The researchers say it could be used in a smartphone app to provide a more comfortable form of detecting the virus than eye-watering swab tests. The tool, named DeepCough3D, uses AI to analyze audio samples of coughs in frequencies that humans can’t hear. The researchers tested it on over 8,000 samples of people coughing in hospitals in Spain and Mexico since April 2020. Around 2,000 of the patients were COVID-19 positive, while the remainder had tested negative. DeepCough3D proved 98% accurate at identifying whether the samples were positive or negative. [Read: How do you build a pet-friendly gadget? We asked experts and animal owners] Lead researcher Dr Javier Andreu-Perez said the tool could “prove a real game-changer” in how we combat the pandemic: DeepCough3D is one of numerous attempts to diagnose COVID-19 by listening to coughs. Notably, MIT researchers recently developed an algorithm that successfully detected around 98% of COVID-19 infections by people with COVID-19. However, the Essex University team say their research stands out from other studies because it’s proven highly accurate at detecting the infection in thousands of clinically-validated sample that were tested by certified laboratories. They say that previous studies used mostly crowdsourced samples found online or only a small quantity of clinically-validated samples. The researchers also used the tool to classify coughs into three severity levels, which could help healthcare professionals allocate resources such as ventilators. They now plan to conduct interventional studies with the tech and work towards a wider release and certification of the tool. You can read the study paper in the journal IEEE Transactions on Service Computing.
