A Thermal-Optical Vision System for Identification and Localization of Symptomatic COVID‑19 Patients

Janabi-Sharifi, Farrokh | $49,953

Ontario Ryerson University 2020 NSERC Alliance COVID-19 Grant

According to World Health Organization (WHO) officials, timely identification and isolation of individuals infected with coronavirus is the key to containing the spread of the virus. With a shortage of testing kits, laboratory supplies, and personnel, temperature screening remains the primary approach to identifying high risk individuals. Thermal screening is non-invasive and gives immediate results for one of the primary symptoms of COVID-19. However, current methods of COVID‑19 public screening in ‘high traffic’ environments involve handheld temperature measurements which are considered inefficient, ineffective, and potentially risky to the screener and other acutely ill patients. Relying on only elevated skin temperatures (and not core temperatures) using distance measurement units might also give false positive classification results. It is hypothesized that fusing temperature measurements with body gait patterns (markers) would increase the accuracy of identifying symptomatic COVID -19 patients.

In this project, researchers from Ryerson University are partnering with Altius Analytics Labs to enhance the scalability and efficiency of COVID‑19 public screening and disease tracking. The main goal of the project is to develop, validate, and test a novel thermal-optical vision-based system to automatically identify symptomatic individuals on a large scale and track their movement through an environment. The outcome of this project will have a significant impact, protecting public health for the current pandemic and providing safeguards against a potential second wave. In addition to medical screening applications, results can be extended to the human factors industry as well. Finally, the project includes significant multidisciplinary training of highly qualified personnel (HQP) in established and emerging areas, including kinesiology, instrumentation, machine vision, signal processing, and machine learning. HQP will also have opportunities to work with the project partner and gain career relevant industrial experience.

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