Fujitsu Cough in a Box

A team of researchers from The Alan Turing Institute and Royal Statistical Society, commissioned by the UK Health Security Agency have discovered that cough-analysing algorithms do a poor job of diagnosing COVID-19.

The team found that even the most accurate cough-detecting model performed worse than a model based on user-reported systems and demographic data, such as age and gender. 

One such model was Fujitsu’s Cough in a Box, an app funded to the tune of GBP 100,000 in 2021 by the UK’s Department of Health and Social Care to collect and analyse audio recordings of COVID-19 symptoms.

In October 2020, a team at the Massachusetts Institute of Technology (MIT) had found that, when new cough sounds were introduced, the algorithm accurately identified 98.5% of coughs from people who were confirmed to have COVID-19, including 100% of coughs from people with no symptoms.

The researchers had used technology that aimed to identify a signature noise, known as a biomarker, in a person’s cough that could be linked to a positive COVID-19 PCR test result. Their findings led to efforts to build an algorithmic-powered app to provide people with a cheap and easy method to test for COVID-19.