Mass screening of suspected febrile patients with remote-sensing infrared thermography: alarm temperature and optimal distance

The topical application of different galenic formulations can alter the thermographic images of skin: Limitations for public thermal screening on infection control situations

BACKGROUND

To analyze whether the application of topical formulas as cosmetics or sunscreens could affect the skin thermographic readings in terms of infection control in pandemic situations.

METHODS

The temperature of the skin of the dorsal region of the back and the face of 20 volunteers was followed after the application of 6 different types of gels, sunscreens, and make-up under controlled temperature and humidity conditions. High-resolution thermographic images were analyzed to calculate the temperature of treated skin compared to skin free of topical products.

RESULTS

The application of hydroalcoholic gel resulted in a mean drop of more than 2°C just after 1 minute followed by organic sunscreens until 1.7°C. Recovery was observed progressively until minute 9. Color make-up type formulas, rich in iron oxide as well as sunscreens with mineral filters had little or no effect on the skin thermal response.

CONCLUSIONS

It is possible to alter the skin temperature almost immediately by using hydroalcoholic gels and sunscreen cosmetics. So, it is possible to produce false negative data in the readings of patients screened thermically.

Noncontact remote sensing of abnormal blood pressure using a deep neural network: a novel approach for hypertension screening

Background

As the global burden of hypertension continues to increase, early diagnosis and treatment play an increasingly important role in improving the prognosis of patients. In this study, we developed and evaluated a method for predicting abnormally high blood pressure (HBP) from infrared (upper body) remote thermograms using a deep learning (DL) model.

Methods

The data used in this cross-sectional study were drawn from a coronavirus disease 2019 (COVID-19) pilot cohort study comprising data from 252 volunteers recruited from 22 July to 4 September 2020. Original video files were cropped at 5 frame intervals to 3,800 frames per slice. Blood pressure (BP) information was measured using a Welch Allyn 71WT monitor prior to infrared imaging, and an abnormal increase in BP was defined as a systolic blood pressure (SBP) ≥140 mmHg and/or diastolic blood pressure (DBP) ≥90 mmHg. The PanycNet DL model was developed using a deep neural network to predict abnormal BP based on infrared thermograms.

Results

A total of 252 participants were included, of which 62.70% were male and 37.30% were female. The rate of abnormally high HBP was 29.20% of the total number. In the validation group (upper body), precision, recall, and area under the receiver operating characteristic curve (AUC) values were 0.930, 0.930, and 0.983 [95% confidence interval (CI): 0.904-1.000], respectively, and the head showed the strongest predictive ability with an AUC of 0.868 (95% CI: 0.603-0.994).

Conclusions

This is the first technique that can perform screening for hypertension without contact using existing equipment and data. It is anticipated that this technique will be suitable for mass screening of the population for abnormal BP in public places and home BP monitoring.

InfraNet: Accurate forehead temperature measurement framework for people in the wild with monocular thermal infrared camera

During an epidemic, accurate human temperature screening based on neural networks for disease surveillance is important and challenging. Existing distant human forehead temperature measuring device usually adopts a dual-camera system using paired RGB and thermal infrared images to conduct face detection and temperature measurement. Since the facial RGB image may undermine people's privacy, we designed a monocular thermal system and proposed an effective framework called the InfraNet to measure and calibrate forehead temperature of people in the wild. To address the challenge of temperature floating, the InfraNet calibrates the subject's temperature with one's physical depth and horizontal offset predicted by a single infrared image. Our InfraNet framework mainly consists of three parts: face detection subnet, depth and horizontal offset estimation subnet and temperature calibration subnet. The temperature calibration performance can be improved with the help of spatial regularization term concentrating on predicting precise depth and horizontal offset of people. Besides, we collected a large-scale infrared image dataset in the both lab and wild scenarios, including 8,215 thermal infrared images. Experiments on our wild dataset demonstrated that the InfraNet achieved 91.6% high accuracy of distant multi-subject temperature measurement on average under the standard temperature threshold of strict 0.3°C.

The defense of Shangri-La: Protecting isolated communities by periodic infection screening in the worst future pandemic

In the worst future pandemic, effective vaccines and medicines could be unavailable for a long time. In such circumstances, it is necessary to evaluate whether a periodic screening can protect isolated communities and critical facilities and avoid a complete shutdown. In this study, we introduced an epidemiological model that included the essential parameters of infection transmission and screening. With varying parameters, we studied the dynamics of viral infection in the isolated communities. In the scenario with a periodic infection screening once per 3 days and a viral basic reproduction number 3.0, >85% of the infection waves have a duration <7 days and the infection size in each of the waves is generally <4 individuals when the efficiency of infection discovery is 0.9 in the screening. When the period of screening was elongated to once per 7 days, the cases of infection dramatically increased to 5 folds of that mentioned previously. Further, with a weak discovery efficiency of 0.7 and the aforementioned low screening frequency, the spread of infection would be out of control. Our study suggests that frequent periodic screening is capable of controlling a future epidemic in isolated communities without other measures.

Infrared image method for possible COVID-19 detection through febrile and subfebrile people screening

This study proposed an infrared image-based method for febrile and subfebrile people screening to comply with the society need for alternative, quick response, and effective methods for COVID-19 contagious people screening. The methodology consisted of: (i) Developing a method based on facial infrared imaging for possible COVID-19 early detection in people with and without fever (subfebrile state); (ii) Using 1206 emergency room (ER) patients to develop an algorithm for general application of the method, and (iii) Testing the method and algorithm effectiveness in 2558 cases (RT-qPCR tested for COVID-19) from 227,261 workers evaluations in five different countries. Artificial intelligence was used through a convolutional neural network (CNN) to develop the algorithm that took facial infrared images as input and classified the tested individuals in three groups: fever (high risk), subfebrile (medium risk), and no fever (low risk). The results showed that suspicious and confirmed COVID-19 (+) cases characterized by temperatures below the 37.5 °C fever threshold were identified. Also, average forehead and eye temperatures greater than 37.5 °C were not enough to detect fever similarly to the proposed CNN algorithm. Most RT-qPCR confirmed COVID-19 (+) cases found in the 2558 cases sample (17 cases/89.5%) belonged to the CNN selected subfebrile group. The COVID-19 (+) main risk factor was to be in the subfebrile group, in comparison to age, diabetes, high blood pressure, smoking and others. In sum, the proposed method was shown to be a potentially important new tool for COVID-19 (+) people screening for air travel and public places in general.

Determination of Internal Temperature by Measuring the Temperature of the Body Surface Due to Environmental Physical Factors-First Study of Fever Screening in the COVID Pandemic

The SARS-CoV-2 virus pandemic has shown that the use of a contact thermometer to verify the elevated body temperature of a suspected person carries a risk of spreading disease. The perfect solution seems to be the use of thermal imaging as a diagnostic method in fever evaluation. The aim of the research is to develop an algorithm for thermovision measurements in fever screening standards in the context of the impact of various weather conditions on the temperature of people entering the public institution. Each examined person had two thermal images of the face-AP and lateral projection. Using a T1020 FLIR thermal camera with a resolution of 1024 × 768 pixels; the mean temperature was measured from the area of the forehead, the maximum forehead, the corners of the eyes, the inside of the mouth and the external auditory canal temperature. On the other hand, using classic contact thermometers, the temperature in the armpit and ear was measured. The obtained preliminary results showed very strong and positive correlations between the temperature in the ear measured with an ear thermometer and the maximum, minimum and average forehead temperature. These correlations oscillate at approximately r = 0.6, but the highest value of Spearman coefficient was obtained for the mean temperature of the forehead. Moreover, high correlations were also obtained between the temperature in the ear, measured with an ear thermometer, and the maximum temperature in the corners of the eyes and in the ear, measured with a thermal imaging camera. These values were, respectively, r = 0.54, r = 0.65. In summarizing, remote body temperature measurement taken with a thermal camera can be useful in the assessment of the body's core temperature.

Statistical Study on Human Temperature Measurement by Infrared Thermography

Increased temperature in humans is the symptom of many infectious diseases and it is thus an important diagnostic tool. Infrared temperature measurement methods have been developed and applied over long periods due to their advantage of non-contact and fast measurements. This study deals with a statistical evaluation of the possibilities and limitations of infrared/thermographic human temperature measurement. A short review of the use of infrared temperature measurement in medical applications is provided. Experiments and statistics-based evaluation to confirm the expected accuracy and limits of thermography-based human temperature measurement are introduced. The results presented in this study show that the standard deviation of the thermographic measurement of the eyes maximum temperature was 0.4-0.9 °C and the mean values differences from the armpit measurement were up to 0.5 °C, based on the used IR camera, even though near ideal measurement conditions and permanent blackbody correction were used. It was also shown that a certain number of outliers must be assumed in such measurements. Extended analyses including simulations of true negative/false positive, sensitivity/specificity and receiver operating characteristics (ROC) curves are presented. The statistical evaluation as well as the extended analyses show that maximum eyes temperature is more relevant than a forehead temperature examination.

Assessment of Alternative Body Points for Temperature Screening As Precautionary Screening During the Pandemic Using Infrared Thermometry

BACKGROUND

The recent coronavirus disease 2019 (COVID-19) pandemic, which swept across the globe in a short period, demonstrated that disease transmission management is a critical step in preventing an outbreak, as is good viral infectious disease screening. Infrared thermography (IRT) has long been considered ideal for screening body temperatures during pandemics.

METHODS

Single-centre cross-sectional study with 159 participants. Using infrared thermometry, participants were subjected to temperature measurement twice daily on various sites. This was compared to oral temperature.

RESULTS

The findings of the study revealed that infrared thermometry could be utilised as a proxy approach for screening by both individuals and medical professionals when employed at the glabella, cubits, or axillae.

CONCLUSION

 Temperature screening is implied as a prophylactic method during pandemics. Owing to contact limitations, oral thermometry cannot be used for mass screening during the pandemic. Infrared thermometry is a noncontact method of temperature screening that can readily be applied for mass temperature screening in congested venues such as airports, shopping malls, places of public convenience, and other similar locations.

Infrared thermography as a modality for tracking cutaneous temperature change and post-mortem interval in the critical care setting

PURPOSE

To evaluate the potential use of cutaneous facial temperature change as measured by an infrared camera as a marker of postmortem interval (PMI) in the minutes immediately following death.

METHODS

This was a prospective, observational pilot study using a convenience sample of all deaths which occurred in a room in an Intensive Care Unit equipped with a ceiling mounted thermal camera. Cutaneous temperature measurements were taken from 60 min antemortem to as long as possible postmortem.

RESULTS

A total of 134 separate measurements was taken from 5 patients, with 65 occurring antemortem, and 69 occurring post-mortem. The longest recorded post-mortem time was 130 min. A Kruskal-Wallis ANOVA testing the hypothesis that there was a difference in facial temperature at each of the different timepoints showed significance (p = 0.029). Post-Hoc comparisons were then performed to compare median temperature values at each timeframe to the baseline value. Compared to baseline, there was a significant difference in facial temperature at 30, 60, and 90 min (p = 0.007, p = 0.01, p = 0.016) (Table 2).

CONCLUSION

There is a statistically significant cutaneous facial temperature change in patients immediately following death as measured by a thermal camera. There is potential for infrared thermography to identify changes immediately before and after death in environments where traditional temperature measurement cannot be accomplished. More work needs to be done to confirm whether a precise postmortem interval (PMI) could be derived from these values.

An Overview of Thermal Infrared Imaging-Based Screenings during Pandemic Emergencies

Infrared thermal imaging (IRI) is a contact-less technology able to monitor human skin temperature for biomedical applications and in real-life contexts. Its capacity to detect fever was exploited for mass screening during past epidemic emergencies as well as for the current COVID-19 pandemic. However, the only assessment of fever may not be selective for the Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2) infection. Hence, novel approaches for IRI data analysis have been investigated. The present review aims to describe how IRI have been employed during the last epidemics, highlighting the potentialities and the limitations of this technology to contain the contagions. Specifically, the methods employed for automatic face recognition and fever assessment and IRI's performances in mass screening at airports and hospitals are reviewed. Moreover, an overview of novel machine learning methods for IRI data analysis, aimed to identify respiratory diseases, is provided. In addition, IRI-based smart technologies developed to support the healthcare during the COVID-19 pandemic are described. Finally, relevant guidelines to fully exploit IRI for COVID-19 identification are defined, to improve the effectiveness of IRI in the detection of the SARS-CoV-2 infection.

[Screening of febrile cows using a small handheld infrared thermography device]

OBJECTIVE

As dairy herds increase in size, close monitoring of health becomes a necessity, but this is expensive and labour-intensive. Early detection of febrile diseases is essential for economical and welfare reasons and to prevent the spread of disease. The goal of this study was therefore to evaluate a mobile, non-invasive technique for measuring the body temperature of cows that precludes the need for restraint of the animals.

MATERIALS AND METHODS

An infrared thermographic imaging camera installed on a smart phone was used to measure the surface temperature of cows. In experiment 1, a metal block heated to defined temperatures was used to obtain infrared thermographic measurements (THM). The accuracy of THM made at different distances from the block and at 2 different ambient temperatures was determined. In experiment 2, non-febrile cows underwent infrared thermographic imaging, and the body regions with the highest correlations between thermographic and rectal temperature were identified. In experiment 3, THM were made in febrile and neighbouring non-febrile cows.

RESULTS

In experiment 1, the thermographic and true temperatures of the block had the strongest relationships at 0.5 and 1.0 m (r = 0.98). The ambient temperature had a significant effect on the THM, which had larger variations and greater deviations from the block temperature at 14.8 °C than at 23.8 °C. In experiment 2, the maximum temperature at the eye (r = 0.37), THM at the muzzle (r = 0.28) and the medial canthus (r = 0.27) showed the strongest relationships with the rectal temperature. After correcting the THM with the mean difference between thermographic and rectal temperatures of the non-febrile cows, sensitivities of 88, 90 and 82 %, respectively, were calculated for THM at the muzzle, eye and medial canthus in febrile cows in experiment 3. The corresponding specificities were 6, 23 and 32 %.

CONCLUSION AND CLINICAL RELEVANCE

Based on the low specificities of the infrared THM, the thermographic imaging camera has limited usefulness for the mass screening of dairy cows for febrile conditions. Cattle falsely identified as febrile need to be separated, caught and re-examined, which causes unnecessary stress to the animal and increases labour input.

A Movement Detection System Using Continuous-Wave Doppler Radar Sensor and Convolutional Neural Network to Detect Cough and Other Gestures

The 2019 coronavirus disease (COVID-19) pandemic has contaminated millions of people, resulting in high fatality rates. Recently emerging artificial intelligence technologies like the convolutional neural network (CNN) are strengthening the power of imaging tools and can help medical specialists. CNN combined with other sensors creates a new solution to fight COVID-19 transmission. This paper presents a novel method to detect coughs (an important symptom of COVID-19) using a K-band continuous-wave Doppler radar with most popular CNNs architectures: AlexNet, VGG-19, and GoogLeNet. The proposed method has cough detection test accuracy of 88.0% using AlexNet CNN with people 1 m away from the microwave radar sensor, test accuracy of 80.0% with people 3 m away from the radar sensor, and test accuracy of 86.5% with a single mixed dataset with people 1 m and 3 m away from the radar sensor. The K-band radar sensor is inexpensive, completely camera-free and collects no personally-identifying information, allaying privacy concerns while still providing in-depth public health data on individual, local, and national levels. Additionally, the measurements are conducted without human contact, making the process proposed in this work safe for the investigation of contagious diseases such as COVID-19. The proposed cough detection system using microwave radar sensor has environmental robustness and dark/light-independence, unlike traditional cameras. The proposed microwave radar sensor can be used alone or in group with other sensors in a fusion sensor system to create a robust system to detect cough and other movements, mainly if using CNNs.

Diagnostic accuracy of non-contact infrared thermometers and thermal scanners: a systematic review and meta-analysis

Infrared thermal screening, via the use of handheld non-contact infrared thermometers (NCITs) and thermal scanners, has been widely implemented all over the world. We performed a systematic review and meta-analysis to investigate its diagnostic accuracy for the detection of fever. We searched PubMed, Embase, the Cochrane Library, medRxiv, bioRxiv, ClinicalTrials.gov, COVID-19 Open Research Dataset, COVID-19 research database, Epistemonikos, EPPI-Centre, World Health Organization International Clinical Trials Registry Platform, Scopus and Web of Science databases for studies where a non-contact infrared device was used to detect fever against a reference standard of conventional thermometers. Forest plots and Hierarchical Summary Receiver Operating Characteristics curves were used to describe the pooled summary estimates of sensitivity, specificity and diagnostic odds ratio. From a total of 1063 results, 30 studies were included in the qualitative synthesis, of which 19 were included in the meta-analysis. The pooled sensitivity and specificity were 0.808 (95%CI 0.656-0.903) and 0.920 (95%CI 0.769-0.975), respectively, for the NCITs (using forehead as the site of measurement), and 0.818 (95%CI 0.758-0.866) and 0.923 (95%CI 0.823-0.969), respectively, for thermal scanners. The sensitivity of NCITs increased on use of rectal temperature as the reference. The sensitivity of thermal scanners decreased in a disease outbreak/pandemic setting. Changes approaching statistical significance were also observed on the exclusion of neonates from the analysis. Thermal screening had a low positive predictive value, especially at the initial stage of an outbreak, whereas the negative predictive value (NPV) continued to be high even at later stages. Thermal screening has reasonable diagnostic accuracy in the detection of fever, although it may vary with changes in subject characteristics, setting, index test and the reference standard used. Thermal screening has a good NPV even during a pandemic. The policymakers must take into consideration the factors surrounding the screening strategy while forming ad-hoc guidelines.

Return to school in the COVID-19 era: considerations for temperature measurement

COVID-19 pandemics required a reorganisation of social spaces to prevent the spread of the virus. Due to the common presence of fever in the symptomatic patients, temperature measurement is one of the most common screening protocols. Indeed, regulations in many countries require temperature measurements before entering shops, workplaces, and public buildings. Due to the necessity of providing rapid non-contact and non-invasive protocols to measure body temperature, infra-red thermometry is mostly used. Many countries are now facing the need to organise the return to school and universities in the COVID-19 era, which require solutions to prevent the risk of contagion between students and/or teachers and technical/administrative staff. This paper highlights and discusses some of the strengths and limitations of infra-red cameras, including the site of measurements and the influence of the environment, and recommends to be careful to consider such measurements as a single "safety rule" for a good return to normality.

Infection Screening System Using Thermography and CCD Camera with Good Stability and Swiftness for Non-contact Vital-Signs Measurement by Feature Matching and MUSIC Algorithm

Screening systems for infectious diseases based on fever have been implemented at international airports to prevent the spread of infection for over a decade. Currently, only Infrared Thermography (IRT) is used for screening and measuring facial skin temperature, which is one of clinical indicators of potential infection. Aiming at higher accuracy in screening, our group adopted heart rate (HR) and respiration rate (RR) for the first time as the new screening parameters. In our previous study, we proposed a screening system based on dual image sensors, which include IRT and a charged-coupled devices (CCD) camera. The sensors can measure three vital signs simultaneously, namely HR, RR, and facial skin temperature. For the measurement of RR in this system, stability and swiftness must be applied for application in airports. In this study, we introduce feature matching and multiple signal classification (MUSIC) algorithm in this system. Feature matching between thermal images and RGB images captured by a CCD camera and IRT, respectively, is used to detect the nose and mouth in IRT, which helps extract respiration signals corresponding to airflow from breathing. In addition, the MUSIC algorithm improves the accuracy of RR frequency estimations in limited time respiration signal and achieves swiftness. The proposed method improves stability by simultaneously detecting the nose and mouth in thermal images, and enhances the accuracy of estimated RR using the MUSIC algorithm. By using this system, we evaluate the accuracy of the estimated vital signs. The performance of this screening system was evaluated using data obtained from 12 influenza patients and 13 healthy subjects at a clinical facility in Fukushima, Japan.

Contactless Vital Signs Measurement System Using RGB-Thermal Image Sensors and Its Clinical Screening Test on Patients with Seasonal Influenza

Background: In the last two decades, infrared thermography (IRT) has been applied in quarantine stations for the screening of patients with suspected infectious disease. However, the fever-based screening procedure employing IRT suffers from low sensitivity, because monitoring body temperature alone is insufficient for detecting infected patients. To overcome the drawbacks of fever-based screening, this study aims to develop and evaluate a multiple vital sign (i.e., body temperature, heart rate and respiration rate) measurement system using RGB-thermal image sensors. Methods: The RGB camera measures blood volume pulse (BVP) through variations in the light absorption from human facial areas. IRT is used to estimate the respiration rate by measuring the change in temperature near the nostrils or mouth accompanying respiration. To enable a stable and reliable system, the following image and signal processing methods were proposed and implemented: (1) an RGB-thermal image fusion approach to achieve highly reliable facial region-of-interest tracking, (2) a heart rate estimation method including a tapered window for reducing noise caused by the face tracker, reconstruction of a BVP signal with three RGB channels to optimize a linear function, thereby improving the signal-to-noise ratio and multiple signal classification (MUSIC) algorithm for estimating the pseudo-spectrum from limited time-domain BVP signals within 15 s and (3) a respiration rate estimation method implementing nasal or oral breathing signal selection based on signal quality index for stable measurement and MUSIC algorithm for rapid measurement. We tested the system on 22 healthy subjects and 28 patients with seasonal influenza, using the support vector machine (SVM) classification method. Results: The body temperature, heart rate and respiration rate measured in a non-contact manner were highly similarity to those measured via contact-type reference devices (i.e., thermometer, ECG and respiration belt), with Pearson correlation coefficients of 0.71, 0.87 and 0.87, respectively. Moreover, the optimized SVM model with three vital signs yielded sensitivity and specificity values of 85.7% and 90.1%, respectively. Conclusion: For contactless vital sign measurement, the system achieved a performance similar to that of the reference devices. The multiple vital sign-based screening achieved higher sensitivity than fever-based screening. Thus, this system represents a promising alternative for further quarantine procedures to prevent the spread of infectious diseases.

Incremental Low Rank Noise Reduction for Robust Infrared Tracking of Body Temperature during Medical Imaging

Thermal imagery for monitoring of body temperature provides a powerful tool to decrease health risks (e.g., burning) for patients during medical imaging (e.g., magnetic resonance imaging). The presented approach discusses an experiment to simulate radiology conditions with infrared imaging along with an automatic thermal monitoring/tracking system. The thermal tracking system uses an incremental low-rank noise reduction applying incremental singular value decomposition (SVD) and applies color based clustering for initialization of the region of interest (ROI) boundary. Then a particle filter tracks the ROI(s) from the entire thermal stream (video sequence). The thermal database contains 15 subjects in two positions (i.e., sitting, and lying) in front of thermal camera. This dataset is created to verify the robustness of our method with respect to motion-artifacts and in presence of additive noise (2–20%—salt and pepper noise). The proposed approach was tested for the infrared images in the dataset and was able to successfully measure and track the ROI continuously (100% detecting and tracking the temperature of participants), and provided considerable robustness against noise (unchanged accuracy even in 20% additive noise), which shows promising performance.

Stable Contactless Sensing of Vital Signs Using RGB-Thermal Image Fusion System with Facial Tracking for Infection Screening

Infrared thermography (IRT) has been used to screen febrile passengers in international airports for over a decade. However, fever-based infection screening using IRT suffered from low sensitivity because measurements can be affected by ambient temperature, humidity, etc. In our previous study, we proposed an RGB-thermal image fusion system to measure vital signs i.e., the RGB camera detects tiny changes in color from facial skin, associated with blood flow, to estimate heart rate, and IRT senses temperature changes around the nasal area, caused by respiration, to measure respiratory rate). The inclusion of heart and respiratory rates lead to increased screening accuracy. In the present study, to promote the widespread use of our system in real-world settings, a face detection and tracking method was developed and implemented into the system, thereby enabling the accurate and stable measurement of vital signs. We assessed heart and respiratory rate estimation via an RGB-thermal image fusion system using Bland-Altman plots and statistical analysis.

Infrared thermography and behavioral biometrics associated with estrus indicators and ovulation in estrus-synchronized dairy cows housed in tiestalls

Most Canadian dairy herds operate in tiestall housing (61%), where average estrus detection rates may be lower than 54%. The objective of this study was to evaluate infrared thermography and behavioral biometrics as indicators of estrus in dairy cows. Eighteen cyclic multiparous cows (Synch) were subjected to an estrus synchronization protocol, and 18 pregnant cows (control) received a sham protocol on the same schedule and frequency as the cyclic cow treatment. A decline in plasma concentrations of progesterone and the appearance of a dominant follicle using transrectal ultrasonography were used as indirect indicators of estrus, and the disappearance of a dominant follicle was used to confirm ovulation. All cows were monitored via visual cameras to determine the frequency of treading, drinking, neighbor interaction, tail movement, lying, and shifting behaviors. Infrared thermograms were recorded at the eye, muzzle, cheek, neck, front right foot, front left foot, rump, flank, vulva area, tail head, and withers. To evaluate the accuracy of behavioral and thermal parameters, a predefined minimum acceptable value (i.e., threshold) for estrus alerts (>0.30 Youden J index and >0.60 area under the curve) was used. Ovulation was confirmed in 14 (77.7%) out of 18 Synch cows. Eye, cheek, neck, rump, flank, vulva area, and wither thermograms exhibited higher temperatures at 48 h [cycle threshold (Δt) = +0.30 to 1.20°C] and 24 h before ovulation compared with 4 d prior to ovulation (Δt = 0.06 to 0.11°C) and during ovulation day (Δt = 0.03 to 0.32°C) in the Synch group. In addition, control cows exhibited greater treading activity per day compared with Synch cows (20.84 ± 0.39 vs. 16.35 events/5 min ± 0.34), and tail movement frequency was greater in Synch cows compared with control cows (14.84 ± 2.7 vs. 10.11 ± 4.7 events/5 min). However, within Synch cows, tail movement was the only behavior that significantly increased in frequency 2 d before ovulation (11.81 ± 1.71 events/5 min) followed by a decrease in frequency 1 d before ovulation (4.67 ± 1.05 events/5 min) compared with ovulation day (0 d; 6.10 ± 1.25 events/5 min) and during luteolysis (3 d before ovulation; 6.01 ± 1.25 events/5 min). Upon evaluation of all variables (thermograms and behavior frequencies) as estrus indicators at 48 and 24 h before ovulation, treading and tail movements before milking and 9 thermal locations satisfied the predefined minimum acceptable value for estrus alerts. This study demonstrates that fluctuations in radiated temperature measured at specific anatomical locations and the frequency of tail movements and treading behaviors can be used as a noninvasive estrus alerts in multiparous cows housed in a tiestall system.

Infrared thermography measured body surface temperature and its relationship with rectal temperature in dairy cows under different temperature-humidity indexes

The aim of this study was to better understand the inflection point of RT and BSTs and measure different body surface temperatures (BSTs) under different temperature-humidity index (THI) conditions. A total of 488 Holstein dairy cows were chosen to manually measure rectal temperature (RT) and BSTs including left side of eye, ear, cheek, forehead, flank, rump, fore udder, and rear udder by infrared thermography for 14 times. Those measurements included six times under high THI (THI > 78), three times under moderate THI (72 ≤ THI ≤ 78), and five times under low THI (THI < 72). Results showed that BSTs were affected by THI conditions (P < 0.01). The THI conditions where mean and maximum forehead temperatures started to increase rapidly (71.4 and 66.8) were lower than that where RT started to increase rapidly (74.1). The correlation coefficients of mean and maximum forehead temperatures to THI were 0.808 and 0.740, and were 0.557 and 0.504 to RT, all showing the highest as compared to other region temperatures with THI and RT, respectively. Thus, we conclude that BSTs are more sensitive to thermal environment than RT, suggesting the variability of BST to reflect body core temperature. In addition, the forehead is a relatively reliable region to assess the heat stress reflecting RT compared to the eye, ear, cheek, flank, rump, fore udder, and rear udder regions.

A pilot study of the Leicester ED medical infrared imaging protocol in fever and sepsis

BACKGROUND

Medical Infrared Imaging (MII) is an investigative method that can be potentially used in emergency care to non-invasively detect thermal signatures associated with change in blood flow. We have developed a protocol for the use of MII in the Emergency Department (ED) and shown that it is feasible. To derive initial data for sample size calculations, we performed an exploratory study in patients with fever and sepsis.

METHODS

The Leicester MII protocol was used to image the temperature patterns along the arm among three patient groups (control, fever and sepsis) of a total 56 patients. Anatomical markers were used to divide this gradient into upper arm, forearm, hand and finger regions. Variations in measurements within and between these regions were described.

RESULTS

The thermal gradient down the arm was successfully extracted in all patients. The distribution of values in each region of the arm was described in control, fever and sepsis patients. There was a significant gradient between upper arm and finger in controls (2.75, p < 0.0001), but no gradient in fever (p = 0.944) or sepsis (p = 0.710). This was reflected in the finger/arm difference, which was of -2.74°C (±3.50) in controls, -0.39C (±2.48) in fever, and -1.80°C (±3.09) in sepsis.

CONCLUSIONS

This study found different thermal gradients along the arm in control and febrile groups, and defined the degree of individual variation. It is likely that the difference between upper arm temperature and finger temperature (representing the temperature gradient down the arm) may be more useful than absolute measurements in future studies.

Applications of Space Technologies to Global Health: Scoping Review

Background

Space technology has an impact on many domains of activity on earth, including in the field of global health. With the recent adoption of the United Nations’ Sustainable Development Goals that highlight the need for strengthening partnerships in different domains, it is useful to better characterize the relationship between space technology and global health.

Objective

The aim of this study was to identify the applications of space technologies to global health, the key stakeholders in the field, as well as gaps and challenges.

Methods

We used a scoping review methodology, including a literature review and the involvement of stakeholders, via a brief self-administered, open-response questionnaire. A distinct search on several search engines was conducted for each of the four key technological domains that were previously identified by the UN Office for Outer Space Affairs’ Expert Group on Space and Global Health (Domain A: remote sensing; Domain B: global navigation satellite systems; Domain C: satellite communication; and Domain D: human space flight). Themes in which space technologies are of benefit to global health were extracted. Key stakeholders, as well as gaps, challenges, and perspectives were identified.

Results

A total of 222 sources were included for Domain A, 82 sources for Domain B, 144 sources for Domain C, and 31 sources for Domain D. A total of 3 questionnaires out of 16 sent were answered. Global navigation satellite systems and geographic information systems are used for the study and forecasting of communicable and noncommunicable diseases; satellite communication and global navigation satellite systems for disaster response; satellite communication for telemedicine and tele-education; and global navigation satellite systems for autonomy improvement, access to health care, as well as for safe and efficient transportation. Various health research and technologies developed for inhabited space flights have been adapted for terrestrial use.

Conclusions

Although numerous examples of space technology applications to global health exist, improved awareness, training, and collaboration of the research community is needed.

Optimising lameness detection in dairy cattle by using handheld infrared thermometers

Lameness is one of the most serious economic and welfare issues in the dairy industry. Early detection of lameness can be difficult, but provision of early treatment is crucial. Previous studies have used infrared thermography to show that increased foot temperature (FT) is associated with lameness and foot lesions. However, poor accuracy has limited the management application potential. This study analysed ambient-temperature (AT)-adjusted foot-surface temperatures and temperature differences between the hind feet of individual cows to enhance lameness detection. Cow FTs were recorded on a 990-cow farm using an infrared thermometer fortnightly for 6 months. Additionally, mobility level was scored using the AHDB Dairy 4-point scale. The averages of FTs and ATs were 23.83 ± 0.03°C and 13.99 ± 1.60°C, respectively. The FT of cows with lameness was significantly higher than that of cows without lameness (P < 0.001). Increases in FTs correlated with the mobility score (MS) (P < 0.001). According to receiver operating characteristic (ROC) curves, the optimal threshold based on actual FTs was 23.3°C with 78.5% sensitivity and 39.2% specificity. However, the ROC curve for the AT-adjusted FT and FT difference parameters showed minimal improvements over the FT in detecting lameness. In conclusion, the infrared thermometer results demonstrated the association between elevated FTs and lameness, but further improvements to this detection technique will be required before it can be implemented as a management tool for detecting cows that could benefit from treatment. With additional validation, the technique could be used as a screening device to identify cows in need of further assessment.

A Survey on Computer Vision for Assistive Medical Diagnosis From Faces

Automatic medical diagnosis is an emerging center of interest in computer vision as it provides unobtrusive objective information on a patient's condition. The face, as a mirror of health status, can reveal symptomatic indications of specific diseases. Thus, the detection of facial abnormalities or atypical features is at upmost importance when it comes to medical diagnostics. This survey aims to give an overview of the recent developments in medical diagnostics from facial images based on computer vision methods. Various approaches have been considered to assess facial symptoms and to eventually provide further help to the practitioners. However, the developed tools are still seldom used in clinical practice, since their reliability is still a concern due to the lack of clinical validation of the methodologies and their inadequate applicability. Nonetheless, efforts are being made to provide robust solutions suitable for healthcare environments, by dealing with practical issues such as real-time assessment or patients positioning. This survey provides an updated collection of the most relevant and innovative solutions in facial images analysis. The findings show that with the help of computer vision methods, over 30 medical conditions can be preliminarily diagnosed from the automatic detection of some of their symptoms. Furthermore, future perspectives, such as the need for interdisciplinary collaboration and collecting publicly available databases, are highlighted.

Body temperature in premature infants during the first week of life: Exploration using infrared thermal imaging

BACKGROUND

Hypothermia is a problem for very premature infants after birth and leads to increased morbidity and mortality. Previously we found very premature infants exhibit abnormal thermal patterns, keeping foot temperatures warmer than abdominal temperatures for their first 12h of life.

PURPOSE

We explored the utility of infrared thermography as a non-invasive method for measuring body temperature in premature infants in an attempt to regionally examine differential temperatures.

RESULTS

Our use of infrared imaging to measure abdominal and foot temperature for extremely premature infants in heated, humid incubators was successful and in close agreement using Bland and Altman technique with temperatures measured by skin thermistors.

CONCLUSIONS

Our study methods demonstrated that it was feasible to capture full body temperatures of extremely premature infants while they were resting in a heated, humid incubator using a Flir SC640 infrared camera. This technology offers researchers and clinicians a method to examine acute changes in perfusion differentials in premature infants which may lead to morbidity.

Applications of Infrared Thermography for Noncontact and Noninvasive Mass Screening of Febrile International Travelers at Airport Quarantine Stations

Infrared thermography (IRT), one of the most valuable tools, is used for noncontact, noninvasive, and rapid monitoring of body temperature; this has been used for mass screening of febrile travelers at places such as airport quarantine stations for over 10 years after the 2003 severe acute respiratory syndrome (SARS) outbreak. The usefulness of thermography for mass screening has been evaluated in many recent studies; its sensitivity varies from 40 to 89.4% under various circumstances. In this chapter, we perform IRT evaluations for detecting febrile international travelers entering Japan at Nagoya Airport, immediately after the SARS epidemic, from June 2003 to February 2004, and at Naha International Airport from April 2005 to March 2009. The correlation of body surface temperature measured via thermography with the axillary temperature was significant. Through IRT, febrile individuals were detected with good accuracy and the detection accuracy was improved by corroborating surveillance with self-reporting questionnaires. However, there are several limitations associated with the use of IRT for fever screening. For instance, taking antifebrile medications results in rapid modification of the body temperature and directly affects the efficiency of IRT. To solve this unreliability and obtain higher accuracy in mass screening, we have developed a novel infection screening system using multisensor data, i.e., heart and respiration rates are determined by microwave radar in noncontact manner and facial skin temperature is monitored through IRT. The detection accuracy of the system improved, which is notably higher compared to the conventional screening method using only IRT.

Remote sensing of multiple vital signs using a CMOS camera-equipped infrared thermography system and its clinical application in rapidly screening patients with suspected infectious diseases

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Remotely monitoring multiple vital signs is proposed for rapid infection screening.

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Vital-sign-based infrared thermography is more sensitive than conventional systems.

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The proposed method will provide an alternative to conventional screening.

Background

Infrared thermography (IRT) is used to screen febrile passengers at international airports, but it suffers from low sensitivity. This study explored the application of a combined visible and thermal image processing approach that uses a CMOS camera equipped with IRT to remotely sense multiple vital signs and screen patients with suspected infectious diseases.

Methods

An IRT system that produced visible and thermal images was used for image acquisition. The subjects’ respiration rates were measured by monitoring temperature changes around the nasal areas on thermal images; facial skin temperatures were measured simultaneously. Facial blood circulation causes tiny color changes in visible facial images that enable the determination of the heart rate. A logistic regression discriminant function predicted the likelihood of infection within 10 s, based on the measured vital signs. Sixteen patients with an influenza-like illness and 22 control subjects participated in a clinical test at a clinic in Fukushima, Japan.

Results

The vital-sign-based IRT screening system had a sensitivity of 87.5% and a negative predictive value of 91.7%; these values are higher than those of conventional fever-based screening approaches.

Conclusions

Multiple vital-sign-based screening efficiently detected patients with suspected infectious diseases. It offers a promising alternative to conventional fever-based screening.

Automated assessment and tracking of human body thermal variations using unsupervised clustering

The presented approach addresses a review of the overheating that occurs during radiological examinations, such as magnetic resonance imaging, and a series of thermal experiments to determine a thermally suitable fabric material that should be used for radiological gowns. Moreover, an automatic system for detecting and tracking of the thermal fluctuation is presented. It applies hue-saturated-value-based kernelled k-means clustering, which initializes and controls the points that lie on the region-of-interest (ROI) boundary. Afterward, a particle filter tracks the targeted ROI during the video sequence independently of previous locations of overheating spots. The proposed approach was tested during experiments and under conditions very similar to those used during real radiology exams. Six subjects have voluntarily participated in these experiments. To simulate the hot spots occurring during radiology, a controllable heat source was utilized near the subject's body. The results indicate promising accuracy for the proposed approach to track hot spots. Some approximations were used regarding the transmittance of the atmosphere, and emissivity of the fabric could be neglected because of the independence of the proposed approach for these parameters. The approach can track the heating spots continuously and correctly, even for moving subjects, and provides considerable robustness against motion artifact, which occurs during most medical radiology procedures.

Veterinary applications of infrared thermography

Abnormal body temperature is a major indicator of disease; infrared thermography (IRT) can assess changes in body surface temperature quickly and remotely. This technology can be applied to a myriad of diseases of various etiologies across a wide range of host species in veterinary medicine. It is used to monitor the physiologic status of individual animals, such as measuring feed efficiency or diagnosing pregnancy. Infrared thermography has applications in the assessment of animal welfare, and has been used to detect soring in horses and monitor stress responses. This review addresses the variety of uses for IRT in veterinary medicine, including disease detection, physiologic monitoring, welfare assessment, and potential future applications.

Comparison of Infrared Thermal Detection Systems for mass fever screening in a tropical healthcare setting

Objectives

Fever screening systems, such as Infrared Thermal Detection Systems (ITDS), have been used for rapid identification of potential cases during respiratory disease outbreaks for public health management. ITDS detect a difference between the subject and ambient temperature, making deployment in hot climates more challenging. This study, conducted in Singapore, a tropical city, evaluates the accuracy of three different ITDS for fever detection compared with traditional oral thermometry and self-reporting in a clinical setting.

Study design

This study is a prospective operational evaluation conducted in the Singapore military on all personnel seeking medical care at a high-volume primary healthcare centre over a one week period in February 2014.

Methods

Three ITDS, the STE Infrared Fever Screening System (IFSS), the Omnisense Sentry MKIII and the handheld Quick Shot Infrared Thermoscope HT-F03B, were evaluated. Temperature measurements were taken outside the healthcare centre, under a sheltered walkway and compared to oral temperature. Subjects were asked if they had fever.

Results

There were 430 subjects screened, of whom 34 participants (7.9%) had confirmed fever, determined by oral thermometer measurement. The handheld infrared thermoscope had a very low sensitivity (29.4%), but a high specificity (96.8%). The STE ITDS had a moderate sensitivity (44.1%), but a very high specificity (99.1%). Self-reported fevers showed good sensitivity (88.2%) and specificity (93.9%). The sensitivity of the Omnisense ITDS (89.7%) was the highest among the three methods with good specificity (92.0%).

Conclusion

The new generation Omnisense ITDS displayed a relatively high sensitivity and specificity for fever. Though it has a lower sensitivity, the old generation STE ITDS system showed a very high specificity. Self-reporting of fever was reliable. The handheld thermograph should not be used as a fever-screening tool under tropical conditions.

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The new generation fever screening system displayed a relatively high sensitivity and specificity for fever.

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Self-reporting of fever was reliable compared to measured temperature.

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The handheld thermograph should not be used as a fever-screening tool under tropical conditions.

An infectious disease/fever screening radar system which stratifies higher-risk patients within ten seconds using a neural network and the fuzzy grouping method

Objectives

To classify higher-risk influenza patients within 10 s, we developed an infectious disease and fever screening radar system.

Methods

The system screens infected patients based on vital signs, i.e., respiration rate measured by a radar, heart rate by a finger-tip photo-reflector, and facial temperature by a thermography. The system segregates subjects into higher-risk influenza (HR-I) group, lower-risk influenza (LR-I) group, and non-influenza (Non-I) group using a neural network and fuzzy clustering method (FCM). We conducted influenza screening for 35 seasonal influenza patients and 48 normal control subjects at the Japan Self-Defense Force Central Hospital. Pulse oximetry oxygen saturation (SpO₂) was measured as a reference.

Results

The system classified 17 subjects into HR-I group, 26 into LR-I group, and 40 into Non-I group. Ten out of the 17 HR-I subjects indicated SpO₂ <96%, whereas only two out of the 26 LR-I subjects showed SpO₂ <96%. The chi-squared test revealed a significant difference in the ratio of subjects showed SpO₂ <96% between HR-I and LR-I group (p < 0.001). There were zero and nine normal control subjects in HR-I and LR-I groups, respectively, and there was one influenza patient in Non-I group.

Conclusions

The combination of neural network and FCM achieved efficient detection of higher-risk influenza patients who indicated SpO₂ 96% within 10 s.

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A novel infectious disease/fever screening radar system stratifies higher-risk patients within ten seconds.

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Use of an optimal neural network and the fuzzy clustering method to classify multiple-dimensional vital signs data.

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The system can be used for preventing secondary exposure of physicians during outbreaks of infectious disease.

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The system has potential to serve as a helpful tool for rapid mass screening of infectious disease.

Application of infrared thermography in computer aided diagnosis

The invention of thermography, in the 1950s, posed a formidable problem to the research community: What is the relationship between disease and heat radiation captured with Infrared (IR) cameras? The research community responded with a continuous effort to find this crucial relationship. This effort was aided by advances in processing techniques, improved sensitivity and spatial resolution of thermal sensors. However, despite this progress fundamental issues with this imaging modality still remain. The main problem is that the link between disease and heat radiation is complex and in many cases even non-linear. Furthermore, the change in heat radiation as well as the change in radiation pattern, which indicate disease, is minute. On a technical level, this poses high requirements on image capturing and processing. On a more abstract level, these problems lead to inter-observer variability and on an even more abstract level they lead to a lack of trust in this imaging modality. In this review, we adopt the position that these problems can only be solved through a strict application of scientific principles and objective performance assessment. Computing machinery is inherently objective; this helps us to apply scientific principles in a transparent way and to assess the performance results. As a consequence, we aim to promote thermography based Computer-Aided Diagnosis (CAD) systems. Another benefit of CAD systems comes from the fact that the diagnostic accuracy is linked to the capability of the computing machinery and, in general, computers become ever more potent. We predict that a pervasive application of computers and networking technology in medicine will help us to overcome the shortcomings of any single imaging modality and this will pave the way for integrated health care systems which maximize the quality of patient care.

Development of an infection screening system for entry inspection at airport quarantine stations using ear temperature, heart and respiration rates

After the outbreak of severe acute respiratory syndrome (SARS) in 2003, many international airport quarantine stations conducted fever-based screening to identify infected passengers using infrared thermography for preventing global pandemics. Due to environmental factors affecting measurement of facial skin temperature with thermography, some previous studies revealed the limits of authenticity in detecting infectious symptoms. In order to implement more strict entry screening in the epidemic seasons of emerging infectious diseases, we developed an infection screening system for airport quarantines using multi-parameter vital signs. This system can automatically detect infected individuals within several tens of seconds by a neural-network-based discriminant function using measured vital signs, i.e., heart rate obtained by a reflective photo sensor, respiration rate determined by a 10-GHz non-contact respiration radar, and the ear temperature monitored by a thermography. In this paper, to reduce the environmental effects on thermography measurement, we adopted the ear temperature as a new screening indicator instead of facial skin. We tested the system on 13 influenza patients and 33 normal subjects. The sensitivity of the infection screening system in detecting influenza were 92.3%, which was higher than the sensitivity reported in our previous paper (88.0%) with average facial skin temperature.

Fever screening of seasonal influenza patients using a cost-effective thermopile array with small pixels for close-range thermometry

Objective

Infrared thermography systems have been used for fever screening at many airports since the outbreak of severe acute respiratory syndrome (SARS) in 2003. However, many of these systems are expensive and non-portable. Therefore, we developed a cost-effective and compact (2.9 × 5.8 × 2.0 cm) thermopile array for fever screening of patients with infectious diseases in the clinical setting.

Methods

The array was created with small pixels (48 × 47 = 2256 pixels) fabricated on a silicon wafer using microelectromechanical systems technology. We tested this array on 155 febrile and afebrile patients (35.4 °C ≤ axillary temperature ≤ 39.3 °C) with seasonal influenza at the Japan Self-Defense Forces Central Hospital.

Results

The maximum facial temperature, measured by the array at 0.3 m from the subject, exhibited a positive correlation with axillary temperature measured using a contact-type thermometer (r = 0.71, p < 0.01). The sensitivity and specificity of the thermopile array in identifying the febrile subjects were 80.5% and 93.3%, respectively, setting the threshold cut-off of maximum facial temperature at an appropriate value.

Conclusions

Our cost-effective thermopile array appears promising for future close-range fever screening of patients with infectious diseases at primary care doctor clinics, health care centers, and quarantine stations in developing and developed countries.

Rapid screening for influenza using a multivariable logistic regression model to save labor at a clinic in Iwaki, Fukushima, Japan

To lighten the workload of health care professionals, we conducted a clinical test of a newly developed automated infection screening system using a multivariable logistic regression model. The system was tested with 44 influenza patients and 45 healthy control subjects based on 3 vital signs: facial temperature, heart rate and respiratory rate. The system showed a high accuracy for distinguishing influenza patients from control subjects within 15 seconds.

Investigation of various essential factors for optimum infrared thermography

We investigated various essential factors for optimum infrared thermography for cattle clinics. The effect of various factors on the detection of surface temperature was investigated in an experimental room with a fixed ambient temperature using a square positioned on a wall. Various factors of animal objects were examined using cattle to determine the relationships among presence of hair, body surface temperature, surface temperature of the eyeball, the highest temperature of the eye circle, rectum temperature and ambient temperature. Also, the surface temperature of the flank at different time points after eating was examined. The best conditions of thermography for cattle clinics were determined and were as follows: (1) The distance between a thermal camera and an object should be fixed, and the camera should be set within a 45-degree angle with respect to the objects using the optimum focal length. (2) Factors that affect the camera temperature, such as extreme cold or heat, direct sunshine, high humidity and wind, should be avoided. (3) For the comparison of thermographs, imaging should be performed under identical conditions. If this is not achievable, hairless parts should be used.

Medical applications of infrared thermography: A review

Abnormal body temperature is a natural indicator of illness. Infrared thermography (IRT) is a fast, passive, non-contact and non-invasive alternative to conventional clinical thermometers for monitoring body temperature. Besides, IRT can also map body surface temperature remotely. Last five decades witnessed a steady increase in the utility of thermal imaging cameras to obtain correlations between the thermal physiology and skin temperature. IRT has been successfully used in diagnosis of breast cancer, diabetes neuropathy and peripheral vascular disorders. It has also been used to detect problems associated with gynecology, kidney transplantation, dermatology, heart, neonatal physiology, fever screening and brain imaging. With the advent of modern infrared cameras, data acquisition and processing techniques, it is now possible to have real time high resolution thermographic images, which is likely to surge further research in this field. The present efforts are focused on automatic analysis of temperature distribution of regions of interest and their statistical analysis for detection of abnormalities. This critical review focuses on advances in the area of medical IRT. The basics of IRT, essential theoretical background, the procedures adopted for various measurements and applications of IRT in various medical fields are discussed in this review. Besides background information is provided for beginners for better understanding of the subject.

Normal variation in thermal radiated temperature in cattle: implications for foot-and-mouth disease detection

Background

Thermal imagers have been used in a number of disciplines to record animal surface temperatures and as a result detect temperature distributions and abnormalities requiring a particular course of action. Some work, with animals infected with foot-and-mouth disease virus, has suggested that the technique might be used to identify animals in the early stages of disease. In this study, images of 19 healthy cattle have been taken over an extended period to determine hoof and especially coronary band temperatures (a common site for the development of FMD lesions) and eye temperatures (as a surrogate for core body temperature) and to examine how these vary with time and ambient conditions.

Results

The results showed that under UK conditions an animal's hoof temperature varied from 10°C to 36°C and was primarily influenced by the ambient temperature and the animal's activity immediately prior to measurement. Eye temperatures were not affected by ambient temperature and are a useful indicator of core body temperature.

Conclusions

Given the variation in temperature of the hooves of normal animals under various environmental conditions the use of a single threshold hoof temperature will be at best a modest predictive indicator of early FMD, even if ambient temperature is factored into the evaluation.

Thermoregulation and thermography in neonatal physiology and disease

INTRODUCTION

Infrared thermal imaging, or thermography, is a technique used to measure body surface temperature in the study of thermoregulation. Researchers are beginning to use this novel methodology to study cancer, peripheral vascular disease, and wound management.

METHODS

The authors tested the feasibility of using an FLIR SC640 uncooled, infrared camera to measure body temperature in neonates housed in heated, humid incubators. The authors examined thermograms to analyze distributions between central and peripheral body temperature in extremely low birth weight infants. The authors have also used this technology to examine the relationship between body temperature and development of necrotizing enterocolitis in premature infants.

RESULTS

Handheld, uncooled, infrared cameras are easy to use and produce high-quality thermograms that can be visualized in grayscale or color palettes to enhance qualitative and quantitative analyses.

CONCLUSION

Future research will benefit from the use of this noninvasive, inexpensive measurement tool. Nurse researchers can use this methodology in adult and infant populations to study temperature differentials present in pathological conditions.

Comparison of 3 infrared thermal detection systems and self-report for mass fever screening

In a hospital setting, the systems had reasonable utility for fever detection.

Despite limited evidence regarding their utility, infrared thermal detection systems (ITDS) are increasingly being used for mass fever detection. We compared temperature measurements for 3 ITDS (FLIR ThermoVision A20M [FLIR Systems Inc., Boston, MA, USA], OptoTherm Thermoscreen [OptoTherm Thermal Imaging Systems and Infrared Cameras Inc., Sewickley, PA, USA], and Wahl Fever Alert Imager HSI2000S [Wahl Instruments Inc., Asheville, NC, USA]) with oral temperatures (>100°F = confirmed fever) and self-reported fever. Of 2,873 patients enrolled, 476 (16.6%) reported a fever, and 64 (2.2%) had a confirmed fever. Self-reported fever had a sensitivity of 75.0%, specificity 84.7%, and positive predictive value 10.1%. At optimal cutoff values for detecting fever, temperature measurements by OptoTherm and FLIR had greater sensitivity (91.0% and 90.0%, respectively) and specificity (86.0% and 80.0%, respectively) than did self-reports. Correlations between ITDS and oral temperatures were similar for OptoTherm (ρ = 0.43) and FLIR (ρ = 0.42) but significantly lower for Wahl (ρ = 0.14; p<0.001). When compared with oral temperatures, 2 systems (OptoTherm and FLIR) were reasonably accurate for detecting fever and predicted fever better than self-reports.

The Ethics of Responding to a Novel Pandemic

Recent epidemics and pandemics have highlighted a number of ethical concerns about the response to the increasing threat of emerging infectious diseases. Some of these ethical concerns are very fundamental. They include why a pandemic was declared, how much clinical information can be collected for public health without threatening patient confidentiality and how to ensure fairness in the distribution of resources. We discuss these issues and suggest approaches to resolve these dilemmas as we anticipate the next pandemic. Key words: Bioethics, Emerging infectious diseases, Ethics, Influenza, Pandemic, Quarantine, SARS, Surveillance