Search Results (152)

Mid-infrared passive spectroscopic imaging is a novel non-invasive and remote sensing method based on Planck’s law. It enables the acquisition of component-specific information from the human body by measuring naturally emitted thermal radiation in the mid-infrared region. Unlike active methods that require an external light source, our passive approach harnesses the body’s own emission, thereby enabling safe, long-term monitoring. In this study, we successfully demonstrated the simultaneous, non-invasive measurements of blood glucose and lactate levels of the human body using this method. The measurements, conducted over approximately 80 min, provided emittance data derived from mid-infrared passive spectroscopy that showed a temporal correlation with values obtained using conventional blood collection sensors. Furthermore, to evaluate localized metabolic changes, we performed k-means clustering analysis of the spectral data obtained from the upper arm. This enabled visualization of time-dependent lactate responses with spatial resolution. These results demonstrate the feasibility of multi-component monitoring without physical contact or biological sampling. The proposed technique holds promise for translation to medical diagnostics, continuous health monitoring, and sports medicine, in addition to facilitating the development of next-generation healthcare technologies. Full article

While radiation thermometry is well-developed for laboratory calibrations using high-emissivity sources, the effect of spectral emissivity in real-world conditions, where emissivity ranges from 0 to 1, is usually not considered. Spectral parameters that influence non-contact temperature measurements are often neglected even in laboratory conditions. These parameters become more important with decreasing emissivity and at lower temperatures, leading to increased uncertainty contributions to the measurement result. In this manuscript, we analyze the impact of various influential spectral parameters using the constructed spectral Monte Carlo simulation of radiation thermometry. The investigation covers the influence of spectral and related parameters, namely spectral emissivity, reflection temperature, spectral sensitivity and atmospheric parameters of temperature, relative humidity and distance of the path in the atmosphere. Simulation results are compared to experimental results, overestimating sensitivity to humidity by 23–27% and sensitivity to emissivity and reflected temperature within 10% at given conditions. Multiple cases of radiation thermometer (RT) use are simulated for measurement uncertainty: high temperature RT use as the reference in calibration by comparison, the use of a flat plate calibrator for RT calibration, measurements with a RT using emissivity input data from literature with relatively high uncertainty and temperature measurements with a RT using emissivity data, obtained with FTIR spectroscopy with relatively low uncertainty. Findings suggest that spectral uncertainty contributions are often unjustifiably underestimated and neglected, nearing extended uncertainty contribution of 1.94 °C in calibration practices using flat plate calibrators with emissivity within 0.93 and 0.97 and 1.72 °C when radiation thermometers with spectral ranges, susceptible to atmospheric humidity, are used on black bodies. Full article

Background: Traditional neonatal assessments rely on anthropometric measures such as weight, body size, and head circumference. However, recent studies suggest that objective movement quantification may serve as a complementary clinical indicator of development in preterm infants. Methods: This study evaluates non-invasive computer vision-based quantification of neonatal movement using contactless pose tracking based on computer vision. We analyzed approximately 800,000 postural data points from ten preterm infants to identify reliable algorithms, optimal recording duration, and whether whole-body or regional tracking is sufficient. Results: Our findings show that 30 s video segments are adequate for consistent motion quantification. Optical flow methods produced inconsistent results, while distance-based algorithms—particularly Chebyshev and Minkowski—offered greater stability, with coefficients of variation of 5.46% and 6.40% in whole-body analysis. Additionally, Minkowski and Mahalanobis metrics applied to the lower body yielded results similar to full-body tracking, with minimal differences of 0.89% and 1%. Conclusions: The results demonstrate that neonatal movement can be quantified objectively and without physical contact using computer vision techniques and reliable computational methods. This approach may serve as a complementary clinical indicator of neonatal progression, alongside conventional measures such as weight and size, with applications in continuous monitoring and early clinical decision-making for preterm infants. Full article

Object-related accidents among older adults often result from inadequately designed furniture and fixtures that do not accommodate age-related changes. However, technologies for quantitatively capturing how furniture and fixtures assist the body in daily life remain limited. This study addresses this gap by introducing a portable, non-disruptive system that measures and visualizes how humans interact with environmental objects, particularly during transitional movements such as standing, turning, or reaching. The system integrates wearable force sensors, motion capture gloves, RGB-D cameras, and LiDAR-based environmental scanning to generate spatial maps of body-applied forces, overlaid onto point cloud representations of actual living environments. Through home-based experiments involving 13 older adults aged 69–86 across nine households, the system effectively identified object-specific support interactions with specific furniture (e.g., doorframes, shelves) and enabled a three-dimensional comparative analysis across different spaces, including living rooms, entryways, and bedrooms. The visualization captured essential spatial features—such as contact height and positional context—without altering the existing environment. This study presents a novel methodology for evaluating life environments from a life-centric perspective and offers insights for the inclusive design of everyday objects and spaces to support safe and independent aging in place. Full article

Background: Rectal temperature measurement in cats, while crucial, can cause discomfort and stress. This study evaluated non-contact infrared thermometry as a less invasive alternative. Methods: A total of 95 cats were enrolled in this study. The cats were categorized into three age groups: Group I (n = 20 kittens, 2–6 months), Group II (n = 34 young cats, 7–24 months), and Group III (n = 41 adult cats, >24 months). Results: The mean rectal temperature in cats was approximately 38 °C, which was significantly higher than both ocular temperature (p < 0.0001) and auricular pinna temperature (p < 0001). No statistically significant difference was found between rectal and perineal temperatures, nor in body temperatures between the age groups. Ocular temperature (p < 0.05) and auricular temperature (p < 0.0001) were influenced by ambient temperature. Perineal infrared temperatures showed a strong correlation and low bias compared to rectal temperature and were not affected by ambient temperature. Conclusions: Non-contact infrared thermometry offers advantages for feline temperature monitoring. Perineal infrared temperatures appear to be a useful, non-invasive alternative to rectal measurements in cats. Full article

Non-contact human respiration rate monitoring can be used for sleep apnea detection and home care. Typically, the human body does not remain stationary for long periods, and body movement can significantly affect the performance of non-contact respiratory monitoring. Because the breathing rate generally remains stable over short periods, using measurements from only a portion of the radar echo signals does not result in significant errors, and these errors will be smaller than those caused by body movement. However, selecting a window size that is too short reduces frequency resolution, leading to increased estimation errors. Choosing an appropriate window length can improve estimation accuracy. In this paper, we propose an algorithm to determine whether the subject is stationary and select the received signal with minimal body movement. Experimental results are compared using alternative schemes, including fast Fourier transform (FFT), short-time Fourier transform (STFT), and RGB-D camera-assisted methods, in terms of root mean square error (RMSE) performance. Full article

Background/Objectives: Childhood obesity is a significant health concern also capable of impacting ocular health. This study evaluates the effects of childhood obesity on corneal morphology, anterior chamber parameters, intraocular pressure (IOP), and corneal endothelial cell morphology. Understanding these relationships may contribute to early diagnosis and management strategies. Methods: This prospective, cross-sectional study was conducted at the Harran University Faculty of Medicine between January and December, 2024. Ninety children aged 7–17 years were included, with only the right eyes being analyzed. The participants were categorized into three groups based on body mass index (BMI) percentiles: normal weight (≤85th percentile), overweight (86–94th percentiles), and obese (≥95th percentile). All participants underwent comprehensive ophthalmological examinations, including IOP measurement with a non-contact tonometer, corneal topography assessment using a Scheimpflug camera, and endothelial cell morphology evaluation via specular microscopy. Results: IOP was significantly higher in the overweight and obese groups (p < 0.001). Central corneal thickness (CCT) also increased significantly in these groups (p < 0.05). Positive correlations were determined between BMI and IOP (r = 0.493, p < 0.001) and CCT (r = 0.345, p < 0.001). Additionally, waist circumference exhibited a strong correlation with BMI (r = 0.905, p < 0.001) and a significant association with IOP (r = 0.463, p < 0.001). No significant differences were observed among the groups in terms of other anterior chamber or endothelial parameters. Conclusions: Childhood obesity is associated with increased IOP and CCT, suggesting potential alterations in corneal biomechanics and ocular physiology. These findings highlight the importance of routine ophthalmological evaluation in obese children to detect early ocular changes and prevent long-term complications. Full article

Monitoring calf body weight (BW) before weaning is essential for assessing growth, feed efficiency, health, and weaning readiness. However, labor, time, and facility constraints limit BW collection. Additionally, Holstein calf coat patterns complicate image-based BW estimation, and few studies have explored non-contact measurements taken at early time points for predicting later BW. The objectives of this study were to (1) develop deep learning-based segmentation models for extracting calf body metrics, (2) compare deep learning segmentation with threshold-based methods, and (3) evaluate BW prediction using single-time-point cross-validation with linear regression (LR) and extreme gradient boosting (XGBoost) and multiple-time-point cross-validation with LR, XGBoost, and a linear mixed model (LMM). Depth images from Holstein (n = 63) and Jersey (n = 5) pre-weaning calves were collected, with 20 Holstein calves being weighed manually. Results showed that You Only Look Once version 8 (YOLOv8) deep learning segmentation (intersection over union = 0.98) outperformed threshold-based methods (0.89). In single-time-point cross-validation, XGBoost achieved the best BW prediction (R² = 0.91, mean absolute percentage error (MAPE) = 4.37%), while LMM provided the most accurate longitudinal BW prediction (R² = 0.99, MAPE = 2.39%). These findings highlight the potential of deep learning for automated BW prediction, enhancing farm management. Full article

Healthcare workers (HCWs) are frequently exposed to a variety of chemical agents, which can result in the development of allergic or irritant contact dermatitis. The present study aimed to assess the prevalence of skin sensitization among HCWs who presented with symptoms of contact dermatitis, considering both occupational and non-occupational risk factors. The study population comprised 127 HCWs who attended routine occupational health surveillance at the Tor Vergata Teaching Hospital in Rome between November 2023 and May 2024. A structured dermatitis questionnaire and patch testing were administered to the participants. Demographic and lifestyle data, including information on occupation, night shift work, smoking habits, and body mass index (BMI), were collected. Patch test positivity was observed in 31.5% of participants, with the most common clinical presentation being erythematous-desquamative allergic contact dermatitis. A significantly higher likelihood of patch test positivity was observed among nurses (57.1%), particularly for nickel sensitization, compared to other occupational groups. A trend towards an association between night shift work and skin sensitization was observed, although this did not reach statistical significance. No significant associations were found for ages over 35 years, sex, or BMI. These findings highlight the elevated risk of contact sensitization among nurses, emphasizing the need for targeted interventions, including exposure reduction strategies and protective measures, to mitigate occupational skin hazards in healthcare settings. Full article

Hypertension (HPT) is a chronic disease characterized by the consistent elevation of arterial blood pressure, which is considered to be a significant risk factor for conditions such as stroke, coronary artery disease, and heart failure. The detection and continuous monitoring of HPT can be a demanding process. As a non-contact measuring method, the ballistocardiography (BCG) signal characterizes the repetitive body motion resulting from the forceful ejection of blood into the major blood vessels during each heartbeat. Therefore, it can be applied for HPT detection. HPT detection with BCG signals remains a challenging task. In this study, we propose an end-to-end deep convolutional model BH-Net for HPT detection through BCG signals. We also propose a data augmentation scheme by selecting the J-peak neighborhoods from the BCG time sequences for hypertension detection. Rigorously evaluated via a public data-set, we report an average accuracy of 97.93% and an average F1-score of 97.62%, outperforming the comparative state-of-the-art methods. We also report that the performance of the traditional machine learning methods and the comparative deep learning models was improved with the proposed data augmentation scheme. Full article

Biochemical oxygen demand (BOD) is an important indicator of the degree of organic pollution in water bodies. Traditional methods for BOD₅ determination, although widely used, are complicated and dependent on accurate chemical measurements of dissolved oxygen. The aim of this study was to propose a facile method for predicting biochemical oxygen demand by fluorescence signals using three-dimensional fluorescence spectroscopy and parallel factor analysis in combination with a machine learning algorithm. The water samples were incubated for five days using the national standard method, during which the dissolved oxygen contents and three-dimensional fluorescence spectroscopy data were measured at eight-hour intervals. The maximum fluorescence intensity of three fluorescence components was decomposed and extracted by parallel factor analysis. The relationship between the maximum fluorescence of the three fluorescence components and the BOD₅ values was established using a random forest model. The results showed that there was a good correlation between the fluorescence components and BOD values. The BOD₅ values were effectively predicted by the random forest model with a high goodness of fit (R² = 0.878) and low mean square error (MSE = 0.28). Although this method did not shorten the incubation time, successful BOD₅ prediction was realized by the non-contact measurement of fluorescence signals. This avoids the complicated operation of DO determination, improves detection efficiency, and provides a convenient solution for analyzing large quantities of water samples and monitoring facile water quality. Full article

Background: Low back pain is one of the most common musculoskeletal complaints in team sports. A screening test can help understand why injuries occur and predict who is at risk for non-contact low back pain. The objectives of the research were (1) to create models using logistic regression analysis of limited lower-extremity ranges of motion to prospectively identify potential factors for in-season non-contact non-contact low back pain and (2) to determine a training threshold (cut-off) for the identified factors in inline hockey players. Methods: A prospective cohort research was performed with 49 male inline hockey players aged 8 to 15 years. Data were collected regarding age, body composition, sports antecedents, competition level, and lower-limb ranges of motion (ROM-SPORT battery, n = 11 tests). A prospective measurement of non-contact low back pain was performed after 1 year (outcome) by asking the players supervised by the medical staff team (questionnaire). Results: Sixteen players (32.7%) experienced non-contact low back pain during the 1-year surveillance period. The model showed a significant relationship (χ²(39) = 43.939; p < 0.001) between the low back pain and the predictor variable hip flexion with the knee extended range of motion (OR = 3.850 [large]; 95% CI = 1.293 to 11.463; p = 0.015). The Bayesian Information Criteria and the Akaike Information Criteria for model fit were 56.885 and 37.967, respectively. The training threshold for hip flexion with the knee extended of ≤67° was set, which has an acceptable (area under the curve ≥ 94.1%) discriminatory ability for the development of non-contact low back pain for the screening test. Conclusions: Hamstring extensibility at 67° or less, as determined by hip flexion with knee extension, is a predictor of non-contact low back pain in youth inline hockey players. Full article

Every day, approximately 7 m³ of air flows through the lungs of an adult, which comes into contact with 80 m² of the lung surface. This air contains both natural and anthropogenic particles, which can deposit on the surface of the mucus lining the respiratory tract. The presence of particles in the mucus leads to changes in its rheology and, consequently, in its functions. Therefore, this research aimed to determine how a non-Newtonian fluid suspension will behave during flow, illustrating the movement of mucus during coughing. The model mucus was an aqueous solution of carboxymethylcellulose (CMC). The tested particles suspended in a non-Newtonian fluid were Arizona Fine Dust, diesel exhaust particles, polyethylene microparticles, and pine pollen. It was noticed that as the fluid viscosity increases, the number of Kelvin–Helmholtz instabilities increases. The fluid’s expansion angle at the output of the measuring cell decreased, and the values of parameters characterizing the aerosol generated at the outlet decrease for selected particles present in the fluid. The research shows that the deposition of particles from polluted air in the respiratory tract, although they do not enter the bloodstream, may affect the human body. Deposited particles can change the behavior of mucus, which may translate into its functions. Full article

Pulse signals can serve as important indicators of one’s cardiovascular condition. However, capturing signals with stable morphology using radar under varying measurement periods remains a significant challenge. This paper reports a non-contact arterial pulse measurement method based on mmWave radar, with stable signals achieved through a range–angle focusing algorithm. A total of six subjects participated in the experiment, and the results showed that, under different measurement times, the pulse morphology of the same body part for each subject had good consistency, reaching a correlation of over 0.84, and four selected pulse signs remained stable. This is a quantitative assessment revealing a high correlation in pulse morphology measured by radar over different periods. In addition, the influence of array size and measurement distance was analyzed, providing a reference of array selection for research work with different requirements. This work offers an effective reference framework for long-term pulse measurement using radar technology. Full article

Non-contact heart monitoring is crucial in advancing telemedicine, fitness tracking, and mass screening. Remote photoplethysmography (rPPG) is a non-contact technique to obtain information about heart pulse by analyzing the changes in the light intensity reflected or absorbed by the skin during the blood circulation cycle. However, this technique is sensitive to environmental lightning and different skin pigmentation, resulting in unreliable results. This research presents a multimodal approach to non-contact heart rate estimation by combining facial video and physical attributes, including age, gender, weight, height, and body mass index (BMI). For this purpose, we collected local datasets from 60 individuals containing a 1 min facial video and physical attributes such as age, gender, weight, and height, and we derived the BMI variable from the weight and height. We compare the performance of two machine learning models, support vector regression (SVR) and random forest regression on the multimodal dataset. The experimental results demonstrate that incorporating a multimodal approach enhances model performance, with the random forest model achieving superior results, yielding a mean absolute error (MAE) of 3.057 bpm, a root mean squared error (RMSE) of 10.532 bpm, and a mean absolute percentage error (MAPE) of 4.2% that outperforms the state-of-the-art rPPG methods. These findings highlight the potential for interpretable, non-contact, real-time heart rate measurement systems to contribute effectively to applications in telemedicine and mass screening. Full article