Covid or just a Cough? AI for Detecting Covid-19 from Cough Sounds

Published in KDNuggets

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Coughing and sneezing were believed to be symptoms of the bubonic plague pandemic that ravaged Rome in the late sixth century. The origins of the benevolent phrase, “God bless you,” after a person coughs or sneezes is often attributed to Pope Gregory I, who hoped that this prayer would offer protection from certain death. The flu-like symptoms associated with the plague co-occur during the current Covid-19 pandemic as well, to the extent where “normal” coughs draw immediate alarm and concern. However, in the present technologically advanced times, we need not resort only to prayers. We can now build sophisticated AI models that learn complex acoustic features to distinguish between cough sounds from Covid-19 positive and otherwise healthy patients.

Since the start of the Covid-19 pandemic, multiple AI research teams have been working towards leveraging AI to improve screening, contact tracing, and diagnosis. Most of the preliminary work involved CT or X-ray scans [1,2,3,4] to diagnose Covid-19 faster and, in some cases, with better accuracy than the RT-PCR test. Recently, AI researchers have started testing cough sounds for preliminary diagnosis or a  prescreening technique for Covid-19 detection in asymptomatic individuals. This is beneficial because, while someone may not have noticeable symptoms, the virus may still cause subtle changes in their body that may be detected by specific algorithms combining audio signal processing and machine learning. Cough-based audio diagnosis is non-invasive, cost-effective, scalable, and, if approved, could be a potential game-changer in our fight against Covid-19. This technology might also prove to have better efficacy than the standard strategy of prescreening for Covid-19 on the basis of temperature, especially for asymptomatic patients.
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