Elsevier

Microvascular Research

Volume 68, Issue 2, September 2004, Pages 104-109
Microvascular Research

Analysis of IR thermal imager for mass blind fever screening

https://doi.org/10.1016/j.mvr.2004.05.003Get rights and content

Abstract

Background: Obtaining meaningful temperature for the human body requires identifying a body site that will provide reliable data across a large population. It is important to understand that skin temperature does not solely depend on body-core temperature and may be affected by other physiological and environmental factors. Currently, there is lack of empirical data in correlating facial surface temperature with body core temperature. Present IR systems in use at airports/immigration checkpoints have not been scientifically validated particularly in regards to the false-negative rate. As a result, they may create a false sense of security by underestimating the number of febrile (and possibly infected) individuals. This article evaluates the effectiveness of thermal scanner when it is being used for mass blind screening of potential fever subjects such as SARS or bird flu patients. Methods: Bio-statistics with regression analysis and ROC is applied to analyse the data collected (502) from the SARS hospital in Singapore and conclusive results are drawn from them. The results are vital in determining two very important pieces of information: the best and yet practical region on the face to take readings and optimal pre-set threshold temperature for the thermal imager. Results: (1) The thermal scanner can be used as a first line tool for the mass blind screening of hyperthermia, (2) the readings from the scanner suggest good correlation with the ear temperature readings, (3) an imager temperature threshold should be determined by the environmental factors, outdoor condition in particular, the physiological site offset and the performance characteristics of thermal imager to warrant the most accurate and reliable screening operation. Conclusions: The analysis suggested that the thermal imager used holds much promise for mass blind screening when the readings from a specific region have a good correlation with the ear temperature. From the regression analysis, the best reading is taken from the maximum temperature in the eye region, followed by the maximum temperature in the forehead region. With ROC analysis, a randomly selected individual from the fever group has a test value larger than that for a randomly selected individual from the normal group in 97.2% of the time. The test can distinguish between the normal and febrile groups and an optimum threshold temperature for the thermal imager can be found. The pre-set threshold cut-off temperature for the current thermal imager was found to be 36.3°C with reference to the associated environmental condition. Any temperature readings that exceed this reading will trigger off the alarm and a thermometer will be used to verify the whether the person is having fever.

Introduction

The cardinal symptoms of SARS and bird flu are fever de Jong et al., 1997, Ksiazek et al., 2003, Peris et al., 2003, Rota et al., 2003 and this has led to temperature monitoring being practised at healthcare institutions, public areas and private establishments where crowds are expected. These fever-screening stations employ personnel to take the aural or oral temperatures so as to pick out those with fever and send them for further clinical evaluation for SARS and hence curb community spread of the disease. Oral and aural temperature measurements are accurate but are fairly “invasive”, time-consuming, labour-intensive and skill-dependent. The ideal device for fever screening should be speedy, non-invasive and be able to detect accurately those with fever with minimal inconvenience and disruption of human traffic. As a first line of defense, infrared (IR) thermal imaging has the potential to fulfil these functions and can serve as a tool for mass screening for fever. However, there is currently lack of scientific evidence to support this application. As quoted in the Canada National Post (September 24, 2003): “SARS scanners praised as placebo. Health Canada report: Cost $2 million, of the 462,000 people screened in the first full month of operation, the machines found 341 had fevers, but uncover no SARS cases, yet ‘build confidence’”. Current IR systems in use at various boarder checkpoints have not been scientifically validated particularly in regards to the false-negative rate. As a result, they may create a false sense of security by underestimating the number of febrile (and possibly infected) individuals. The unadjusted mode threshold temperature setting in a thermal imager needs to correct the difference between the skin and core body temperatures. It then has to take into account the effects of ambient conditions and the thermal imager's performance parameters.

This paper studies two possible spots on the face (forehead vs. inner corner region around eyes, other parts are either mostly covered or too inappropriate to scan) which yield IR skin temperatures that correlate/proxy with the core body temperature (benchmark with averaged both ears temperature, fever if ≥37.7°C in an adult using Braun Thermoscan IRT 3520+) for mass blind screening of fever to complement and not to replace the conventional thermometers.

Section snippets

Infrared camera technology

IR imaging is a physiological test only rather than an anatomical test such as X-rays or CT scan. The test is non-invasive, and the camera and operator can be positioned at a distance from the subject to be screened (Ng and Sudharsan, 2001). The images show areas of both inflammations (usually hot) and nerve dysfunction (usually cold) in the patterns produced. As such it is possible to use infrared thermography for the detection of suspected SARS or bird flu patients in a crowd as an early

Methodology

Data collection was carried out in the Emergency Department, Tan Tock Seng Hospital (the designated SARS center in Singapore), the Singapore Civil Defense Forces and Civil Aviation Authority to study the relationship between the forehead and eye-vicinity temperatures and actual body temperature. The total initial blind sample size collected was 85 ‘febrile’ and 417 ‘normal’ cases. The scanner used was the handheld radiometric IR ThermaCAM S60 FLIR system (FLIR Systems, 2004). The focal length

Regression data analysis

Eye range (max)
Dependent Y: Eye Range (Max)
Independent X: Ear Temp
Sample size = 310
Coefficient of determination = 0.5509
Residual standard deviation = 0.7061
- REGRESSION EQUATION -
Y = 4.1972 + 0.8509 X

Eye range (min)
Dependent Y : Eye Range (Min)
Independent X: Ear Temp
Sample size = 310
Coefficient of determination = 0.0672
Residual standard deviation = 1.7788
- REGRESSION EQUATION -
Y = 11.7507 + 0.5194 X

Forehead (max)
Dependent Y: Forehead (Max)
Independent X: Ear Temp
Sample size = 310
Coefficient of

Conclusion

The analysis suggested that the thermal imager used here holds much promise for mass blind screening when the readings from a specific region have a good correlation with the ear temperature. From the Regression Analysis, the best reading is taken from the maximum temperature in the eye region, followed by the maximum temperature in the forehead region. In addition, the pre-set threshold cut-off temperature for the current thermal imager has been found to be 36.3°C with reference to the

Acknowledgements

The first author would like to express his appreciation to members of the Ad hoc Technical Reference Committee on Thermal Imagers under Medical Technology Standards Division by SPRING, and Ministry of Health, TTSH of National Health Group, Singapore for sharing of their views and interests on “Thermal Imagers for Fever Screening-Selection, Usage and Testing”.

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