ABSTRACT Ensuring railway safety is a paramount concern, particularly in detecting overheated axle bearings, commonly referred to as hot boxes. In an attempt to improve upon existing operational solutions, the integration of fast infrared (IR) thermal vision technology in the wayside with computer vision has provided new insights for automatically detecting hot-bearing boxes. However, this method involves labour-intensive frame-by-frame processing that can delay critical decision-making. Instead, the present research work shifts focus to the processing of panoramic IR thermal images. Our approach begins with the study and development of a pre-processing technique that employs coarse-to-fine optical flow estimation and image stitching to generate high-resolution panoramic views from sequential IR frames. To enable automatic detection and counting of the hot box, two distinct detection approaches are implemented: custom image processing approach and deep-learning based computer vision approach. The performance of both approaches is evaluated across diverse experimental scenarios, involving both freight and passenger trains and using two distinct IR camera models, cooled and uncooled. Preliminary results are encouraging, demonstrating a clear reduction in the time required for hot box detection and counting, thereby enhancing overall train monitoring efficiency.

This study presents a disruptive, non-invasive diagnostic framework for the high-resolution electromagnetic characterization of sinusoidally modulated High Impedance Surfaces (HIS). Traditional near-field scanning techniques, while standardized, are inherently limited by probe-induced field perturbations and restricted spatial throughput. To overcome these constraints, we propose and validate the use of transient infrared (IR) thermography as a high-fidelity electromagnetic-to-thermal transducer. Operating within the 2.1-2.4 GHz spectrum, we demonstrate that the thermal signature captured on a high-emissivity Arlon substrate serves as a precise metrological proxy for Bloch mode propagation and energy localization. By synchronizing frequency-domain vector network analysis with spatial thermal mapping, we achieve a direct experimental extraction of the guided wavelength ([Formula: see text]) and the Slow-Wave Factor (SWF). Our quantitative assessment reveals a remarkable wavelength compression in the HIS prototype, reaching an SWF of 6.56 at 2.339 GHz, which correlates with a profound resonance dip of -21.09 dB. The temporal stability of the standing wave patterns observed during the transient heating phase (0-60 s) confirms the excitation of stable Bloch modes and validates the methodology's ability to decouple electromagnetic signatures from lateral heat diffusion. These results establish transient IR thermography as a robust, high-throughput alternative for validating complex periodic metasurfaces, providing a strategic pathway for the optimization of next-generation wearable shielding and electromagnetic compliance in augmented/virtual (AR/VR) technologies.

Pain assessment remains challenging for patients unable to verbally communicate, including neonates, cognitively impaired individuals, sedated patients, and those who suppress expressions due to cultural norms or stoicism. We demonstrate that integrating thermal imaging with RGB facial expression analysis provides more accurate and robust pain intensity estimation than either modality alone. Our dual-camera system records synchronized thermal and RGB video, processed through a cross-spectral attention fusion (CSAF) model with a temporal transformer for continuous 0–10 scale pain prediction. In a controlled laboratory pain induction study, 50 healthy adults (ages 21–68, 87.3 h video) underwent Cold Pressor Test and pressure algometry protocols; our system achieves MAE = 0.79, representing a 33.1% improvement over RGB-only (MAE = 1.18, p < 0.001). In a real-world clinical postoperative monitoring study, 30 surgical patients (ages 31–74, 17.7 h video) recovering from abdominal surgery were monitored; our system achieves MAE = 1.08, representing a 28.5% improvement over RGB-only (MAE = 1.51, p < 0.001). Across the combined cohort (n = 80), MAE = 0.87 (29.3% overall improvement over RGB-only). Benefits increase at higher pain intensities (38.5% at severe pain) and for challenging populations where expressions are suppressed (37.6% for low expressers). Thermal responses precede visible expressions by 1.2 ± 0.3 seconds, enabling earlier detection. This work was validated on adults only; pediatric applications require dedicated validation. Translation to clinical practice requires multi-site prospective trials, regulatory approval, and careful implementation planning.

ABSTRACT In this study, the mixtures obtained by adding the volume of 5%, 10%, 15%, 20% and 25% hydrogen to natural gas were burned in a Bunsen burner. For this purpose, a thermal camera, video camera, and gas analyzer were utilized to investigate that of changes in detail. Besides, flame sizes and areas were measured by converting flame photographs from RGB format to HSV color space using a MATLAB-based method. It was observed that as the hydrogen ratio in the mixture increased; the flame length shortened, the flame temperature increased, CO and NO2 emissions increased slightly, and NO emissions decreased. In the case of 25% hydrogen addition, an increase in flame temperature of 53°C was detected compared to 100% natural gas. Moreover, the area covered by the premixed flame decreased by 55.6% and the flame length decreased by 18 mm at the same case. The changes in flame dimensions affect the heat transfer in the combustion chamber, and the low temperatures occurring in the combustion chamber cause an increase in CO and NO2 emissions. On the other hand, when the combustion chamber diameter was reduced from 250 mm to 130 mm, it was observed that CO emissions decreased and NO2 emissions increased as the hydrogen ratio was increased from 0% to 25%. When natural gas is enriched with hydrogen and burned, the relationship between flame size and the combustion chamber has been shown to affect emissions. These experimental results have shown that matching flame and combustion chamber sizes is important for emissions when using hydrogen-enriched natural gas mixtures.

Assessing periocular inflammation is essential in several disorders, including Thyroid Eye Disease (TED). The Clinical Activity Score (CAS) is the most commonly used method to assess orbital inflammation, but is associated with significant inter-observer variability. The aim of this study was to assess the ability of Infrared Thermography (IRT) to detect orbital inflammation in TED and other orbital inflammation disorders (OOID). A retrospective study was conducted between March 2020 and November 2023. Patients were divided into four groups: active TED (CAS ≥ 3), non-active TED (CAS < 3), OOID, and healthy controls. Demographics, proptosis, and CAS were recorded. IRT was performed in 6 periocular areas, including the caruncle. Four IRT periocular patterns were characterized. Hundred and ten patients (63.64% of women) with a mean age of 59.47 (25-93) years were included. Thirteen (11.82%) patients were included in the active TED group, 44 (40.00%) in the non-active TED group, 17 (15.45%) in the OOID group and 36 (32.73%) in the control group. Non-active TED and control patients had lower mean caruncular and periocular temperatures compared to active TED and OOID patients (p < 0.05). The caruncular temperature was significantly higher in active TED patients compared to OOID patients (p < 0.05). Non-active TED and control patients mainly showed round and upper coma IRT patterns while active TED and OOID patients showed crab claw and other IRT patterns (p < 0.05). Periocular IRT measurement is a rapid, simple, non-invasive, cost-effective, and reproducible method for detecting orbital inflammation and allows differentiating active TED from OOID.

Inflammatory arthritis, especially rheumatoid arthritis (RA), imposes substantial morbidity that diminishes quality of life and escalates health care costs when left untreated. Timely diagnosis and treatment are pivotal. However, limited access to rheumatologists underscores the importance of triaging referrals based on symptom severity. We developed a protocol for using infrared thermography (IRT) to detect joint inflammation and implemented it in an academic primary care clinic as a screening tool for rheumatology referrals. We enrolled people with RA, osteoarthritis (OA), and controls to undergo joint power doppler ultrasound (PDUS) and IRT. IRT image analysis employed manual segmentation with specialized software to determine surface joint temperatures. IRT temperature cutoff points using PDUS as the gold standard for joint inflammation were established. Subsequently, we recruited people with hand or foot joint pain and fast-tracked to rheumatology those surpassing IRT cutoff points for joint inflammation. Thirty-two people with RA, 10 with OA, and 9 controls were enrolled. Most participants (86.3%) were females, and 37.3% were black. Temperature measurements showed robust interrater reliability. Cutoff points at metacarpophalangeal (MCP) (T center ≥32.93 °C, T mean ≥32.67 °C) and wrist (T center ≥33.76 °C, T mean ≥33.79 °C) joints discriminated between inflamed and noninflamed joints. Of the 20 pilot participants, N = 10 (50%) were referred to rheumatology using IRT findings, with N = 8 (80%) seen within 4 weeks. Diagnoses included osteoarthritis, gout, and calcium pyrophosphate deposition disease. IRT demonstrates potential as a reliable tool for identifying inflamed joints and offers a feasible pathway for identifying patients with joint-level thermal abnormalities who may benefit from expedited rheumatologic evaluation. Further research is needed to refine IRT-based rheumatology referral protocols and optimize their utilization.

Despite advancements in prosthetic design, many lower limb amputees continue to experience discomfort and report abandonment rates between 25% and 57%. Issues at the residual limb-socket interface, such as pressure, friction, and poor fit, remain critical challenges affecting long-term prosthesis use. Objective: This study introduces a comprehensive protocol to collect and analyze quantitative data from transtibial amputees, incorporating thermal imaging and biomechanical measures to enhance prosthesis fitting in clinical settings.Study Design: Cross-sectional quantitative clinical study evaluating thermal and biomechanical parameters of prosthetic socket fitting in unilateral transtibial amputees. This is a cross-sectional study that employs quantitative analysis of thermal and biomechanical parameters in transtibial amputees. The study, conducted in a clinical setting, included independent unilateral transtibial amputees. Participants underwent a series of evaluations that included thermograms of the residual limb captured with a thermal camera, weight distribution using a plantar pressure platform, gait symmetry via an inertial sensor, and the 2-minute walk test (2MWT). The protocol aimed to compare the effectiveness of different suspension systems on prosthetic fit. The analysis targets temperature variations at the stump-socket interface and between-system differences in thermal and biomechanical metrics. We hypothesize that suction-based systems demonstrate better thermal consistency and symmetry, pin-lock systems exhibit higher proximal temperature, and valve systems achieve the longest 2-minute walk test distances. Variability in weight distribution and symmetry will inform individualized socket adjustments. The integration of thermal imaging and biomechanical analysis provides a more comprehensive evaluation of prosthesis fitting. Infrared thermography (IRT), although underused, is a promising tool for identifying critical adjustments in prosthetic design. Further research and standardization of such protocols can enhance clinical outcomes and user satisfaction.

Objective. Warm-up is a fundamental part of the training session and competition preparation, improving performance and reducing sports injuries. The FIFA 11+ is a specific evidence-based routine created to enhance neuromuscular performance and prevent lower-limb injuries. Infrared thermography (IRT) is a non-invasive tool for monitoring tissue state and thermoregulation responses. This study examined the acute effects of the FIFA 11+ warm-up on skin surface temperature (Tsk) patterns of the dominant lower limb in amateur football players using IRT.Approach. A pre-post observational design was applied to 120 amateur players (60 men, 60 women) before a match. Baseline and post-intervention Tsk measurements were acquired with a FLIR T540-EST camera following the TERMOINEF protocol.Main results. Significant post-warm-up Tsk reductions were detected in proximal muscle regions, particularly in quadriceps and adductors, with a reduction of -1.9 to -2.4 °C (ES = - 1.63 to -1.92, large) in women and -0.7 to -1.2 °C (ES = - 0.66 to -1.07, moderate) in men. Conversely, distal regions such as the anterior plantar arch showed marked Tsk increases of +2.6 °C (ES = 1.83, large) in women; +2.1 °C (ES = 1.42, large) in men. Men exhibited higher absolute Tsk values overall (η2≈ 0.17-0.26), whereas women displayed greater relative percentage changes, including sex-specific Achilles tendon response (a decrease in women versus a slight increase in men).Significance. FIFA 11+ induces heterogeneous, region- and sex- dependent thermal adaptations, supporting the use of IRT as a valid tool for individualized warm-up monitoring and optimization in football.

A novel IR-SRGAN assisted super-resolution evaluation of photothermal coherence tomography for impact damage in toughened thermoplastic CFRP laminates under room and low temperature

Electromagnetic induced infrared thermography for fast detection of interfacial debonding in coating-metal multilayer structure

Operando Infrared Thermography and Quantitative Insights into Lithium Plating Dynamics on Electrodes during Fast Charging

Infrared thermography (IRT) reveals significant temperature differences between central and peripheral body regions in preterm infants, despite stable core temperature. This suggests active thermoregulation. Photoplethysmography imaging (PPGI) enables contactless, spatially resolved perfusion measurement. Ten preterm infants [GA at birth: 26 weeks (24-28); postnatal age: 35 days (12-62); weight: 960 g (670-1290)] were examined in prone (PR) and supine (SU) positions in the incubator. PPGI (amplitude) and IRT were recorded from arm, head, and thorax every 10 s for 5 min per position, with a 10 min washout. Heart rate (ECG) was monitored. Lin's concordance correlation coefficient was calculated. Central regions were ~1°C warmer than peripheral regions (p<0.05), independent of position. PPGI amplitude remained constant (< 1.0; p>0.05) in all regions, with no correlation between IRT and PPGI (p>0.05). In preterm infants, local perfusion remains stable despite regional temperature differences, suggesting that skin temperature is influenced more by passive heat diffusion than by perfusion changes.

ABSTRACT Assessing heat loss in existing building envelopes is essential for implementing energy-efficient retrofitting projects. However, evaluating envelope thermal performance using infrared thermography (IRT) remains challenging because of limited detection range and the lack of standardized metrics and comparative methods. This study proposes an unmanned aerial vehicle (UAV)-based IRT method for heat-loss assessment. First, infrared digital orthophoto maps (IR-DOMs) of building facades are generated using photogrammetric techniques, enabling extraction of infrared (IR) temperatures from external walls and windows. A dynamic prediction model, referred to as the ‘standard temperature’, is then developed from numerically generated reference samples and regression analysis to provide reference temperatures for comparison with measured IR data. Finally, by analyzing the difference between the measured average IR temperature and the standard temperature, together with the average heat-loss discrepancy, the method introduces quantitative indicators for grading and evaluating envelope thermal performance. The methodology was examined using heating energy consumption data from five buildings in a cold region of China. The resulting heat-loss grades were generally consistent with both annual and 24-hour heating use, indicating that the proposed indicators can support comparative evaluation across multiple buildings and help prioritize retrofit candidates.

Abstract Identification of less-articulated objects using single-channel images, such as thermal images, is important in many applications, such as surveillance. However, in this domain, existing methods show poor performance due to high similarity among objects of the same category in the absence of color information (overlooking shape information) and de-emphasized texture information. Furthermore, variability in viewpoint adds more complexity as the features vary from side to side. We address these issues by constructing viewpoint-conditioned feature vectors and area-specific feature comparisons in separate feature spaces. These interventions enable leveraging the advancements of existing RGB-pre-trained ViT feature extractors while effectively adapting them to address the challenges specific to the thermal domain. We test our system with RGBNT100 (IR) vehicle dataset and a thermal maritime dataset acquired by us. Our results surpass the state-of-the-art methods by 19.7% and 12.8% for the above datasets in mAP scores, respectively. We also plan to make our thermal dataset available, the first of its kind for maritime vessel identification.

To use infrared thermography (IRT) to identify the risk of intraoperative-acquired pressure injuries (IAPIs) and analyze the factors influencing both the occurrence and high risk of IAPIs. A prospective observational study design was employed. The authors recruited 323 patients who underwent general anesthesia with intraoperative sacral compression for an estimated operative time of >3 hours. Infrared thermal images of the sacrum were captured before entering the operating room, after admission to the postanesthesia care unit, and daily for 3 days postoperatively. Sacral skin assessments were conducted based on the International Staging Criteria for Pressure Injuries. Univariate analysis and logistic regression analysis were used to analyze IAPI risk factors and factors associated with the high risk of IAPIs identified by infrared thermography. There were 12 cases of IAPIs (3.72%), all classified as stage 1 PIs. IRT identified 45 cases (13.9%) at high risk for IAPIs. Preoperative hospitalization days and intraoperative SpO2 ≤93% were independent risk factors for IAPIs. Age, body mass index, and intraoperative SpO2 ≤93% were independent risk factors for high-risk IAPIs. Intraoperative SpO2 ≤93% emerged as a common independent risk factor for both IAPI occurrence and high-risk IAPIs. IRT is an effective tool for identifying the risk of IAPIs. Maintaining intraoperative SpO2 above 93% is beneficial in reducing both the occurrence and risk of IAPIs.

Surgical castration is a routine management procedure in swine production that raises welfare concerns due to pain, inflammation, and risk of post-procedure complications. Topical products are commonly applied to castration wounds, but their efficacy in promoting healing and reducing inflammation has not been systematically evaluated. This study investigated and compared the efficacy of five commercially available antiseptic and barrier topical products on wound healing, inflammatory responses, and growth performance in piglets undergoing surgical castration. One hundred and ninety piglets, 3-5 days-old of age, were evaluated under the following treatments: Iodine, Oinkment®, PhytoCare®, Vetericyn®, Zinc Oxide, or intact controls (NoCast). Treatments were applied immediately after castration (D1). Body weights were recorded at baseline (D0; day before castration) and at weaning. Blood samples were collected on days 0 (baseline), 7, and 14 for analysis of prostaglandin E₂ (PGE₂) and haptoglobin. Infrared thermography (IRT) was used to assess surface temperature. Histological evaluation of wound healing was performed on subsets of piglets on days 7 and 14. No treatment effects were observed on body weight or pre-weaning survival; castrated piglets grew similarly to intact controls. Concentrations of PGE₂ declined over time (P < 0.001) but did not differ between treatments, suggesting it may have limited utility as an inflammatory biomarker in neonatal pigs. Haptoglobin concentrations increased across all groups by days 7 and 14, including intact controls, indicating minimal specificity for castration-related inflammation. In contrast, IRT consistently distinguished castrated from intact piglets, supporting its potential as a non-invasive indicator of inflammatory responses. Histological evaluations showed expected time-dependent healing progression, with epidermal thickness correlating with wound severity, but no treatment effects were found. None of the tested topical products were superior to others in regard to wound healing or reduced systemic inflammation under a single-application protocol. While safe and without adverse effects on growth, benefits are unclear when compared to a traditional iodine treatment. The current standard operational procedure for castration requires piglets to receive Iodine after castration to reduce infection risk. Future research should explore no treatment option, repeated applications, microbial wound presence, and behavioral indicators to better evaluate post-castration wound-care strategies.

Intestinal stoma care requires continuous nursing assessment and timely management of peristomal skin complications (PSCs) and perfusion-related risks, yet routine evaluation still relies predominantly on visual inspection and subjective symptom reporting. Infrared thermography (IRT) provides non-contact, visualized temperature monitoring and has been explored across wound and postoperative settings as an objective adjunct for early risk signaling. This review outlines the theoretical foundation of IRT, discusses acquisition and interpretation considerations, and summarizes current evidence in contexts relevant to intestinal stomas, along with implementation-oriented implications for nurse-led stoma care. We conducted a structured literature search in Chinese databases, including China National Knowledge Infrastructure (CNKI), Wanfang Database, and China Science and Technology Journal Database (VIP), and in English-language databases (PubMed, CINAHL, Cochrane Library, Web of Science, and Embase) from inception through February 18, 2026. Controlled vocabulary terms and free-text keywords were combined for thermography and stoma/peristomal concepts, supplemented by wound, postoperative monitoring, and perfusion/ischemia-related terms. Two reviewers independently screened titles/abstracts and full texts using predefined eligibility criteria, with adjudication by a third reviewer when needed. Findings were synthesized narratively due to heterogeneity. Nine studies were included, spanning postoperative infection/delayed healing monitoring, perfusion/ischemia-related evaluation, abdominal thermographic mapping, stimulated thermography for tissue differentiation, and mobile thermography with algorithmic analysis. Across studies, temperature-difference metrics (e.g., temperature difference, ΔT) and pattern-based interpretation were commonly used, while devices, acquisition conditions, and reported thermal metrics varied substantially. Current evidence supports feasibility of IRT as a non-contact adjunct for temperature-pattern monitoring in contexts relevant to intestinal stoma care, but robust stoma-specific validation remains insufficient. Standardized acquisition procedures, interpretable thresholds, and pathway-level integration into nurse-led decision-making are key prerequisites for translation. Future implementation-ready studies with clinically meaningful endpoints and reproducibility testing are required to define when IRT adds value beyond routine assessment and how it can be embedded safely into real-world stoma care pathways.

Context Residual feed intake (RFI) and residual intake and gain (RIG) are widely used metrics to assess feed efficiency in sheep. However, their practical implementation in breeding programs remains limited owing to the high cost and complexity of individual feed intake measurements. Consequently, alternative indicators, such as physiological responses and infrared thermography (IRT), have been proposed as potential proxies for identifying animals with superior feed efficiency under different environmental conditions. Aims This study aimed to evaluate the relationships between RFI and RIG classifications and physiological parameters, as well as surface body temperatures obtained via IRT, in Texel ewes exposed to natural heat stress. Methods Thirty-nine young Texel ewes were monitored for 57 days in a covered facility equipped with an automated feeding and watering system with individual intake recording. Animals were classified into low, medium, and high-efficiency groups according to their RFI and RIG values. Physiological responses, including respiratory rate (RR), heart rate (HR), rectal temperature (RT), and the heat tolerance coefficient (HTC), were recorded. Additionally, surface temperatures of the eye, muzzle, hooves, and vulva were measured using infrared thermography (IRT). Statistical analyses included ANOVA and principal component analysis (PCA) to explore associations among traits. Key results No significant differences were detected among RFI or RIG classes for RR, HR, RT, or HTC. Similarly, IRT-derived surface temperatures did not differ across efficiency classifications. PCA showed that RR and HTC explained the greatest proportion of total variance, whereas RFI and RIG contributed to other independent components. Conclusions Neither physiological parameters nor IRT-based surface temperatures were effective indicators of feed efficiency in Texel ewes under natural heat stress. Implications The results indicated that RFI and RIG cannot be accurately inferred from physiological or IRT variables under field conditions. Future research should integrate additional phenotypic and behavioral indicators to identify reliable, low-cost biomarkers for metabolic efficiency in sheep.

This contribution presents a combined approach for in-situ experimental characterisation and numerical modelling of thermo-mechanical behaviour in directed energy deposition (DED). Full-field temperature and substrate deformation are measured simultaneously using infrared (IR) thermography and stereo digital image correlation (DIC) during laser-beam powder deposition on a thin substrate. The experimental data are used to calibrate thermal boundary conditions and to validate a macroscopic finite-element model. The validated framework is then applied to compare different deposition strategies, demonstrating the capability of the coupled measurements and simulations to capture transient thermal fields, deformation evolution and toolpath-dependent effects relevant for process optimisation.

Abstract Non-Destructive Testing (NDT) has become an essential technology for modern industrial maintenance and the inspection of various materials. Amongst different NDT technologies, Infrared Thermography (IRT) offers a robust framework to reveal the subsurface anomalies inside the sample. However, conventional Infrared Imaging (IR) methods are often time consuming, manual and incapable of automatic distinguishing defects from non-defective regions. To address the issue, an automatic defect detection framework is proposed, which integrates an unsupervised autoencoder learning approach with image fusion. Autoencoder is trained on non-defective regions to model the heat distribution patterns. During testing, defective frames show large reconstruction errors and obtained frames are further used for segmentation. The defective frames are segmented using adaptive thresholding to highlight regions with high reconstruction error and generate binary masks that localize potential defect areas. Subsequently, Signal to Noise Ratio (SNR) is computed across each defective region to estimate the thermal contrast. This SNR directs the fusion across all the defective frames of the given defect at given spatial location. The proposed approach estimated the reconstructed and accurate frame with automatic identification of defective frames, achieving high detection sensitivity across varying defect depths. The integration of infrared imaging with neural network based autoencoder substantially enhances the efficiency, reliability, and depth resolving capability of thermal-based defect detection system.