Plenary Lecture

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

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: ).

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