract Study aim The aim of the present study was to assess the effect of roll-over self-massage on the occurrence of symptoms of delayed post-workout muscle soreness after Tabata training. Material and methods The research involved 81 people, randomly divided into two groups. A series of three roller self-massages was applied by members of Group 1 (n = 33). Persons assigned to control Group 2 (n = 48) did not undergo any procedures supporting the post-workout recovery. All participants performed training of lower limb muscles, according to the Tabata protocol. Then the frontal surface of the thighs was tested with a thermal imaging camera. The intensity of pain was measured (by the Visual Analogue Scale – VAS) after 24, 48 and 72 hours. Results The highest average pain level in Group 1 was recorded at the second measurement, i.e. 24 hours after training, and in Group 2 after 48 h. In the study group, a significantly lower result was observed on each successive day. The differences between the groups in pain levels measured 48 and 72 hours after exercise were statistically significant (p < 0.05). Conclusion Self-massage with a roller accelerated muscle regeneration. It can therefore be an effective procedure to support post-workout recovery, especially for athletes during the start period.

Stable Arterial Perforators Mapping in Lower Leg Using Color-Coded Doppler Sonography, Acoustic Doppler, and Thermal Imaging Camera in Patients Undergoing Digital Subtraction Angiography

Abstract Background Chronic defects in the lower leg present significant challenges in plastic surgery due to their diverse etiologies and association with impaired peripheral circulation. This study describes the localization of stable perforators and assesses their changing velocities after digital subtraction angiography (DSA) and alterations of flow characteristics. Methods Ten patients with lower extremity defects requiring DSA had undergone examinations by using standard methods. The localization of 40 stable perforators originating from the anterior tibial artery, posterior tibial artery, fibular artery, and medial sural artery was performed before and after angiography. Where stenoses or occlusions were observed, percutaneous transluminal angioplasty (PTA) was conducted, and velocity changes following reperfusion were measured. Results Angiographic abnormalities were observed in all of patients, thus necessitating PTA interventions. Prior to PTA, handheld acoustic Dopplers detected 37 out of 40 perforators (90%), whereas color-coded sonography detected 35 out of 40 perforators (87.5%). After PTA, these numbers increased to 38 out of 40 (95%) and 37 out of 40 (92.5%), respectively. The diameter of the perforators ranged between 1.14 and 1.16 mm. The mean flow characteristics included the peak systolic velocities (PSV) of 21.9 and 27.2, end-diastolic velocities (EDV) of 9.4 and 11.4, and resistance indexes (RI) of 0.63 and 0.71, respectively. In the postintervention period, 16 microvessels exhibited enlarged lumen diameters ranging from 1 to 3 mm, resulting in increased perfusion values for PSV in 85.2% (21.9/27.2) and EDV in 88.2% (9.4/11.4) of the patients. The RI increased from 0.63 to 0.71. However, two perforators showed decreases in flow velocity after PTA. Conclusion In most patients with chronic lower leg wounds and other comorbidities, adequate perforators for reconstruction can be identified by using conventional methods. PTA interventions positively impact blood flow in perforators, although they are not necessarily required prior to reconstruction.

Analyzing Thermal Images to Evaluate Thermal Protection in Residential Structures: Lessons from Russian Practices

Building thermography is a non-destructive and effective method for diagnosing the thermal insulation of buildings with various purposes. Regardless of the specifics of conducting thermographic surveys, the obtained thermal images (thermograms) can be analyzed both qualitatively and quantitatively. The first method of analyzing thermal images is implemented using specialized software typically provided with the thermal imaging camera. The second method is carried out based on the results of thermographic surveys following the methodologies regulated by the country’s normative documents. Using the example of thermographic inspection of enclosing structures in a multi-story residential building constructed from reinforced concrete panels, a qualitative assessment of thermal images was conducted to identify potential thermal defects. Thermal bridges were detected in the area of vertical joints of panel plates, and excessive heat losses were identified in the region where the heating device niche is located.Quantitative assessment of thermal images revealed that the thermal resistance in the temperature anomaly area is nearly twice as low as the thermal resistance in the baseline section of the thermogram. One of the variations for evaluating the error of indirect measurements of relative thermal resistance is presented, taking into account the range of measuring instruments used. Verification of the thermal resistance of the enclosing structure of the external wall of the residential building was conducted to ensure compliance with sanitary and hygienic requirements. According to the results of in-situ measurements, it was determined that the temperature on the inner surface of the enclosure was lower than the specified value.

Thermal imaging and computer vision technologies for the enhancement of pig husbandry: a review.

Pig farming, a vital industry, necessitates proactive measures for early disease detection and crush symptom monitoring to ensure optimum pig health and safety. This review explores advanced thermal sensing technologies and computer vision-based thermal imaging techniques employed for pig disease and piglet crush symptom monitoring on pig farms. Infrared thermography (IRT) is a non-invasive and efficient technology for measuring pig body temperature, providing advantages such as non-destructive, long-distance, and high-sensitivity measurements. Unlike traditional methods, IRT offers a quick and labor-saving approach to acquiring physiological data impacted by environmental temperature, crucial for understanding pig body physiology and metabolism. IRT aids in early disease detection, respiratory health monitoring, and evaluating vaccination effectiveness. Challenges include body surface emissivity variations affecting measurement accuracy. Thermal imaging and deep learning algorithms are used for pig behavior recognition, with the dorsal plane effective for stress detection. Remote health monitoring through thermal imaging, deep learning, and wearable devices facilitates non-invasive assessment of pig health, minimizing medication use. Integration of advanced sensors, thermal imaging, and deep learning shows potential for disease detection and improvement in pig farming, but challenges and ethical considerations must be addressed for successful implementation. This review summarizes the state-of-the-art technologies used in the pig farming industry, including computer vision algorithms such as object detection, image segmentation, and deep learning techniques. It also discusses the benefits and limitations of IRT technology, providing an overview of the current research field. This study provides valuable insights for researchers and farmers regarding IRT application in pig production, highlighting notable approaches and the latest research findings in this field.

EVALUAREA COMPORTARII TERMICE A PLANTELOR IN MICROSERA CU SENZORI DE IMAGINE MICROBOLOMETRICI

In this research, the data from temperature measurements obtained with the InfiRay T2S+ device, an infrared thermal imaging camera have been checked to monitor plant thermal behaviour. Plant leaf temperature is a parameter frequently used as representative for stomatal conductance, as stomatal confinement results in attenuated transpiration, and consequently leads to increased plant temperature. Also, to identify the stress of the plant, indices of thermal and modified stress have been calculated. The results obtained show that the Kalanchoe blossfeldiana species chosen for this study, when exposed to extreme values of temperature or water requirements, presented significant changes in the infrared electromagnetic wave spectra.

Implementation of Thermal Camera for Human Stress Detection: A Review

Stress has become a major problem that people face today. The high level of competition and environmental demands make people more susceptible to stress. Stress can interfere with a person's ability to work effectively. If left unchecked for a long time, stress can cause various dangerous diseases such as hypertension, heart problems, and others that can lead to death. Research has been conducted for a long time to detect stress. Various technologies have been used to detect and anticipate stress that occurs in humans. One promising technology for detecting stress is the use of thermal cameras. Thermal cameras have several advantages: being non-contact and non-invasive, quick, easy to use, and cost-effective. In general, the architecture of the stress detection system using a thermal camera consists of several stages, including image acquisition, pre-processing, ROI tracking and selection, feature extraction, and statistical analysis or classification. This paper aims to review the use of thermal cameras in detecting stress in humans. This paper also seeks to answer the research question of what analysis can be done to improve stress detection accuracy using thermal camera images. Research shows that ROI selection must be carefully considered to obtain good accuracy. Combining thermal images with other data can improve accuracy in stress detection. Machine learning in classification provides many benefits in recognizing patterns but is highly influenced by the number of datasets used.

Study of local cryotherapy methods for the knee joint

BACKGROUND: A promising method for treating musculoskeletal disorders to alleviate symptoms and promote recovery is local cryotherapy (LC). Proper control and regulation of the procedure enable safe interventions with predictable therapeutic effects for various locations.
 AIMS: This study aims to identify measurable physical criteria for the effectiveness of the LC procedure and the dosing characteristics and to compare and analyze the capabilities of various methods.
 MATERIALS AND METHODS: The experiment involved 16 volunteers who were randomized into 4 groups. The first and second groups underwent LC using ice bags for 20 min with a cooling agent consisting of an ice and water mixture and a 23.1% sodium chloride solution. The third and fourth groups underwent nitrogen (for 3 min) and air (for 20 min) LC, respectively. During the experiment, the skin temperature was measured using a temperature sensor and thermal imaging camera.
 RESULTS: The lowest value of the minimum final temperature after cooling was recorded with liquid nitrogen vapor as equal to 0.88 ± 1.75 ℃. The minimum area of the work zone was 33.7 ± 7.1 cm2. When cooled with an ice bag with water and ice, the most uniform distribution of the temperature field among the investigated cases was observed, with the highest values of the minimum final temperature (i.e., 6.43 ± 0.90 ℃) and minimum area of the work zone (i.e., 135.2 ± 34.6 cm2) among the investigated methods.
 CONCLUSIONS: The main physical criteria for the effectiveness of LC are identified as temperature and the dynamics of its changes on the surface of the object of exposure. A dosing characteristic, i.e., the area of the work zone, was proposed and evaluated. In the area of the work zone, the target temperature is achieved. Based on the main physical criteria, the three main cooling methods are compared. These methods achieve the target result in different ways. The easiest to use and prepare are contact methods using ice bags. Air cooling in the investigated mode is more easily tolerated by the subjects, and in terms of the physical criteria, it is equivalent to contact methods. Cooling with nitrogen vapor leads to the fastest achievement of the target temperature on the surface and the least cooling of internal tissues; therefore, cooling deep into the biological tissue is limited.

Temperature rise in photopolymerized adhesively-bonded resin composite: A thermography study

ObjectivesTo assess visually and quantitatively the contributions of the adhesive layer photopolymerization and the subsequent resin composite increment to spatio-temporal maps of temperature at five different cavity locations, subjected to two irradiance curing protocols: standard and ultra-high. MethodsCaries-free molars were used to obtain 40, 2 mm thick dentin slices, randomly assigned to groups (n = 5). These slices were incorporated within 3D-printed model cavites, 4 mm deep, restored with Adhese® Universal bonding agent and 2 mm thick Tetric® Powerfill resin composite, and photocured sequentially, as follows: G1: control-empty cavity; G2: adhesive layer; G3 composite layer with no adhesive; and G4 composite layer with adhesive. The main four groups were subdivided based on two curing protocols, exposed either to standard 10 s (1.2 W/cm2) or Ultra high 3 s (3 W/cm2) irradiance modes using a Bluephase PowerCure LCU. Temperature maps were obtained, via a thermal imaging camera, and numerically analyzed at 5 locations. The data were analyzed using two-way ANOVA followed by multiple one-way ANOVA, independent t-tests and Tukey post-hoc tests (α = 0.05). Tmax, ΔT, Tint (integrated area under the curve) and time-to-reach-maximum-temperature were evaluated. ResultsTwo-way ANOVA showed that there was no significant interaction between light-curing time and location on the measured parameters (p > 0.05), except for the time-to-reach-maximum-temperature (p < 0.05). Curing the adhesive layer alone with the 10 s protocol resulted in a significantly increased pulpal roof temperature compared to 3 s cure (p < 0.05). Independent T-tests between G3 and G4, between 3 s and 10 s, confirmed that the adhesive agent caused no significant increases (p > 0.05) on the measured parameters. The ultra-high light-curing protocol significantly increased ΔT in composite compared to 10 s curing (p < 0.05). SignificanceWhen the adhesive layer was photocured alone in a cavity, with a 2 mm thick dentin floor, the exothermal release of energy resulted in higher temperatures with a 10 s curing protocol, compared to a 3 s high irradiance. But when subsequently photocuring a 2 mm layer of composite, the resultant temperatures generated at pulpal roof location from the two curing protocols were similar and therefore there was no increased hazard to the dental pulp from the immediately prior adhesive photopolymerization, cured via the ultra-high irradiation protocol.

SUITABILITY ASSESSMENT OF DIFFERENT SENSORS TO DETECT HIDDEN INSTALLATIONS FOR AS-BUILT BIM

Abstract. Knowledge on the utilities hidden in the wall, e.g., electric lines or water pipes, is indispensable for work safety and valuable for planning. Since most of the existing building stock originates from the pre-digital era, no models as understood for Building Information Modeling (BIM) exist. To generate these models often labor-intensive procedures are necessary; however, recent research has dealt with the efficient generation and verification of a building’s electric network. In this context, a reliable measurement method is a necessity. In this paper we test different measurement techniques, such as point-wise measurements with hand-held devices or area-based techniques utilizing thermal imaging. For this purpose, we designed and built a simulation environment that allows various parameters to be manipulated under controlled conditions. In this scenario the low-cost handheld devices show promising results, with a precision between 92% and 100% and a recall between 89% and 100%. The expensive thermal imaging camera is also able to detect electric lines and pipes if there is enough power on the line or if the temperature of the water in the pipe and the environment’s temperature are sufficiently different. Nevertheless, while point-wise measurements can directly yield results, the thermal camera requires post-processing in specific analysis software. The results reinforce the idea of using reasoning methods in both the do-it-yourself and commercial sector, to rapidly gather information about hidden installations in a building without prior technical knowledge. This paves the way for, e.g., exploring the possibilities of an implementation and presentation in augmented reality (AR).

Ocular Surface Temperature Profile of Eyes with Retinal Vein Occlusion

Retinal vein occlusion (RVO) results in ischemia followed by an inflammatory response. Both processes affect tissue temperature in opposite directions. Here, we evaluate the effect of RVO on the ocular surface temperature (OST) profile. Subjects with RVO were prospectively recruited. Healthy subjects without any ocular disease served as controls. The OST was determined using the Therm-App thermal imaging camera, and image processing software was employed to compute the mean temperature values of the medial canthus, lateral canthus, and cornea. We obtained thermographic images from 30 RVO subjects (30 eyes) and 148 controls (148 eyes). A univariate analysis found that eyes with RVO had significantly elevated OSTs compared to the controls (mean difference of 0.6 ± 0.3 Celsius, p &lt; 0.05). However, this distinction between the groups lost statistical significance upon adjusting for possible confounders, including patient and environmental factors. These findings were confirmed with a post hoc case–control matched comparison. In conclusion, RVO does not seem to affect the OST. This might be due to the balance between inflammatory thermogenesis and heat constriction from ischemia in RVO. It is also possible that, in our cohort, the RVO pathophysiological processes involved were localized and did not extend to the anterior segment. Patient and environmental factors must be considered when interpreting the OST.

Using infrared cameras in drones to detect bleeding events

BackgroundHemorrhage is one of the main causes of death in trauma. Critical bleeding in patients needs to be detected as soon as possible to save the patient. Drones are gaining increasing importance in emergency services and can support rescue forces in accident scenarios such as a mass casualty incident.MethodsIn this study, a simulated pelvic hemorrhage was detected using a drone from 7 m above the ground over a time span of 30 s.ResultsThe results allow a good detection of the pelvic hemorrhage. Nevertheless, the simulated blood cools down quickly. After 30 s, there was no significant temperature difference compared to the rest of the body. At this point, further assessment is only possible via the RGB image.ConclusionThe findings suggest that bleeding from an open and continuously bleeding wound would most likely be detectable using the drone’s thermal imaging camera, even over a longer period of time.