Texas Tech University researchers have developed an algorithm that uses eye surface temperature measured by an infrared camera to estimate core body temperature. The algorithm is accurate to within 0.0035-0.045°C across a range of thermal resolutions and environmental conditions. It has potential applications in forensic science, clinical medicine, occupational health, and veterinary medicine as a noninvasive way to monitor core temperature. Further clinical studies are needed to fully validate the accuracy of the algorithm.

1. New Technology to Estimate
Core Body Temperature
Senay Tewolde, Ming Chyu, and Kevin Long
linkedin.com/in/senaytewolde

2. Texas Tech University researchers have
developed an algorithm that uses eye
surface temperature to estimate the
core body temperature behind the eye
(eye socket temperature).

3. Clinical Contributions

4. The algorithm has a potential for a
wide range of applications
regardless of environmental &
physiological conditions.

5. • Forensic Science: Estimate time of death in
forensic practice
• Clinical Medicine: Diagnose hyper- and
hypothermia; determine clinical death and
biological death; screen infectious diseases
without physical contact
• Occupational Health: Monitor body temperature
of workers, such as firefighters, for heat stress
• Veterinary Medicine: Monitor temperature of
animals, such as cows, for febrile disease, estrus
and onset of calving without contacting the
animal

6. Convenient and noninvasive.
Easy to operate and has
potential to be easily accessible,
even from a hand-held device
that has access to IR camera.

7. How the Algorithm
Works

8. The core body temperature
estimation algorithm is based on
four computational frameworks.

9. A pattern search
algorithm based on
asynchronous
Generating Search
Set (GSS) method
HOPSPACK SUNDANCE
The process
continues until the
minimum objective
target value is
satisfied.
Image Acquisition
Mapping
Inverse Analysis & Optimization
Given
• Main Code
(Sundance)
• Input file name
• Output file name
• Tag #
Image Processing

10. A pattern search
algorithm based on
asynchronous
Generating Search
Set (GSS) method
HOPSPACK SUNDANCE
The process
continues until the
minimum objective
target value is
satisfied.
Image Acquisition
Mapping
Inverse Analysis & Optimization
Image Processing

11. Algorithm Accuracy

12. The algorithm has consistently
demonstrated its capability of
accurately estimating the core
body temperature from a wide-
range of thermal resolutions.

13. For a thermal resolution <0.04 –
0.07K, the temperature was
estimated at 310.3K with ±0.0035 -
±0.045K variability.

14. Even though reduction in the noise-
effect slightly improved the
temperature variation, no significant
changes were observed in the nominal
temperature values.

15. Clinical Facts

16. Normal Core body temperature
varies from 36.8 to 37.7°C,
depending on:
• Measurement Site
• Gender
• Age
• Methods of Measurements
• Invasive Method
• Noninvasive Method

17. Accurate monitoring of core body
temperature typically requires
invasive measurement at different
sites in a clinical setting.
While accurate, invasive methods are
inconvenient and associated with
complications.

18. Core body temperature can also be
measured using noninvasive methods.
However, the measurement accuracy
depends on operator technique,
patient anatomy, and other inherent
factors.

19. This algorithm is convenient, accurate, and
noninvasive. The method is easy to operate
and has potential to be easily accessible,
even from a hand-held device that has
access to IR camera.
Rigorous clinical study will be required to
validate the results of the algorithm.
New Method to Measure Core Body
Temperature