An artificial-intelligence (AI) algorithm was built at the Massachusetts Institute of Technology (MIT) lab suggests that ‘Covid cough’ could be inaudible to humans.
According to MIT scientist Brian Subirana, who co-authored the paper, published in the IEEE Journal of Engineering in Medicine and Biology, the way you produce sound changes when you have Covid, even if you're asymptomatic.
The report suggested that "Practical use cases could be for daily screening of students, workers and public, as schools, jobs, and transport reopen, or for pool testing to quickly alert of outbreaks in groups.”
Several organisations, including Cambridge University, Carnegie Mellon University and UK health start-up Novoic, have been working on similar projects.
“In July, Cambridge's Covid-19 Sounds project reported an 80% success rate in identifying positive coronavirus cases based on a combination of breath and cough sounds. By August, it had 459 cough and breath sample sounds submitted by 378 members of the public. But the MIT lab has collected about 70,000 audio samples each containing a number of coughs. Of those, 2,500 are from people with confirmed cases of coronavirus,” the BBC reported.
In tests, it has said to have achieved a 98.5% success rate among people who had received an official positive coronavirus test result, rising to 100% in those who had no other symptoms. The researchers require a regulatory approval to develop it into an app.
