Plenary Lecture
Is Thermal Scanner Losing its Bite for Indoor Mass Blind
Fever Screening of Pandemic Influenza at Ports of Entry
and in the Community?
Associate Professor Eddie YK Ng
School of Mechanical and Aerospace Engineering
College of Engineering
Nanyang Technological University, 50 Nanyang Avenue,
Singapore 639798
Also: Adjunct NUH Scientist
Office of Biomedical Research, National University
Hospital of Singapore, Singapore
E-mail:
mykng@ntu.edu.sg
Abstract:
The outbreak of SARS-2003 and recent Influenza A
(H1N1-2009) has ignited studies and research (and even
the general public interests) in the field of infrared (IR)
imaging system for blind mass human fever screening to
control the spread of pandemic. The ideal device for
blind mass fever screening should be speedy,
non-invasive and be able to detect accurately those
people with fever. IR thermography has been used to
measure/indicate physiology variations, detect
inflammatory abnormalities and has the potential to
serve as a tool for mass screening of fever.
This talk reviews the IR fever screening systems, their
effectiveness to detect subjects with elevated body
temperature, followed by suggesting the performance and
environmental requirements in characterizing
thermography for possible fever screening due to
pandemic under indoor controlled environmental
conditions. The essential elements on performance
requirements include display color scale, display
temperature resolution, emissivity setting, screening
temperature range, workable target plane, response time
and selection of critical parameters such as uniformity,
minimum detectable temperature difference, detector
pixels and drift between auto-adjustment. It is critical
for thermal imagers to be able to identify febrile from
normal subjects accurately. Minimizing the number of
false positive and false negative cases, improves the
efficiency of the screening stations. False negative
results should be avoided at all costs, as letting an
infected person through the screening process may result
in potentially catastrophic results. Various statistical
methods such as linear regression, ROC analysis and
neural networks based classification were used to
analyze the temperature data collected from various
sites on the face on both the frontal and side profiles.
Two important conclusions were drawn from the analysis:
the best region on the face to obtain temperature
readings and the optimal pre-set threshold temperature
for the thermal imager. Finally, the talk however does
not preclude users from potential errors and
misinterpretations of the data derived from thermal
imagers.
Brief Biography of the Speaker: Eddie received
Ph.D. at Cambridge University with a Cambridge
Commonwealth Scholarship. His main area of research is
thermal imaging, human physiology, biomedical
engineering; computational turbomachinery aerodynamics,
microscale cooling problems, and CFD-CHT. He is an
Associate Professor in NTU. He has published more than
285 papers in refereed international journals (170),
international conference proceedings (70), textbook
chapters (18), and others over the years. Currently he
is an Editor for several journals such as JMMB, JBiSE,
CMJ, CFDJ, IJRM, ONMJ, etc. He has co-edited 4 books on
"Cardiac Pumping and Perfusion Engineering" by WSPC
Press (2007), "Imaging and Modelling of Human Eye" by
Artech House (2008), "Distributed Diagnosis and Home
Healthcare" (ASP, 2009) and "Performance Evaluation in
Breast Imaging, Tumor Detection and Analysis" by ASP
(in-press). Co-authored a book: "Compressor Instability
with Integral Methods" by Springer (2007). ( see
URL:http://www3.ntu.edu.sg/home/mykng ).
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