Communications of the ACM
Computer Vision Tech Assesses Proper Mask Wearing
CCTV videos recorded staff entering a Boston hospital at two different entries.
Credit: Getty Images
Researchers from Brigham and Women's Hospital (BWH) and the Massachusetts Institute of Technology (MIT) used a computer vision algorithm in a system to measure adherence to and provide real-time feedback on mask-wearing to staff in a hospital.
The computer visualization system accurately detected the presence of mask adherence 100 percent of the time. Most participants reported a positive experience interacting with the system in a hospital. The team describes its work in a study published in BMJ Open.
"We recognize the challenges in ensuring appropriate mask usage and potential barriers associated with personnel-based notification of mask misuse by colleagues and here we describe a computer vision-based alternative and our colleagues' assessment of initial acceptability of the platform," says senior author C. Giovanni Traverso, M.D., of the Department of Medicine at BWH and in the Department of Mechanical Engineering at MIT.
Continued development of detection systems could provide a useful tool for preventing the spread of future airborne pathogens, the study says.
From Brigham and Women's Hospital
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