The rush to understand, predict and head off the Covid-19 outbreak has prompted technology researchers to deploy artificial intelligence to create tools that can determine whether a person is infected by analysing the sound of their cough, breathing or even the way they speak.
Currently, most of these efforts are at a stage when the researchers are gathering data – voice recordings paired of those with and without an infection – that will then be processed by machine learning algorithms.
“The sound of our voice (regardless of language), and the sounds we make when we breathe or cough change when our respiratory system is affected. The changes range from coarse, clearly audible changes, to minute changes — what we call “micro” signatures, that are not audible to the untrained listener, but are nevertheless present,” say researchers from Carnegie Mellon University (United States) about their tool, the COVID Voice Detector.
This tool uses a computer programme patented by a faculty member of the Pittsburg-based university’s LTI School of Computer Science and used for voice profiling work in law enforcement.
A similar effort has been launched by researchers at the University of Cambridge. The COVID-19 Sounds app, available as a Chrome or Firefox plugin now, is at present building a large, crowdsourced data set.
“Having spoken to doctors, one of the most common things they have noticed about patients with the virus is the way they catch their breath when they’re speaking, as well as a dry cough, and the intervals of their breathing patterns,” said Professor Cecilia Mascolo from Cambridge’s Department of Computer Science and Technology in an article published by the university.
“There are very few large datasets of respiratory sounds, so to make better algorithms that could be used for early detection, we need as many samples from as many participants as we can get. Even if we don’t get many positive cases of coronavirus, we could find links with other health conditions.”
A third such initiative is being carried out by Mumbai-based Wadhwani Institute for Artificial Intelligence. Launched on April 7, Wadhwani’s Cough Against Covid mobile application asks users to record the sound of their coughing and share an image of a test result if they are positive. The goal of the app, the institute said in a statement, is to “collect and analyse cough sounds to try and find the early signs of COVID-19 through AI”.
As the disease brings much of the planet to a halt, scientists and health experts have called for technology to play a bigger part in tackling the pandemic – which has grown too quickly for conventional containment tools to have an effect.
Software giants such as Apple and Google are working on a mobile phone-based contact tracing tool, a technology that several nations – including India with the Aarogya Setu app – have already deployed on their own.
Apart from AI and proximity-estimating tools meant to trace contacts, researchers are also looking at internet-of-things (IOT) devices such as smart thermometers. “A company called Kinsa comes up with heat maps of fever prevalence. Such tools can be useful in identifying large outbreaks that health authorities can respond to and direct testing and containment resources if need be,” said Bhramar Mukherjee, the head of biostatistics at the University of Michigan.
To be sure, these tools can only play a tertiary part in disease containment and surveillance efforts, which need the precision and accuracy of medical science.
The efforts also present a challenge for privacy, since connected devices data, personal audio recordings, location histories and health records need to be protected from profiteering and surveillance.
India’s Aarogya Setu app has been criticised by privacy advocates for collecting too much data, the use of which is governed by privacy policies that, they say, lacks transparency and accountability. The developers and the government of India have rejected the concerns.