Use of non-contact infrared thermometers in rehabilitation patients: a randomized controlled study

A Comparative Study of Forehead Temperature and Core Body Temperature under Varying Ambient Temperature Conditions

When the ambient temperature, in which a person is situated, fluctuates, the body's surface temperature will alter proportionally. However, the body's core temperature will remain relatively steady. Consequently, using body surface temperature to characterize the core body temperature of the human body in varied situations is still highly inaccurate. This research aims to investigate and establish the link between human body surface temperature and core body temperature in a variety of ambient conditions, as well as the associated conversion curves.

METHODS

Plan an experiment to measure temperature over a thousand times in order to get the corresponding data for human forehead, axillary, and oral temperatures at varying ambient temperatures (14-32 °C). Utilize the axillary and oral temperatures as the core body temperature standards or the control group to investigate the new approach's accuracy, sensitivity, and specificity for detecting fever/non-fever conditions and the forehead temperature as the experimental group. Analyze the statistical connection, data correlation, and agreement between the forehead temperature and the core body temperature.

RESULTS

A total of 1080 tests measuring body temperature were conducted on healthy adults. The average axillary temperature was (36.7 ± 0.41) °C, the average oral temperature was (36.7 ± 0.33) °C, and the average forehead temperature was (36.2 ± 0.30) °C as a result of the shift in ambient temperature. The forehead temperature was 0.5 °C lower than the average of the axillary and oral temperatures. The Pearson correlation coefficient between axillary and oral temperatures was 0.41 (95% CI, 0.28-0.52), between axillary and forehead temperatures was 0.07 (95% CI, -0.07-0.22), and between oral and forehead temperatures was 0.26 (95% CI, 0.11-0.39). The mean differences between the axillary temperature and the oral temperature, the oral temperature and the forehead temperature, and the axillary temperature and the forehead temperature were -0.08 °C, 0.49 °C, and 0.42 °C, respectively, according to a Bland-Altman analysis. Finally, the regression analysis revealed that there was a linear association between the axillary temperature and the forehead temperature, as well as the oral temperature and the forehead temperature due to the change in ambient temperature.

CONCLUSION

The changes in ambient temperature have a substantial impact on the temperature of the forehead. There are significant differences between the forehead and axillary temperatures, as well as the forehead and oral temperatures, when the ambient temperature is low. As the ambient temperature rises, the forehead temperature tends to progressively converge with the axillary and oral temperatures. In clinical or daily applications, it is not advised to utilize the forehead temperature derived from an uncorrected infrared thermometer as the foundation for a body temperature screening in public venues such as hospital outpatient clinics, shopping malls, airports, and train stations.

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

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.

Comparative Analysis of Human Body Temperatures Measured with Noncontact and Contact Thermometers

Body temperature measurement is one of the basic methods in clinical diagnosis. The problems of thermometry—interpretation of the accuracy and repeatability of various types of thermometers—are still being discussed, especially during the current pandemic in connection with the SARS-CoV-2 virus responsible for causing the COVID-19 disease. The aim of the study was to compare surface temperatures of the human body measured by various techniques, in particular a noncontact thermometer (infrared) and contact thermometers (mercury, mercury-free, electronic). The study included 102 randomly selected healthy women and men (age 18–79 years). The Bland–Altman method was used to estimate the 95% reproducibility coefficient, i.e., to assess the degree of conformity between different attempts. Temperatures measured with contact thermometers in the armpit are higher than temperatures measured without contact at the frontal area of the head. The methods used to measure with contact thermometers and a noncontact infrared thermometer statistically showed high measurement reliability. In order to correctly interpret the result of measuring human body temperature, it is necessary to indicate the place of measurement and the type of thermometer used.

Regression model for predicting core body temperature in infrared thermal mass screening

With fever being one of the most prominent symptoms of COVID-19, the implementation of fever screening has become commonplace around the world to help mitigate the spread of the virus. Non-contact methods of temperature screening, such as infrared (IR) forehead thermometers and thermal cameras, benefit by minimizing infection risk. However, the IR temperature measurements may not be reliably correlated with actual core body temperatures. This study proposed a trained model prediction using IR-measured facial feature temperatures to predict core body temperatures comparable to an FDA-approved product. The reference core body temperatures were measured by a commercially available temperature monitoring system. Optimal inputs and training models were selected by the correlation between predicted and reference core body temperature. Five regression models were tested during the study. The linear regression model showed the lowest minimum-root-mean-square error (RSME) compared with reference temperatures. The temple and nose region of interest (ROI) were identified as optimal inputs. This study suggests that IR temperature data could provide comparatively accurate core body temperature prediction for rapid mass screening of potential COVID cases using the linear regression model. Using linear regression modeling, the non-contact temperature measurement could be comparable to the SpotOn system with a mean SD of ± 0.285 °C and MAE of 0.240 °C.