Facial Thermal and Blood Perfusion Patterns of Human Emotions: Proof-of-Concept

In this work, a preliminary study of proof-of-concept was conducted to evaluate the performance of the thermographic and blood perfusion data when emotions of positive and negative valence are applied, where the blood perfusion data are obtained from the thermographic data. The images were obtained for baseline, positive, and negative valence according to the protocol of the Geneva Affective Picture Database. Absolute and percentage differences of average values of the data between the valences and the baseline were calculated for different regions of interest (forehead, periorbital eyes, cheeks, nose and upper lips). For negative valence, a decrease in temperature and blood perfusion was observed in the regions of interest, and the effect was greater on the left side than on the right side. In positive valence, the temperature and blood perfusion increased in some cases, showing a complex pattern. The temperature and perfusion of the nose was reduced for both valences, which is indicative of the arousal dimension. The blood perfusion images were found to be greater contrast; the percentage differences in the blood perfusion images are greater than those obtained in thermographic images. Moreover, the blood perfusion images, and vasomotor answer are consistent, therefore, they can be a better biomarker than thermographic analysis in identifying emotions.Comment: 22 pages, 9 figure

Infrared radiometric technique in temperature measurement

One class of commercially available imaging infrared radiometers using cooled detectors is sensitive to radiation over the 3 to 12 micron wavelength band. Spectral filters can tailor instrument sensitivity to specific regions where the target exhibits optimum radiance. The broadband spectral response coupled with real time two-dimensional imaging and emittance/background temperature corrections make the instruments useful for remote measurement of surface temperatures from -20 C to +1500 C. Commonly used radiometric techniques and assumptions are discussed, and performance specifications for a typical modern commercial instrument are presented. The potential usefulness of an imaging infrared radiometer in space laboratories is highlighted through examples of research, nondestructive evaluation, safety, and routine maintenance applications. Future improvements in instrument design and application of the radiometric technique are discussed

What not to do in facial infrared thermographic measurements: A post data enhancement

The accuracy of infrared thermographic measurements depends on several factors, including movement of target. In this study, accuracy of nose tip temperatures obtained in a mental workload assessment using a thermal imaging camera were impacted by participants’ movement and camera zooming/panning. To correct these measurement errors, we compared manual facial landmark identification techniques using data labelling software with an automated deep learning-based approach utilised for facial landmark tracking and evaluated both against the built-in tracking features of the thermal camera, Thermal Spot Tracking. Using the Manual Thermal Landmark Annotation measurements as the ground truth, our results show that the Automated Facial Feature Tracking approach, which is the AI based approach performed better than the Thermal Spot Tracking as it matched comparatively more spatial coordinates and temperature datapoints as well as showed comparatively lower mean relative error. The study highlights the potential of AI in enhancing the accuracy of thermographic measurements, particularly in applications involving facial temperature analysis

Effect of Facial Skin Temperature on the Perception of Anxiety: A Pilot Study

[EN] The extent of anxiety and psychological stress can impact upon the optimal performance of simulation-based practices. The current study investigates the association between di erences in skin temperature and perceived anxiety by under- (n = 21) and post-graduate (n = 19) nursing students undertaking a cardiopulmonary resuscitation (CPR) training. Thermal facial gradients from selected facial regions were correlated with the scores assessed by the State-Trait Anxiety Inventory (STAI) and the chest compression quality parameters measured using mannequin-integrated accelerometer sensors. A specific temperature profile was obtained depending on thermal facial variations before and after the simulation event. Statistically significant correlations were found between STAI scale scores and the temperature facial recordings in the forehead (r = 0.579; p < 0.000), periorbital (r = 0.394; p < 0.006), maxillary (r = 0.328; p < 0.019) and neck areas (r = 0.284; p < 0.038). Significant associations were also observed by correlating CPR performance parameters with the facial temperature values in the forehead (r = 0.447; p < 0.002), periorbital (r = 0.446; p < 0.002) and maxillary areas (r = 0.422; p < 0.003). These preliminary findings suggest that higher anxiety levels result in poorer clinical performance and can be correlated to temperature variations in certain facial regionsSIThis research was supported by the Innovative Educational Groups’ Support Program (PAGID 2018) from the Universidad de León (ULE

A low cost shading analyzer and site evaluator design to determine solar power system installation area

Shading analyzer systems are necessary for selecting the most suitable installation site to sustain enough solar power. Afterwards, changes in solar data throughout the year must be evaluated along with the identification of obstructions surrounding the installation site in order to analyze shading effects on productivity of the solar power system. In this study, the shading analysis tools are introduced briefly, and a new and different device is developed and explained to analyze shading effect of the environmental obstruction on the site on which the solar power system will be established. Thus, exposure duration of the PV panels to the sunlight can be measured effectively. The device is explained with an application on the installation area selected as a pilot site, Denizli, in Turkey. © 2015 Selami Kesler et al

Intelligent Thermal Condition Monitoring Of Electrical Equipment Using Infrared Thermography

Infrared thermographic inspection system is widely being utilized for defect detection in electrical equipment. Conventional inspection based on the temperature data interpretation and evaluation the condition of the equipment is subjective and depends on the human experts. Implementation of an automatic diagnostic system based on artificial neural network reduces operating time, human efforts and also increases the reliability of system. In this thesis, an automatic features extraction system from thermal image of defects and the intelligent classification of thermal condition based on neural network are proposed. The proposed system extracts first order histogram based features and grey level co-occurrence matrix features from the segmented regions and evaluates the effectiveness of these features for defect characterization. Three feature selection techniques namely principal component analysis, the discriminant analysis and individual feature performance analysis are employed to find out the useful and important statistical features. In this study, multilayered perceptron network is proposed for classifying thermal condition into two classes namely normal and defective. The multilayered perceptron neural networks are trained using various training algorithms. Additionally, the present research introduces a computer aided defect diagnosis system where the defected region is found by manual thresholding and intensity features are extracted from each segmented region. The results prove that the statistical features are capable to classify thermal condition and the neural networks achieve the accuracy around 73~78

Comparison of Cooled and Uncooled IR Sensors by Means of Signal-to-Noise Ratio for NDT Diagnostics of Aerospace Grade Composites

This work aims to address the effectiveness and challenges of non-destructive testing (NDT) by active infrared thermography (IRT) for the inspection of aerospace-grade composite samples and seeks to compare uncooled and cooled thermal cameras using the signal-to-noise ratio (SNR) as a performance parameter. It focuses on locating impact damages and optimising the results using several signal processing techniques. The work successfully compares both types of cameras using seven different SNR definitions, to understand if a lower-resolution uncooled IR camera can achieve an acceptable NDT standard. Due to most uncooled cameras being small, lightweight, and cheap, they are more accessible to use on an unmanned aerial vehicle (UAV). The concept of using a UAV for NDT on a composite wing is explored, and the UAV is also tracked using a localisation system to observe the exact movement in millimetres and how it affects the thermal data. It was observed that an NDT UAV can access difficult areas and, therefore, can be suggested for significant reduction of time and cost

Unsupervised automatic tracking of thermal changes in human body

An automated system for detecting and tracking of the thermal fluctuation in human body is addressed. It applies HSV based k-means clustering which initialized and controlled the points which lie on the ROI boundary. Afterward a particle filter tracked the targeted ROI in the thermal video stream. There were six subjects have voluntarily participated on these experiments. For simulating the hot spots occur during the some medical tests a controllable heater utilized close to the subjects body. The results indicated promising accuracy of the proposed approach for tracking the hot spots. However, there were some approximations (e.g. the transmittance of the atmosphere and emissivity of the fabric) which can be neglected because of independency of the proposed approach for these parameters. The approach can track the heating spots efficiently considering the movement in the subjects which provided a confidence of considerable robustness against motion-artifact usually occurs in the medical tests

Infrared Thermography in Marine Applications

Infrared (IR) thermography has become a powerful tool for basic and applied scientifi c research and for the application in various fi elds such as industry, environment, military and maritime affairs, etc. As a „predictive“ maintenance tool, IR thermography has the ability to identify problems before they occur. It is especially helpful for trouble shooting potential electrical overloads, worn or bad circuit breakers and buses. IR thermography can also be used to detect bad bearings, shafts, worn pulleys or any application where heat detection would be benefi cial. This paper has the intention to familiarize researchers, engineers and sea business staff with possibilities of applying IR thermography in the fi eld of maritime affairs. Therefore, basic principles of IR thermography are presented and examples of the tool application are given