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14May 2020

Researchers at Cornell University have designed an open-faced helmet that patients can wear to minimize the risks of SARS-CoV-2 transmission during dental procedures.

The helmet is connected to a medical-grade air filtration pump from the top to create a reverse flow of air, preventing cough droplets from exiting the helmet.

In a computer simulation using computational fluid dynamics, the helmet contained 99.6% of droplets emitted from coughing within 0.1 seconds.

“To put this into context, if we use the same air pump to create a negative pressure isolation room, it will take about 45 minutes to remove 99.0% of the airborne contaminants from the room,” said author Mahdi Esmaily Moghadam, PhD, assistant professor at Cornell Engineering.

Currently available personal protective equipment does not provide open face access while maintaining high effectiveness in containing contaminants, the researchers said.

Also, the researchers said, current solutions such as N95 masks and face shields, clinic room evacuation, negative pressure rooms, and air filtration systems are expensive but not highly effective or accessible.

The proposed helmet has a shell that is 1 mm thick and fully encloses the head with access and vacuum ports.

A nozzle is attached to the access port to extend the distance that droplets must travel against the flow and minimize their chance of escape through the opening, allowing for a smoother flow transition that reduces patient discomfort generated by flow turbulence.

And while a negative pressure room with air filtration can cost tens of thousands of dollars, the cost of each helmet could be as cheap as a couple of dollars if they are made to be disposable, the researchers said.

Medical-grade HEPA filter negative air machines designed to power the helmets are readily available and cost around a thousand dollars, the researchers added.

“Our next step is to refine the helmet design to have higher efficiency and broader application,” said author and mechanical engineering student Dongjie Jia, MS.

“After that, we plan to build prototypes of the helmet and perform experiments to verify our simulation predictions,” Jia said.

The simulation framework could be used as a fast and accurate way to study other particle-related phenomena and designs, the researchers said.