Infrared (IR) modalities represent the only currently viable mass fever screening approaches for outbreaks of infectious disease pandemics such as Ebola virus disease and severe acute respiratory syndrome. Non-contact IR thermometers (NCITs) and IR thermographs (IRTs) have been used for fever screening in public areas such as airports. While NCITs remain a more popular choice than IRTs, there has been increasing evidences in the literature that IRTs can provide great accuracy in estimating body temperature if qualified systems are used and appropriate procedures are consistently applied. In this study, we addressed the issue of IRT qualification by implementing and evaluating a battery of test methods for objective, quantitative assessment of IRT performance based on a recent international standard (IEC 80601-2-59). We tested two commercial IRTs to evaluate their stability and drift, image uniformity, minimum resolvable temperature difference, and radiometric temperature laboratory accuracy. Based on these tests, we illustrated how experimental and data processing procedures could affect results, and suggested methods for clarifying and optimizing test methods. Overall, the insights into thermograph standardization and acquisition methods provided by this study may improve the utility of IR thermography and aid in comparing IRT performance, thus improving the potential for producing high quality disease pandemic countermeasures.

This paper describes a novel simulator to perform electromagnetic compatibility (EMC) tests for active implantable medical devices (AIMDs) with electromagnetic fields emitted by security systems. The security system simulator was developed in response to over 100 incident reports over 17 years related to the interference of AIMD's with security systems and the lack of a standardized test method. The simulator was evaluated regarding field homogeneity, signal distortion, and maximum magnetic field strength levels. Small three-axis probes and a three-axis scanning system were designed to determine the spatial and temporal characteristics of the fields emitted by 12 different types of walk through metal detectors (WTMDs). Tests were performed on four implanted pacemakers with a saline phantom and correlated to a newly developed test method performed "in air" (without the phantom). Comparison of the simulator thresholds with tests performed in real WTMDs showed that the simulator is able to mimic the pacemaker interference. The interference thresholds found in the simulator indicate that pulsed magnetic fields are more likely to cause interference in pacemakers than sinusoidal fields. The security system simulator will help biomedical engineers, manufacturers of medical devices, and manufacturers of security systems to identify incompatible combinations of WTMDs and AIMDs early in the development stage.

Infrared thermographs (IRTs) implemented according to standardized best practices have shown strong potential for detecting elevated body temperatures (EBT), which may be useful in clinical settings and during infectious disease epidemics. However, optimal IRT calibration methods have not been established and the clinical performance of these devices relative to the more common non-contact infrared thermometers (NCITs) remains unclear. In addition to confirming the findings of our preliminary analysis of clinical study results, the primary intent of this study was to compare methods for IRT calibration and identify best practices for assessing the performance of IRTs intended to detect EBT. A key secondary aim was to compare IRT clinical accuracy to that of NCITs. We performed a clinical thermographic imaging study of more than 1000 subjects, acquiring temperature data from several facial locations that, along with reference oral temperatures, were used to calibrate two IRT systems based on seven different regression methods. Oral temperatures imputed from facial data were used to evaluate IRT clinical accuracy based on metrics such as clinical bias (Δcb), repeatability, root-mean-square difference, and sensitivity/specificity. We proposed several calibration approaches designed to account for the non-uniform data density across the temperature range and a constant offset approach tended to show better ability to detect EBT. As in our prior study, inner canthi or full-face maximum temperatures provided the highest clinical accuracy. With an optimal calibration approach, these methods achieved a Δcb between ±0.03 °C with standard deviation (σΔcb) less than 0.3 °C, and sensitivity/specificity between 84% and 94%. Results of forehead-center measurements with NCITs or IRTs indicated reduced performance. An analysis of the complete clinical data set confirms the essential findings of our preliminary evaluation, with minor differences. Our findings provide novel insights into methods and metrics for the clinical accuracy assessment of IRTs. Furthermore, our results indicate that calibration approaches providing the highest clinical accuracy in the 37–38.5 °C range may be most effective for measuring EBT. While device performance depends on many factors, IRTs can provide superior performance to NCITs.

Non-contact infrared thermometers (NCITs) are being widely used during the COVID-19 pandemic as a temperature-measurement tool for screening and isolating patients in healthcare settings, travelers at ports of entry, and the general public. To understand the accuracy of NCITs, a clinical study was conducted with 1113 adult subjects using six different commercially available NCIT models. A total of 60 NCITs were tested with 10 units for each model. The NCIT-measured temperature was compared with the oral temperature obtained using a reference oral thermometer. The mean difference between the reference thermometer and NCIT measurement (clinical bias) was different for each NCIT model. The clinical bias ranged from just under − 0.9 °C (under-reporting) to just over 0.2 °C (over-reporting). The individual differences ranged from − 3 to + 2 °C in extreme cases, with the majority of the differences between − 2 and + 1 °C. Depending upon the NCIT model, 48% to 88% of the individual temperature measurements were outside the labeled accuracy stated by the manufacturers. The sensitivity of the NCIT models for detecting subject’s temperature above 38 °C ranged from 0 to 0.69. Overall, our results indicate that some NCIT devices may not be consistently accurate enough to determine if subject’s temperature exceeds a specific threshold of 38 °C. Model-to-model variability and individual model accuracy in the displayed temperature were found to be outside of acceptable limits. Accuracy and credibility of the NCITs should be thoroughly evaluated before using them as an effective screening tool.

The finite difference time domain (FDTD) method in combination with a well established frequency scaling method was used to calculate the internal fields and current densities induced in a simple model of a pregnant woman and her foetus, when exposed to hand-held metal detectors. The pregnant woman and foetus were modelled using a simple semi-heterogeneous model in 10 mm resolution, consisting of three different types of tissue. The model is based on the scanned shape of a pregnant woman in the 34th gestational week. Nine different representative models of hand-held metal detectors operating in the frequency range from 8 kHz to 2 MHz were evaluated. The metal detectors were placed directly on the abdomen of the computational model with a spacing of 1 cm. Both the induced current density and the specific absorption rate (SAR) are well below the recommended limits for exposure of the general public published in the ICNIRP Guidelines and the IEEE C95.1 Standard. The highest current density is 8.3 mA m(-2) and the highest SAR is 26.5 microW kg(-1). Compared to the limits for the induced current density recommended in the ICNIRP Guidelines, a minimum safety factor of 3 exists. Compared to the IEEE C95. 1 Standard, a safety factor of 60 000 for the specific absorption rate was found. Based on the very low specific absorption rate and an induced current density below the recommended exposure limits, significant temperature rise or nerve stimulation in the pregnant woman or in the foetus can be excluded.

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Fever screening based on infrared (IR) thermographs (IRTs) is an approach that has been implemented during infectious disease pandemics, such as Ebola and Severe Acute Respiratory Syndrome. A recently published international standard indicates that regions medially adjacent to the inner canthi provide accurate estimates of core body temperature and are preferred sites for fever screening. Therefore, rapid, automated identification of the canthi regions within facial IR images may greatly facilitate rapid fever screening of asymptomatic travelers. However, it is more difficult to accurately identify the canthi regions from IR images than from visible images that are rich with exploitable features. In this study, we developed and evaluated techniques for multi-modality image registration (MMIR) of simultaneously captured visible and IR facial images for fever screening. We used free form deformation (FFD) models based on edge maps to improve registration accuracy after an affine transformation. Two widely used FFD models in medical image registration based on the Demons and cubic B-spline algorithms were qualitatively compared. The results showed that the Demons algorithm outperformed the cubic B-spline algorithm, likely due to overfitting of outliers by the latter method. The quantitative measure of registration accuracy, obtained through selected control point correspondence, was within 2.8 ± 1.2 mm, which enables accurate and automatic localization of canthi regions in the IR images for temperature measurement.

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