Scientists Develop Algorithm for Mobile Phones for Detecting Coronavirus Cough

An MIT team was developing AI models to analyze forced-cough recordings to see if they could detect signs of Alzheimer’s, a disease associated with not only memory decline but also neuromuscular degradation such as weakened vocal cords, MIT News reports.

When the coronavirus pandemic began to unfold, they wondered whether their AI framework for Alzheimer’s might also work for diagnosing Covid-19, as there was growing evidence that infected patients experienced some similar neurological symptoms such as temporary neuromuscular impairment.

MIT researchers have now found that people who are asymptomatic may differ from healthy individuals in the way that they cough. These differences are not decipherable to the human ear. But it turns out that they can be picked up by artificial intelligence.

In April, the team set out to collect as many recordings of coughs as they could, including those from Covid-19 patients. They established a website where people can record a series of coughs, through a cellphone or other web-enabled device. Participants also fill out a survey of symptoms they are experiencing, whether or not they have Covid-19, and whether they were diagnosed through an official test, by a doctor’s assessment of their symptoms, or if they self-diagnosed. They also can note their gender, geographical location, and native language, tip.ba reports, citing MIT News as the source.

To date, the researchers have collected more than 70,000 recordings, each containing several coughs. Around 2,500 recordings were submitted by people who were confirmed to have Covid-19, including those who were asymptomatic. The model identified 98.5 percent of coughs from people confirmed with Covid-19, and of those, it accurately detected all of the asymptomatic coughs.

Massachusetts Institute of Technology

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