Performance characterization of non-contact infrared thermometers (NCITs) for forehead temperature measurement

Sullivan, Stacey J. L.; Seay, Nathanael; Zhu, Liang; Rinaldi, Jean E.; Hariharan, Prasanna; Vesnovsky, Oleg; Topoleski, LD Timmie

doi:10.1016/j.medengphy.2021.05.007

Cited by 7 publications

(9 citation statements)

References 5 publications

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“…Previous studies have reported that the ambient temperature has a certain impact on the accuracy of NCIT readings, 21 , 37–40 which is consistent with our results. We found that the accuracy of NCIT measurements at the four surface sites was significantly reduced when the temperature was lower than 18°C, and further decreased as the ambient temperature dropped to 14°C.…”

Section: Discussionsupporting

confidence: 93%

“… 32–35 These differences may be attributed to the temperature reduction caused by sweat on the forehead or temporal areas. 36 , 37 Furthermore, the forehead and temple are typically exposed to ambient temperatures, whereas the neck is often concealed by the collar. The neck is also located near the carotid artery and is, thus, closer to the body’s core while the wrists are located at the extremities so that the blood supply provides far less heat than the neck.…”

Section: Discussionmentioning

confidence: 99%

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Reliability of Non-Contact Infrared Thermometers for Fever Screening Under COVID-19

Lai¹,

X²,

Wang³

et al. 2022

RMHP

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Purpose Fever is one of the most typical clinical symptoms of coronavirus disease 2019 (COVID-19), and non-contact infrared thermometers (NCITs) are commonly used to screen for fever. However, there is a lack of authoritative data to define a “fever” when an NCIT is used and previous studies have shown that NCIT readings fluctuate widely depending on ambient temperatures and the body surface site screened. The aim of this study was to establish cut-off points for normal temperatures of different body sites (neck, forehead, temples, and wrist) and investigate the accuracy of NCITs at various ambient temperatures to improve the standardization and accuracy of fever screening. Patients and Methods A prospective investigation was conducted among 904 participants in the outpatient and emergency departments of Chengdu Women’s and Children’s Central Hospital. Body temperature was measured using NCITs and mercury axillary thermometers. A receiver operating characteristic curve was used to determine the accuracy of body temperature detection at the four body surface sites. Data on participant characteristics were also collected. Results Among the four surface sites, the neck temperature detection group had the highest accuracy. When the neck temperature was 37.35°C as the optimum fever diagnostic threshold, the sensitivity was 0.866. The optimum fever diagnostic thresholds for forehead, temporal, and wrist temperature were 36.65°C, 36.65°C, and 36.75°C, respectively. Moreover, triple neck temperature detection had the highest sensitivity, up to 0.998, whereas the sensitivity of triple wrist temperature detections was 0.949. Notably, the accuracy of NCITs significantly reduced when the temperature was lower than 18°C. Conclusion Neck temperature had the highest accuracy among the four NCIT temperature measurement sites, with an optimum fever diagnostic threshold of 37.35°C. Considering the findings reported in our study, we recommend triple neck temperature detection with NCITs as the fever screening standard for COVID-19.

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Section: Discussionsupporting

confidence: 93%

Section: Discussionmentioning

confidence: 99%

Reliability of Non-Contact Infrared Thermometers for Fever Screening Under COVID-19

Lai¹,

X²,

Wang³

et al. 2022

RMHP

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“…During our clinical study, two different IRTs and six models of NCITs were used to collect temperature data from each subject. The laboratory and clinical accuracy of these six models of NCITs has been analyzed in references [ 56 ] and [ 45 ] respectively. Laboratory results indicate that five of the six NCIT models did not meet the laboratory acceptance criterion of ±0.3 °C recommended by the ASTM E1965-98:2016 standard [ 33 ].…”

Section: Resultsmentioning

confidence: 99%

Infrared Thermography for Measuring Elevated Body Temperature: Clinical Accuracy, Calibration, and Evaluation

Wang

Zhou

Ghassemi

et al. 2021

Sensors

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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.

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“…At present, the traditional method for detecting temperature measurement errors in pressure thermometers mainly involves simultaneously entering the test environment, pressure thermometer, and standard mercury thermometer into a constant temperature bath to maintain a stable reading of the two thermometers, and finding temperature measurement errors in pressure thermometers through different methods [3]. However, traditional temperature measurement error detection results often do not analyze the accuracy of the detection, and directly weigh and sum all calculation results to obtain the final temperature measurement error [4]. This may result in the final temperature measurement error result being too far from the actual error result, thereby affecting the judgment of the temperature measurement error of the pressure thermometer.…”

Section: Introductionmentioning

confidence: 99%

Hall sensor-based pressure thermometer temperature measurement error detection

Wang,

Dou,

Sang

et al. 2024

Ninth International Symposium on Sensors, Mechatronics, and Automation System (ISSMAS 2023)

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The current conventional pressure thermometer temperature measurement error detection method mainly realizes detection by calculating the fixed error of temperature measurement, which leads to poor detection effect due to the lack of analysis of the uncertainty in the temperature measurement process. Therefore, based on Hall sensors, research has been conducted on the detection method of temperature measurement errors in pressure thermometers. Firstly, the uncertainties in different temperature measurement scenarios are analyzed and combined, and the temperature measurement error detection device is constructed. Hall sensors are used to judge the stability of the thermometer temperature values in the thermostat tank, and the actual temperature error is calculated by combining the deviation values brought by the uncertainties. In the experiment, the proposed method is tested for the accuracy of temperature measurement error detection. The experimental results show that the proposed method has a low misjudgment rate and has a more excellent detection effect when the temperature measurement error of the pressure thermometer is detected by the proposed method.

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Performance characterization of non-contact infrared thermometers (NCITs) for forehead temperature measurement

Cited by 7 publications

References 5 publications

Reliability of Non-Contact Infrared Thermometers for Fever Screening Under COVID-19

Reliability of Non-Contact Infrared Thermometers for Fever Screening Under COVID-19

Infrared Thermography for Measuring Elevated Body Temperature: Clinical Accuracy, Calibration, and Evaluation

Hall sensor-based pressure thermometer temperature measurement error detection

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