Researchers from the Luxembourg Institute of Health has published their findings that vocal recordings of COVID-19 affected people could be used to monitor related symptoms of the disease and could become a novel and easy way for healthcare practitioners to provide at risk-patients with immediate help
The study was part of Predi-COVID Cohort and was published on 20 October 2022 in the scientific journal in PLOS Digital Health.
“Such a vocal biomarker could be integrated into future telemonitoring solutions, digital devices or in clinical practice. It offers an easily available, non-invasive tool to collect data that can be used from home. This could revolutionise the way patients are monitored, treated, and offer a much needed solution to relieve the burden from our healthcare systems,” said Dr Guy Fagherazzi, Director of the Department of Precision Health and Group Leader of the Deep Digital Phenotyping Research Unit, and the lead authour of the research publication.
According to the LIH, COVID-19 is a very heterogeneous disease and while some people are asymptomatic or exhibit only mild symptoms, others require hospital care or even result to death. For some patients, recovery is quick whereas others are chronically affected by Long COVID. The symptoms themselves also vary from person to person, ranging from fever, cough or body aches to loss of smell or nausea, and can appear alone or in any number of combinations. All of these factors make individual tailored medical care in response to the disease a necessity.
If physicians were able to remotely monitor mild cases and quickly assess the symptoms, this would certainly take some weight off the overall healthcare system, giving the priority to more severe cases, advocated LIH researchers.
The researchers obtained vocal recordings data via Predi-COVID, a study of people who tested positive for COVID-19. Participants regularly recorded themselves with their smartphones while reading a set text and then filled out a questionnaire about their symptoms and general health status. The 272 participants were then divided into two different groups: symptomatic and asymptomatic. Audio features were extracted and compared between the groups and the data was fed into an artificial-intelligence based model in order to predict the symptomatic status. Dr Fagherazzi explained that the researchers were able to “derive a vocal biomarker that could be used to accurately monitor symptomatic and asymptomatic individuals with COVID-19.”
This study is the first to use spoken voice recordings, as opposed to coughing or breathing, from various devices, and in a real world environment to identify COVID-19-related symptoms. According to the researchers, in the future, healthcare practitioners will be able to use this novel technology to both screen patients as well as track the progression of their symptoms via remote monitoring, using cheap and non-invasive tools like smartphones. It could also be a practical solution for monitoring Long COVID patients over an extended period in order to anticipate the evolution of their symptoms.
The full article is available online via: https://journals.plos.org/digitalhealth/article?id=10.1371/journal.pdig.0000112.
